MC Project

Here's how the largest fraternities earn and spend their millions

support@mycoding.id (Kristine Villarroel) — Wed, 07 Oct 2026 20:42:37 +0700

Students at the University of Michigan collect at the Sigma Chi fraternity home to gathering on a Saturday afternoon. : Jim West/UCG/Universal Images Group via Getty Images

Fraternities are a staple of the American university experience, whether it's for their social power on campus, sprawling alumni networks, or, at times, controversies.

But rearward the parties and secretive traditions are tax-exempt organizations that bring in millions of dollars all year.

Tax filings recommendation a partial glance into how the country's biggest fraternities acquire and expend their money.

Sigma Phi Epsilon Fraternity Inc., the national institution rearward among the largest fraternities throughout US university campuses, reported $10.6 myriad in income in financial 2025 and ended the twelvemonth alongside $29.4 myriad in net assets, according to public tax filings.

In comparison, Chi Phi Fraternity Inc., which has concerning 48 energetic chapters nationwide and is affiliated alongside Cornell's now-shuttered Chi Phi chapter, reported $1.8 myriad in income and $2.1 myriad in net resources in the identical year, per its tax filings.

Chi Phi declined a petition for comment from Business Insider.

Because many fraternities' local chapters, philanthropic foundations, and accommodation groups run independently, tax filings frequently display lone part of their broader, additional complex financial picture.

Take a appearance into how the US's largest fraternities acquire and expend their millions — and what small is known concerning their inner finances.

Every semester, thousands of students hurry to associate fraternities throughout the US.

College freshmen row up to hurry a fraternity at the University of Florida in 2016. Andrew Lichtenstein/Corbis via Getty Images

Recruitment brings new dues-paying members to Greek existence organizations, reaching thousands of students throughout university campuses.

At Miami University in Ohio, for example, 2,208 students registered for Greek-life recruitment in fountain 2026. This included 859 men who registered for recruitment alongside the school's 25 Interfraternity Council fraternities.

That identical semester, nearly one in three full-time undergraduate men at the school's chief Oxford evidence belonged to a fraternity.

Member dues are a important income source.

Members of the Sigma Alpha Mu division at the University of Southern California gathering in 2007. Ken Hively/Los Angeles Times via Getty Images

Member dues are frequently the most dependable origin of earnings for local fraternity chapters, but how much students pay and anywhere that prosperity goes can change extensively throughout campuses and chapters.

At the University of Arizona, members of the 20 fraternities in the Interfraternity Council pay an average of concerning $1,573 per semester in active-member fees, excluding housing, as of summer 2026, according to the university's Sorority and Fraternity Programs website. Including housing, the average is concerning $5,535 per semester.

The university adds that the organizations set and collect their own dues independently.

Contributions, including alumni gifts, can be another origin of earnings for national Greek organizations.

Pi Kappa Phi fraternity members greeted a freshman into their fraternity during Bid Day. Mark Leffingwell/Digital First Media/Boulder Daily Camera via Getty Images

In the financial twelvemonth ending June 2025, Sigma Alpha Epsilon Fraternity, the national organization's tax-exempt entity, reported $2.82 myriad in contributions, accounting for 29.4% of its $9.61 myriad in total revenue, according to its tax filings.

Program services, a tax category that mostly covers prosperity earned through activities connected to the organizations' purposes, are the largest income category for many of the biggest Greek-letter organizations in the US, Business Insider established in a assessment of national entities' tax filings.

Greek life's biggest resources can be its houses.

The Phi Gamma Delta fraternity home at the University of California, Berkeley, in 2024. Jay L Clendenin/Getty Images

Some of the most precious genuine asset in college towns throughout the US is located on the edges of campus, at the expansive properties that home fraternities and sororities.

In 2017, the Oklahoma State University division of Pi Kappa Alpha dedicated a new 32,500-square-foot, $12.8 myriad mansion (equivalent to $17.5 myriad today, according to the Bureau of Labor Statistics' cost increase calculator).

In a 2024 inspection of additional than 1,300 Greek properties throughout 50 campuses, Today's Homeowner established that Chi Psi had the highest average asset evaluation among the fraternities it surveyed, at $1.64 myriad per house.

National fraternities expend heavily on hazard management.

The USC Sigma Chi fraternity home in Los Angeles, California, in 2022. Carolyn Cole / Los Angeles Times via Getty Images

Delta Upsilon, a fraternity that describes itself as a "non-secret fraternity," stated in a 2026-27 document that loss-prevention fees accounted for 39% of its revenue, during defeat safety made up 38% of its expenses.

The annual fees paid by energetic members fund, among another expenses, liability coverage for bodily injury, asset damage, and personal-injury claims; accident safety that supplements members' health insurance; and coverage protecting board and officers against negligence claims.

Delta Upsilon did not react to a petition for comment from Business Insider.

A 2014 investigation by The Atlantic described in item how liability insurance, risk-management rules, and lawful defenses can form fraternity finances, as fine as how national organizations have sought to bounds their visibility to lawsuits through an extended coverage system.

Executive pay can additionally be a important disbursal for national organizations.

A fraternity home for the San Diego State University division of Sigma Alpha Epsilon. Bloomberg/Getty Images

SAE's 2025 filing lists CEO Steven Mitchell's compensation at $284,114, affirmative $8,523 in another compensation.

Sigma Alpha Epsilon did not react to a petition for comment from Business Insider.

Housing costs, including food, are a important expense, too.

A associate of Phi Kappa Tau at the University of Southern California moves belongings from the fraternity home to a new home on 'Frat Row.' Carolyn Cole / Los Angeles Times via Getty Images

For members, accommodation is among the draws and the most crucial aspects of Greek life.

Delta Upsilon says that, at chapters alongside houses that assist food, 60% of members' dues go toward housing-related costs, including home loan or rent payments, utilities, asset taxes and insurance, repairs, landscaping, cleaning, food, and salaries for galley personnel and home directors.

Maintaining a social existence on evidence can be a important prosperity item.

A assemblage of University of California, Berkeley students and parents during a fraternity gathering before a football equivalent against North Carolina State University in 2024. Jay L Clendenin/Getty Images

While it varies mostly between distinct organizations, the Delta Upsilon fraternity says that between 17% and 22% of its members' dues at chapters that have a house, depending on whether they assist food, go toward social costs, which may contain formals, date parties, tailgates, homecoming, social apparel, and events for alumni and parents, and are distributed at the chapter's discretion.

Another 8% to 11% of dues goes to local operational costs, including composites, agency supplies, recruitment events, elder gifts, dues-collection systems, promotion materials, intramurals, scholarly incentives, philanthropy events and contributions, and Interfraternity Council dues. That spending is additionally topic to division discretion.

Supporting alumni, including politicians, is another crucial expenditure.

Then-former President Donald Trump during a sojourn to the Alpha Gamma Rho fraternity in 2023. Jabin Botsford/The Washington Post via Getty Images

The Fraternity & Sorority Political Action Committee — additionally known as FratPAC — is among the governmental assistance arms of Greek life.

The commission shares a goal of "helping additional Greek alumnae get elected to the House or Senate for the archetypal time," and raised complete $900,000 in the 2023-24 ballot cycle. The bipartisan commission stated it donated to 97 legislative candidates, alongside 52% of finances going to Republican candidates and 48% going to Democratic candidates.

National tax filings are lone a small opening into the finances of Greek existence organizations.

A fraternity home on evidence at Dartmouth College in Hanover, New Hampshire, in 2021. Bloomberg/Getty Images

Many fraternities and their affiliated entities are tax-exempt, but the organizational construction and the separations among local chapters, national organizations, philanthropic and instructional foundations, and accommodation corporations can create the general financial landscape difficult to navigate.

For example, Sigma Phi Epsilon operates through distinct organizations and entities: the national fraternity itself; a separate educational foundation supporting instructional and grant programs; and a wholly owned national accommodation LLC subsidiary that supports chapters alongside asset management, operations, and renovations — whose income and resources are additionally reported under the national fraternity organization.

Some local chapters additionally have distinct tax-exempt entities, akin SigEp's housing corporation affiliated alongside its University of Georgia division — although tax and reporting structures can change by division and jurisdiction.

A spokesman for the fraternity told Business Insider that "undergraduate dues paid to the national institution are reinvested in the SigEp cognition through programs and services that advancement our mission," and that "generous alumni assistance complements those dues, assisting provision guidance development, pupil housing, and grant opportunities."

Looking lone at the national fraternity's tax filing offers a partial perspective of the organization's finances.

Google Opens Its SynthID Watermark Detector To The Public

support@mycoding.id (Matt G. Southern) — Wed, 07 Oct 2026 20:38:35 +0700

Google has opened its SynthID Detector to everyone. The tool checks image, video, and audio records for SynthID, Google’s invisible watermark for AI media, and is accessible globally in English starting today.

Pushmeet Kohli, VP of Science and Strategic Initiatives at Google DeepMind, announced the enlargement in a blog post. Google introduced an early version of the detector final year, and journalists, media professionals and researchers could associate a waitlist for access.

A social or satisfied squad can now inspect an depiction or clip for a SynthID watermark from Google or a partner before it goes into a article or campaign.

What The Detector Checks

The detector runs at synthid.com, anywhere you upload a document to inspect it. According to the post, it can inform whether a document was made alongside AI from Google or its partners, including OpenAI, NVIDIA, and Kakao.

The location says the watermarks are added throughout generative AI person products from those companies, afterward adds:

“This is not a broad AI detector. We can lone detect media from the complete companies, who have adopted SynthID technology.”

The location additionally asks for the best-quality copy of a document you have, saying that gives the most exact result.

What A Result Says

Google’s article presents a example video demonstrating the finding of “SynthID.” Its outcome panel displays “SynthID was detected” and states that “This media was made or edited alongside Google AI.” It additionally notes that the media “may have been edited additional since then.”

The site’s FAQ explains that “no indication is entirely robust” and advises “collecting multiple points of data before making a decision.”

Why This Matters

Since the detector’s outcome shows “made or edited,” a photo that has been touched up using Google’s AI and one that was created from scratch alongside it power the two be tagged the identical way. Plus, equal if a document comes rear without a watermark, it could motionless have been generated alongside AI by a business that doesn’t use SynthID.

Looking Ahead

Apple is the lone detector partner Google announced as coming soon, alongside no publish date. Google’s article lone references English and omits another languages.

Featured Image: Google. Source: Google.

Category News Tools

The Best Last-Minute Deals on Tablets and iPads During October Prime Day

support@mycoding.id (Daniel Oropeza) — Wed, 07 Oct 2026 20:30:00 +0700

Daniel is Lifehacker's Shopping Editor covering tech deals and reviewing TVs, headphones, speakers, and projectors. He earned his master’s in reporting from Columbia University and has reported for the Miami Herald. He lives in Atlanta.

October Prime Day is nearly over, and you have until tonight to shop for several pretty awesome deals. I've searched Amazon for the finest deals on tablets and vetted them alongside price tracking tools. While lone among the best tablets of 2026 made it onto the catalog below, all of these devices are worthwhile deals at their current prices.

Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025)

$399.00 at Amazon

$449.00 Save $50.00

Get Deal

Amazon Kindle Scribe 16GB 10.2" eReader & Notebook (Like-New Condition, Black)

$284.99 at Amazon

$359.99 Save $75.00

Get Deal

TCL Nxtpaper 14 256GB 14.3" Tablet With Pen and Case (Gray)

$329.99 at Amazon

$469.99 Save $140.00

Get Deal

XTEINK X4 Classic Pocket eReader, Ultra-Light 68g & 4.9mm Thin, Space Black

$69.99 at Amazon

$89.00 Save $19.01

Get Deal

Amazon Fire HD 10 10.1" Tablet (4GB RAM, 32GB, Black)

$72.99 at Amazon

$154.99 Save $82.00

Get Deal

Get Deal SEE 2 MORE

The 11th-gen iPad is $399 correct now

iPads were among the many tech products that went up in cost dramatically in 2026 because of an ongoing RAM crisis, so it's nice to see this example get a discount, equal if it's not that big. Right now, the iPad 11-inch alongside the A16 chip is $399 (originally $449). This is the 128 GB version, which is among the most affordable iPads. It supports the Apple Pencil, is brilliant and colorful, and is considered the best tablet for most people.

Other iPad deals:

Apple iPad Air 11-inch (M2) $799 (originally $1,249)
Apple iPad Air 11-inch (M4) $649 (originally $749)
Renewed Apple iPad 2021 (10.2-inch, Wi-Fi, 64GB) $184.26 (originally 463.55)

A like-new Kindle Scribe is nearly fractional the cost of a new one

Kindle Scribes are expensive—the 64GB can run for nearly fractional a grand—but you can get a "like-new" 64GB version for $319.99 correct now. The 16GB version is $284.99, but the upgrade in retention is value the $35 difference. It's improbable you'll discover a improved agreement on s like-new Scribe during this sale.

The TCL NXTPAPER 14 is $120 off

TCL started venturing into tablets in 2020, and their latest tablet, the NXTPAPER 14, came out this year. Right now, it's at its lowest cost ever: $329.99 (originally $469.99). This tablet has a 14.3-inch matte display alongside distinct viewing modes for reading, streaming video, and writing. While it's not the most portable because of the size, its design makes it versatile and ideal for group who desire a tablet that can do a bit of everything.

The Xteink X4 Classic pocket e-reader is fair $76

Pocket readers appear to be gaining fame lately, alongside additional companies making new models of these hyper-small study tablets. The Xteink X4 Classic is particularly small: At fair four inches (about the size of a credit card), you can fit comfortably into nearly any pocket. This is the second generation of the device, which came out in first September, and it's incredibly affordable: At $69.99 (originally $89), it's about fractional the cost of the entry-level Kindle.

The Fire HD 10 tablet is 53% off

Right now, the Amazon Fire HD 10 tablet is additional affordable than ever: It's currently 53% off, bringing its cost downward to a document low of $72.99. (Note that this agreement is for the type of the equipment alongside lock-screen ads.) While this tablet won't win any awards for offering the latest and finest specs, it's an amazing value for the price, and it can likely grip all the essential tasks you'd ask of a tablet.

Other tablet deals to consider:

Lenovo Idea Tab Pro Gen 2 Tablet + Pen & Folio Case $384.99 (originally $419.99)
Samsung Galaxy Tab S10 FE $384.99 (originally $549.99)
TCL TAB A1 Plus NXTPAPER Android Tablet $259.99 (originally $399.99)

FAQ for October Prime Day

When is Prime Day in October?

Amazon Prime Day is an annual event held in June or July. Amazon's October Prime Day event, known as Prime Big Deal Days, is a two-day transaction that starts Oct. 6 and ends on Oct. 7.

What do you think so far?

What goes on transaction during October Prime Day?

Since Prime Big Deal Days happens in the fall, you're apt to see additional deals on gaming and indoor gym equipment. Amazon has already announced several of the 35 categories that volition be on sale, including beauty, tech, kitchen, fashion, and home. Some brands Amazon has already mentioned are: Shark, Princess Polly, Soundcore by Anker, UGG, Nest New York, Sony, Tarte, Adidas, and Barefoot Dreams.

Is Prime Day formerly a year?

Prime Day happens all summer. Prime Big Deal Days (or October Prime Day) happens all October. Amazon's Big Spring Sale happens all spring.

Are tablets really cheaper on Prime Day?

Yes, there have been many tablets at record-low prices or matching their lowest cost ever, according to our cost tracking tools. Most of those are listed current in this roundup; others have arrive and gone. Prime Day is among the finest times to buy these types of high-tech devices.

What are the finest deals on tablets correct now?

The like-new Kindle Scribe and Fire HD 10 tablets are the finest deals accessible correct now. Both are awesome deals, but depending what you're looking for, one power activity improved for you.

Is there a transaction on Fire tablets for Amazon Prime Day?

Yes, and Amazon devices are anywhere you'll discover several of the finest deals. Right now, for instance, the like-new Kindle Scribe is a awesome agreement at $319.99.

Our Best Editor-Vetted Prime Day Deals Right Now

Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $179.00 (List Price $249.00)

Sony WH-1000XM5 — $198.00 (List Price $399.99)

Ring Indoor Cam Plus 2K Wired Security Camera (2-Pack, White) — $59.98 (List Price $119.98)

Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $399.00 (List Price $449.00)

Blink Outdoor 4 1080p 3-Camera Kit With Sync Module Core + Doorbell — $65.99 (List Price $259.98)

Ring 2nd Gen 2K Wired Video Doorbell With Chime (2026 Release) — $49.99 (List Price $114.98)

Fire TV Stick 4K Plus Streaming Player With Remote (2025 Model) — $37.99 (List Price $69.99)

Apple Watch Series 12 — $349.99 (List Price $399.00)

Deals are selected by our commerce team

Covering tech deals and reviewing TVs, headphones, speakers, and projectors.

ChatGPT’s ‘Intelligent UI’ update fills its responses with pictures, charts, and buttons

support@mycoding.id (Emma Roth) — Wed, 07 Oct 2026 20:10:42 +0700

Emma Roth

is a news author who covers the streaming wars, person tech, crypto, social media, and much more. Previously, she was a author and publishing company at MUO.

OpenAI is launching a new Intelligent UI characteristic in ChatGPT that allows the chatbot to answer your questions alongside interactive visuals. The update, which is rolling out to all users alongside GPT-6, gives ChatGPT the capability to merge a content reply alongside diagrams, charts, forms, tappable buttons, and more.

In a blog article explaining the change, OpenAI says it trained GPT-6 whenever to create interactive visuals complete text, as fine as how to format them in its response. An example shared by OpenAI shows how ChatGPT power display a diagram of a seven-speed bicycle if you ask concerning its design, complete alongside interactive buttons that emphasize distinct parts.

Another shows how ChatGPT can instruct you to perform Mahjong by generating visuals of all tile and placing them into categories that you can scroll through. You can additionally ask ChatGPT to create tools for distinct tasks, specified as a withdrawal funds calculator, retro game, or invoice splitter. It volition afterward create the tool in-line alongside its response.

OpenAI announced its first GPT-6 models final month, but now it’s bringing the Sol and Luna versions to ChatGPT. In supplement to enabling Intelligent UI, OpenAI says its GPT-6 allows ChatGPT to execute improved web searches and provision quicker, partial answers to users during it gathers information. The business notes that GPT-6 “showed stronger opposition to attempts to bypass its safety training” as well.

GPT-6 alongside Intelligent UI is rolling out globally to ChatGPT Plus, Pro, Business, and Enterprise users starting today, but volition develop to Go and liberated tiers on Thursday. While higher-tier subscribers volition acquire admission to the mid-range GPT-6 Sol model, Go and liberated users volition get to use the additional productive GPT-6 Luna.

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Emma Roth

The first Nvidia RTX Spark laptops cost up to $7,000

support@mycoding.id (Antonio G. Di Benedetto) — Wed, 07 Oct 2026 20:05:52 +0700

Antonio G. Di Benedetto

is a reviewer covering laptops and the occasional gadget. He spent complete 15 years in the photography industry before joining The Verge as a deals author in 2021.

The archetypal gathering of laptops powered by Nvidia’s new RTX Spark part are designed to vie alongside high-end MacBook Pros — and they’ve got several high-end prices to match.

The flagship Surface Laptop Ultra and RTX Spark laptops from Dell, Lenovo, MSI, HP, and Asus commencement as low as $2,599 for configurations alongside an 18-core CPU, 24GB of unified memory, and 512GB of storage. That’s near in cost to a likewise specced 14-inch MacBook Pro alongside M5 Pro chip, although Apple includes 1TB of storage. But the prices for the two RTX Spark and Apple laptops of way go much, much higher.

Of the pricing we’ve seen so far, a kitted-out Asus ProArt P16 RTX Spark laptop alongside a 20-core chip, 128GB of unified memory, and 2TB of retention expenses up to $6,999.99. We don’t yet cognize the complete breadth of configuration options for Microsoft’s Surface Laptop Ultra, as the preorder page lone has an email sign-up box to get updates, but a 48GB example on Best Buy expenses $3,999.99.

Wildly costly laptops aren’t really item new: you can configure a 16-inch MacBook Pro alongside M5 Max part to nearly $10,000 if you max out all options. But the archetypal volley of RTX Spark options are evidently aimed at the high-end flank of creators and local AI users. And RAMageddon certainly isn’t assisting create this any easier on peoples’ wallets.

Will they be value it? We’ll discover out soon. The Surface Laptop Ultra and another RTX Spark laptops are launching this duration — as first as October 16th.

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Antonio G. Di Benedetto

ICANN Reveals 2026 Round Applications for New Generic Top-Level Domains

support@mycoding.id (Adi Gunawan) — Wed, 07 Oct 2026 20:01:45 +0700

Today, the Internet Corporation for Assigned Names and Numbers (ICANN) published the catalog of applications received in the New Generic Top-Level Domains (gTLD) Program: 2026 Round, revealing the applied-for strings and applying entities. As required by community-developed guideline set onward in the Applicant Guidebook, the published data includes the applied-for chief strings and any applicable type or replacement strings, a list of disagreement sets (CSV format), and community portions of all application. The thorough listing can be established on the 2026 Round Application Publication and Statistics website.

"Reveal Day marks an crucial milestone for the next enlargement of the Domain Name System," stated Kurtis Lindqvist, President and Chief Executive Officer of ICANN. "These applications display how organizations about the earth are innovating new ways to build trusted online identities, assist their communities, and nexus alongside Internet users. ICANN remains focused on administering a fair, transparent, and predictable evaluation procedure restricted in the policies developed by our earth multistakeholder community."

Reveal Day 2026 Data Snapshot

The use submission opening was open from 30 April–12 August 2026. Highlights from the 2026 Round use data* include:

1,615 applications
333 brand applications
16 community-based applications
15 self-identified geographic name applications
51 applications submitted by Applicant Support Program applicants
16 applications from Africa
218 applications from Asia/Australia/Pacific
506 applications from Europe
11 applications from Latin America and the Caribbean
864 applications from North America
21 applications for Internationalized Domain Names
9 applications for variants. This is whenever an applicant applies for a cord that has another forms in distinct scripts specified as Arabic or Chinese.

*This snapshot reflects chief cord use data as of 7 October 2026. The final figure and types of applications volition be confirmed on String Confirmation Day.

Below is data on consequent milestones in the program through the end of the year.

Replacement Period: 8 October 2026 (00:01 UTC)–21 October 2026 (23:59 UTC)

Following Reveal Day, applicants that applied for a second-choice or substitute "replacement" cord whenever they submitted their gTLD use have two weeks in which they may choose to toggle from their chief applied-for cord to their replacement string. Applicants may toggle to the replacement cord lone during this period, and lone if their replacement cord is eligible. If the replacement cord is identical to another applied-for chief string, or another replacement string, it cannot be used. Applicants have to be conscious that replacement strings could end up in disagreement in the afterward stages of the program (e.g., hence of a singular/plural notification or String Confusion Objection). More data on the Replacement Period is accessible on this webpage.

String Confirmation Day: 17 November 2026

Following the String Replacement Period, a final catalog of all the applied-for gTLD strings is published on String Confirmation Day, as fine as an updated catalog of disagreement sets. String Confirmation Day marks the commencement of the Community Input and Objections Period and the final 10 days during which applicants can retreat their use to obtain a 65 percent refund of the gTLD evaluation fee paid. To obtain a refund during this refund window, a petition must be submitted by 23:59 UTC on 27 November 2026. More data on refunds and timing is accessible on this webpage.

Community Input and Objections Period: 17 November 2026–16 March 2027

The ICANN community and members of the community volition have an chance to provision feedback on applications following String Confirmation Day. Input may arrive via use comments, Governmental Advisory Committee Member Early Warnings, singular/plural notifications, or objections using the Application Comment Forum. More information, including particulars on additional objections periods, can be established on this webpage.

ICANN Office Closure

2026 Round operations volition be paused during ICANN's end-of-year agency closure from 1:00 UTC on 19 December 2026 until 16:00 UTC on 4 January 2027. This intermission has been factored into the Community Input and Objections Period to justify that applicants, the community, and the community keep the complete amount of allotted period to provision input or react to objections. Additional particulars volition be made accessible in the coming months.

Prioritization Draw: 2027

The Prioritization Draw sets the command that applications and disagreement sets volition be processed following the decision of the String Evaluation Stage. The String Evaluation Stage is the procedure of reviewing applied-for gTLD strings (and their allocatable type strings) to justify they encounter the requirements of the New gTLD Program; all strings are reviewed concurrently. As use and disagreement set handling volition not commencement until following the decision of the String Evaluation Stage (expected to final 180 days), the Prioritization Draw volition obtain location on a to-be-determined date in the archetypal fractional of 2027. Applicants cannot act the Draw in individual but can prosecute the live event virtually. More data volition be provided at a afterward date.

Future 2026 Round Milestones

ICANN volition continue to activity on the preparedness and confirmation of timelines for afterward 2026 Round milestones, specified as the publish of String Evaluation Results and the commencement dates for Applicant and Application Evaluation and disagreement resolution, and volition communicate them accordingly.

Additional Resources

More data on the key phases of the use lifecycle can be established on the 2026 Round Applicant Journey webpage. Be certain to inspect the program's News and Announcements page frequently for the latest news and updates. This data additionally volition be sent immediately to entities that have submitted an use in the TLD Application Management System.

Why Legacy PPC Account Structures Are Sabotaging Your Smart Bidding Strategy

support@mycoding.id (Sarah Stemen) — Wed, 07 Oct 2026 20:00:23 +0700

Search advertisers spent years construction granular document structures akin Single Keyword Ad Groups (SKAGs), equipment splits, and secluded equivalent types. That flat of micro-management made complete awareness whenever managers manually adjusted bids row by line. Modern ad platforms run on automated bidding systems that run under entirely distinct operational rules. Smart Bidding feeds on conversion quantity and indication history.

When an document spreads constricted traffic throughout dozens of campaigns, there’s not going to be adequate data inside all run for bidding to optimize effectively. Fragmenting traffic throughout dozens of campaigns can depart automated bidding alongside too small data in all run to create powerful decisions.

If an ad document feels volatile, stays stuck in perpetual learning phases, or struggles to scale, underlying structural fragmentation is normally the base cause.

Why Legacy Structures Harm Modern Algorithms

Single keyword ad groups were designed for manual control. Smart Bidding requires conversion volume, data velocity, and indication elasticity throughout the account. In my experience, campaigns typically need at smallest 30 conversions per duration at the run flat for algorithms to accurately measure contextual signals akin device, location, time, and intent.

Hyper-fragmentation spreads crucial quantity throughout lean ad groups, causing predictable bottlenecks:

RSA Machine Learning Bottlenecks: Responsive Search Ads depend on uninterrupted belief and conversion data to test header combinations. Sparse traffic keeps imaginative evaluation stalled.
Semantic Friction: Modern algorithms equivalent on search intent fairly than exact content strings. Dense cross-negation designed to keep rigid keyword isolation actively blocks high-converting long-tail queries.
Operational Overhead: Managing hundreds of lean ad groups consumes period on low-impact care alternatively of high-leverage growth drivers akin recommendation scheme and imaginative testing.

How Excessive Segmentation Fragments Data

Fragmenting an document divides conversion speed and prosperity liquidity, restricting how efficiently chief and algorithms operate:

Widened Statistical Noise: Spreading 60 monthly conversions throughout 12 lean campaigns leaves all alongside five sales. The algorithm cannot differentiate genuine trends from random variance, triggering erratic bid overcorrections.
Budget Traps and Artificial Caps: Assigning fixed regular budgets to micro-campaigns traps chief in silos. High-intent traffic surges can cap out a small prosperity first during unspent finances sit idle in quiescent segments nearby.
Flawed Optimization Decisions: Low-volume campaigns alongside impermanent elevated CPAs frequently guide managers to intermission keywords according to raw variance fairly than true achievement trends.

Common culprits contain duplicating keywords throughout secluded exact, phrase, or broad campaigns, splitting desktop and mobile, or construction distinct campaigns for insignificant geographic radiuses.

The Cost Of Low-Volume Data Starvation

When campaigns deficiency adequate conversion density, Smart Bidding relies on statistical approximation alternatively of true optimization:

Performance Swings: A sole conversion causes the bidding algorithm to overbid wildly, during a quiescent day chokes off traffic entirely.
Permanent Calibration: Campaigns remain trapped in learning phases, never reaching predictable achievement baselines.
Lost Auction Share: Facing elevated uncertainty, the scheme bids conservatively, missing out on high-intent buyers and depressing general conversion volume.

Consolidation gives the algorithm the data quantity needed to stabilize bids and lesser acquisition expenses without requiring new ad copy or keywords.

Where Consolidation Goes Too Far

Simplification does not average flattening an complete document into a sole campaign. Consolidation goes too far whenever it erases structural distinctions that indicate essential endeavor differences, changeable gain margins, or distinct revenue cycles.

Merging high-margin and low-margin products into a sole mark forces the algorithm toward an average that underserves top-performing inventory. Similarly, collapsing brand and non-brand keywords into the identical run muddies intent signals that foretell vastly distinct conversion behaviors.

High-Impact Preserved Segmentations

Some structural splits remain essential under Smart Bidding since they portray center strategic or financial variances:

Differing Business Objectives: Lead generation and straightforward ecommerce revenue necessitate distinct conversion goals and bidding strategies.
Margin Variance: Products or services alongside distinct gain margins necessitate autonomous Target ROAS or Target CPA targets to defend profitability.
Strategic Geography: Separate campaigns are necessary whenever regions necessitate dedicated budgets, localization, or distinct market positioning.
Divergent Funnel Intent: Traffic driving to basically distinct landing experiences, akin a high-friction demo petition versus a low-friction trial, should remain divided to maintain relevance.

The regulation is straightforward: If splitting a run changes your underlying endeavor strategy, budget, or imaginative experience, keep it separate. If it lone changes how identical client journeys are tagged in reports, consolidate.

How Platform Automation Changes the Stakes

The enlargement of features akin AI Max accelerates this transition. Broadening keyword matching, auto-generating content variations, and applying campaign-level automation eliminate the operational burden manual segmentation formerly filled.

Advertisers positioned to advantage most from phase automation are those who consolidate indication bases, align conversion tracking alongside income outcomes, and reserve run segmentation exclusively for true strategic boundaries.

Action Plan: Focus On Signal Quality Over Granular Control

Modern accounts necessitate prioritizing data density and indication norm complete bequest authority habits:

Audit: Identify SKAGs, duplicated match-type campaigns, and low-volume segments fragmenting document data.
Consolidate: Merge redundant structures during preserving splits dictated by margin, objective, or distinct landing experiences.
Test and Scale: Roll out a consolidated construction throughout a sole merchandise row or run collection to benchmark stability and conversion quantity improvements.

Transitioning distant from bequest splits is a essential necessity for managing ad accounts efficiently in an AI-driven hunt ecosystem. By restructuring your document about conversion quantity and endeavor strategy, you provision device learning algorithms alongside the indication density required to discover high-value auction opportunities.

More Resources:

Featured Image: Elenyska/Shutterstock

Category Paid Media Paid Media Strategy PPC

Meta and Microsoft Limit Employee Use of Claude AI Tools

support@mycoding.id (Adi Gunawan) — Wed, 07 Oct 2026 19:49:40 +0700

Meta and Microsoft have commenced a important decrease in employee use of Anthropic’s Claude AI as they pivot towards their own proprietary coding instruments, as reported on October 5 by The Information.

This strategic modification prioritizes inner expenditure and workforce processes, fairly than discontinuing client admission to Claude through Microsoft’s offerings.

This passage underscores the expanding imperative to oversee AI expenditures as coding assistants rotate into integral to regular application operations.

While the two corporations continue to be significant clients of Anthropic, they additionally discover themselves in competition alongside the firm. Their actions indicate a convergence of AI investment, merchandise strategies, and authority complete developer resources.

Microsoft Reduces AI Expenditure Allowances

Microsoft had earlier anticipated that inner expenditures on Anthropic technology would exceed $1 milliard annually.

However, this evaluation has diminished by complete a third consequent to management’s directive for workforce to curtail their use of Claude and to increasingly clasp Microsoft tools, specified as GitHub Copilot and OpenAI frameworks.

Within Microsoft’s haze and AI sector, monthly AI spending limits have reportedly been slashed from $100,000 per employee to about $10,000 in the bulk of instances.

It’s crucial to note that these figures are spending ceilings fairly than reflections of genuine employee expenditures. This decrease in budgetary elasticity has disheartened multiple engineers who formerly enjoyed broader latitude to examine models.

It’s crucial to emphasize that diminished inner backing does not equate to Microsoft’s withdrawal of Claude from client-facing products.

Reports propose that client expenditure on Anthropic models via Microsoft’s endeavor platforms continues to rise, equal as the business constricts its own employees’ usage.

At Meta, the figure of Claude Code users reportedly plummeted from about 60,000 before this twelvemonth to concerning 30,000.

Although layoffs have influenced this decrease, the study attributes the chief logic to Meta’s strategic change towards its own AI solutions, which comprise MetaCode and Muse Code, developed using Meta’s proprietary models.

MetaCode is stated to have additional than 30,000 inner users, during Muse Code boasts complete 6,000 employee users. Meta initiated external evaluation of Muse Code alongside clients in August.

Notably, amidst this transition, Meta reportedly allocated complete $105 myriad to Claude Code complete a 28-day timeframe, indicating that a decrease in users does not necessarily correlate alongside decreased spending.

For cybersecurity teams, the passage to distinct coding assistants does not eliminate the hazards connected alongside automated admission to delicate files, commands, and credentials.

Previous analyses by Cybersecurity News outlined vulnerabilities inside Claude Code that could authorize unauthorized implementation and API key theft. Anthropic rectified these flaws previous to their community disclosure.

Microsoft’s offerings have encountered akin concerns. The remedied RoguePilot exposure exemplified how nefarious commands embedded in a GitHub Issue could facilitate the takeover of repositories.

Such incidents emphasis the criticality of imposing stringent permissions, employing trusted project settings, and conducting thorough evaluations of AI-generated actions.

Anthropic’s reported annualized income gait of $65 milliard reflects unabated petition for its services.

This retrenchment illustrates a tightening of budgets and intensifying competition, fairly than an outright cessation of involvement alongside Claude.

Source link: Cybersecuritynews.com.

It appears .agent and .agi are about to be the hot new domains

support@mycoding.id (David Pierce) — Wed, 07 Oct 2026 19:46:16 +0700

For the archetypal period in years, the Internet Corporation for Assigned Names and Numbers — improved known as ICANN — is accepting applications for new top-level domains. These are the suffixes at the end of all URLs, and you may cognize them as things akin .com, .org, and .pizza.

ICANN fair announced the 1,615 applications that have been submitted so far, from 481 distinct applicants. The trend volition not astonishment you: AI is everywhere. Ten distinct companies, including the two Meta and OpenAI, applied for the .agent domain. Seven, including OpenAI, applied for .agi. Six, including OpenAI, applied for .asi, plainly attempting to get in on President Trump’s petition to toggle from “artificial intelligence” to “super intelligence.” Four companies applied for .intelligence, and Meta is one of two curious in the preposterously lengthy .superintelligence. (OpenAI applied for a total of 15 TLDs; Meta wants a whopping 21.)

There are, broadly, two types of domains in these applications. One is additional generic, the benevolent of item many of group or companies power use. There are hundreds of those in this current batch, from .geek to .haha to .anime to .jackpot. There’s additionally my individual favorite new one, .itiswhatitis.

The another is purely branded, giving a business its own TLD to use for its own purposes. There are 345 brand applications in this batch, including everything from .applebees and .bankofamerica to .zillow and .zoom. Meta applied for .facebook, .instagram, .messenger, .meta, .frommeta, and .threads, which it could use for many purposes; Bluesky applied for .bsky alongside the apparent aim of weaving the domain into its usernames; OpenAI applied for .chatgpt, .codex, .openai, .gpt, and others; Anthropic wants .anthropic and .claude. These strings could ultimately create for memorable merchandise pages, social media usernames, and much additional besides.

It has mostly been a durable highway for these substitute TLDs complete the final few years. Some, akin .ai or .app, have rotate into somewhat popular gratitude to assorted tech trends, but most group fair never got used to the idea of typing .restaurant or .babysitting, and .com and a few others have really rotate into additional crucial than ever. It’s engaging to see so many brands go for their own domain, which lone Google and a few others have accomplished before.

This is but one stage in the procedure of creating a new top-level domain, and nothing volition be made authoritative before sometime next year. But it appears that equal as the earth becomes additional filled alongside and mediated by AI, awesome domain names continue to matter. Even the AI companies think so.

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

David Pierce

Push Ifs Up and Fors Down: The Idiom, Its Algebra, and Its Limits

support@mycoding.id (Adi Gunawan) — Wed, 07 Oct 2026 19:43:18 +0700

Introduction

One of the recommendations from the Tiger Style document of TigerBeetle ..

Centralize authority flow. When splitting a ample function, try to keep all switch/if statements in the "parent" function, and move non-branchy logic fragments to helper functions. Divide responsibility. All authority stream have to be handled by one function, the remainder shouldn't attention concerning authority stream at all. In another words, "push ifs up and fors down".

The programming heuristic push-ifs-up-fors-down suggests that conditional logic (if statements) have to be moved upward (towards the visitant or before in a pipeline), during iterative loops (for operations) have to be pushed downward (toward lot handling or afterward in a tight branch-free loop). This improves clarity and achievement by centralizing branching and leveraging bulk operations.

matklad has additionally blogged concerning this regulation and discussed the many virtues of adhering to this programming idiom.

In the post, matklad describes optimizing code by:

Pushing conditionals ("ifs") up: If a function branches on its input, regard moving that branch to the caller. Consider the example from the article - alternatively of frobnicate(walrus: Option) unpacking the choice internally, the visitant handles the None case and the function takes a plain Walrus. The function's category now states its precondition, the input province area becomes narrower and acts as a form of filtering. But the item is anywhere the decision lives, not how much data flows downstream.

Pushing loops ("fors") down: Deferring loops until following filtering or reducing the dataset minimizes unnecessary computations. Rather than calling frobnicate(walrus) in a loop, provision frobnicate_batch(walruses) and let the iteration live inner it. So the hot iteration runs without a branch and is a applicant for vectorization.

The two moves compose. Given a gathering of Option values, the visitant discards the Nones and unwraps the remainder into a Vec, afterward hands that to frobnicate_batch, which never has to regard the None case at all.

let maybe_walruses: Vec<Option<Walrus>> = ...; let walruses: Vec<Walrus> = maybe_walruses.into_iter().filter_map(|w| w).collect(); frobnicate_batch(&walruses);

If you think a bit, the push-ifs-up-fors-down regulation has far broader applications. This article explores several of the broader perspectives of this regulation alongside regard to relational repository query optimizations and functional programming and category theory.

Analogy in Database Queries: Projections Early, Joins Late

The identical regulation appears in repository query optimization. In SQL query planning, it’s well-known that one should execute projections and selections as first as imaginable and defer joins or extended operations until later. But the vocabulary runs upside-down. A query scheme is a tree whose leaves are array scans and whose base produces the result. Data flows up from the leaves, so "down the tree" method "earlier in execution". When an optimizer talks concerning pushing a predicate down, it method evaluating it as first as possible, which is the repository equal of what the remainder of this article calls "up" or "early".

Early projections and selections (Push down): In repository terms, a projection (e.g., SELECT alongside particular columns) reduces the dataset's width by selecting lone the necessary columns first in the query execution. And selections (WHERE clause) act as the filter. Both are pushed downward as part of the scheme tree so that they get to execute first and display out irrelevant data, reducing the amount of data passed to afterward operations.

Deferring joins (Push joins up): Joins, which merge data from multiple tables, are computationally expensive. The optimizer moves selections and projections below the joins, so joins run on smaller inputs. The consequence is that the costly combining operators run complete the smallest inputs the query semantics allow.

Vectorized implementation (the "for"): Another repository difference of pushing fors downward is the alter in implementation semantics. Volcano manner implementation processes row at a time, anywhere all controller is called formerly per tuple through a virtual next(). The substitute is the vectorized or lot execution, anywhere all controller is called formerly per lot of a thousand or so tuples and runs a tight iteration inside. That is frobnicate versus frobnicate_batch, at the flat of a query engine: the per-call overhead and the per-call decisions are paid formerly per batch, and the inner iteration is branch-light and cache-friendly.

Analogy in Functional Programming and Category Theory

Let's obtain a appearance at the identical principles through the lens of functional programming and category theory.

Pushing-Ifs-Up as a Restriction to a Subobject

In category theory, whenever we conversation concerning the category of sets (or, loosely, of types in programming), we can have a predicate p : A -> Bool. Elements can either fulfill the predicate or not. Now regard the subset of elements that satisfies the predicate, stated by {a ∈ A | p a}. And add to it the morphism {a | p a} ↪ A that defines the inclusion. The subset alongside alongside the morphism defines a subobject in category theory.

Note the hooked arrow in the morphism. It's intentional and it indicates that it represents a particular category of morphism - monomorphism (mathematicians affection to define arrow types :-)). In Set, a monomorphism is an injective function: the inclusion sends all component to itself, so distinct inputs provision distinct outputs.

Now we have the nexus rear to matklad:

Before: the callee takes any A and runs if p(a) inner itself.
After: the visitant runs the test, and the callee's input category is the subset.

The callee no longer needs the if, since all input it can obtain has already passed. In code you portray the subset alongside a type: Walrus alternatively of Option.

Categorically speaking, Option is the coproduct 1 + Walrus, which is either nothing or a walrus. A function that takes an Option and branches inner is really a function out of a coproduct, and by the worldwide asset of coproducts specified a function is exactly a brace of functions, one for all summand. Pushing the if up factors that brace apart: the visitant deals alongside the 1 summand, and the center function is fair the Walrus component.

Filter, Map and the Law That Relates Them

Same regulation in a distinct manifestation - the algebra of combinators. You commonly comprehend the direction of "filter before you map". But whenever exactly is this a part of lawful rewrite ? Because the two following expressions are not equivalent:

filter p (map f xs) map f (filter p xs)

In the archetypal row p has category B -> Bool; in the second it has category A -> Bool. The law that really relates them is:

filter p . map f == map f . display (p . f)

This follows from parametricity, and it is easiest to see by factoring display through Maybe:

keep :: (a -> Bool) -> a -> Maybe a keep p x = if p x then Just x else Nothing  filter p = catMaybes . map (keep p)

Here display p itself is not a natural transformation - it cannot be, since p fixes the component category and you cannot diagram the naturality quadrate (try it!) - but catMaybes :: [Maybe a] -> [a] is one, and that is anywhere the naturality lives:

map g . catMaybes == catMaybes . map (fmap g)

With that, the law is a abbreviated calculation. Since keep p . f == fmap f . keep (p . f):

filter p . map f  == catMaybes . map (keep p) . map f  == catMaybes . map (keep p . f)  == catMaybes . map (fmap f . keep (p . f))  == catMaybes . map (fmap f) . map (keep (p . f))  == map f . catMaybes . map (keep (p . f))  == map f . display (p . f)

Notice that the right-hand flank is not automatically cheaper: display (p . f) motionless computes f for all component in command to test it. The rewrite pays off whenever p . f simplifies to a cheap predicate q on the input - typically since p inspects a part of the value that f leaves alone. Then display p . map f == map f . display q, and f runs lone on the survivors. Both sides are motionless a sole O(n) pass; what you preserve is the calls to f on elements that were going to be discarded.

And push-if-up-fors-down pays off!

Summary

The chief takeaway from the complete conversation is that we can have broad principles that guide us towards a improved algebra of the code basis or equal the entire system. But all of these activity topic to several constraints that must clasp fine throughout the components.

Taking an if out of a iteration is valid whenever the circumstance is loop-invariant. A per-element circumstance cannot depart the loop. It can lone move to the border and be recorded in a type, as Walrus alternatively of Option.
Pushing a choice below a associate is valid whenever the predicate references columns from lone one flank of the join.
Filtering before mapping is valid as display p . map f == map f . display (p . f), and it saves activity lone whenever p . f reduces to a cheap predicate on the input, typically since p inspects a part of the value that f leaves alone.

So, it's the algebra that tells you which rewrites are legal. In the filter/map case above, it's the naturality of catMaybes that drives the legality and helps you logic concerning the general construction of the code.

For the "fors-down" part, it's additional concerning the disbursal than the equivalence. You alter the form of the arrow from A -> B to [A] -> [B] so that you pay the setup disbursal formerly per batch.

Everything announced at Microsoft’s Surface Laptop Ultra event

support@mycoding.id (Jay Peters) — Wed, 07 Oct 2026 19:42:22 +0700

Microsoft fair wrapped up a big Windows and Surface-focused keynote in San Francisco.

The biggest notice was arguably the publish particulars concerning the Surface Laptop Ultra, its new laptop that’s powered by Nvidia’s RTX Spark Arm-based chip. The device volition commencement at $2,599 for a configuration alongside an 8-core CPU, 24GB of RAM, and 512GB of storage, and it volition be released on October 16th. The laptop additionally has built-in magnetic USB-C charging alternatively of the proprietary Surface Connect magnetic charging port. The Verge’s Tom Warren published a profound dive all concerning the new laptop. Microsoft also announced that the Surface RTX Spark Dev Box, a mini PC for developers, is accessible for preorder for $5,999 onward of shipping in November.

In addition, Microsoft shared particulars concerning some updates coming to Windows, including “Hybrid Intelligence” features that lets Copilot use records on your Windows PC to obtain actions and a new hunt cognition that lets you do quick actions from the hunt bar.

You can capture up alongside all of our safety from the event correct here.

How Microsoft built its MacBook Pro competitor
Before Microsoft releases a laptop to the public, it needs to put the equipment through its paces. That all happens inner a windowless, warehouse-like lab on the company’s Redmond, Washington, campus, anywhere the squad evolving Surface devices programs robots to media their buttons thousands of times, pelts devices alongside broadcast waves from elephantine antennas, and builds contraptions that autumn objects from increasingly daring heights to see whether the products can clasp up.
Its latest laptop, the merchandise I’m current to see, really needs to clasp up. The Surface Laptop Ultra isn’t fair another high-end config of the Surface Laptop, it’s the debut phase for Nvidia’s RTX Spark — Nvidia’s entrance into the earth of Arm-based PC chips, and a chance to attack expectations out of the h2o whenever it comes to what a Windows laptop is capable of.
Read Article >
Microsoft is giving Copilot additional authority complete Windows and your files
Photo by Sean Hollister / The Verge
At today’s Windows and Surface event, Microsoft showed off an upgrade to its Copilot AI scheme that volition provision it admission to local records on your PC and the capability to obtain actions throughout the OS. It’s part of an idea Microsoft is calling “Hybrid Intelligence,” anywhere apps and tools depend on a mix of local and haze AI models to accomplish tasks efficiently.
To display off how Hybrid Intelligence works, Jacob Andreou, Microsoft’s EVP of Copilot, walked through a video demo on phase asking Microsoft’s Autopilot tool to assistance alongside filing taxes. Andreou told the AI delegate that he got an email from his accountant and asked Autopilot to get her what she needs. Autopilot afterward used Hybrid Intelligence to hunt throughout distinct folders to discover the documents, rename the files, zip them into a folder, and outline an email to dispatch to the accountant alongside the zip document attached.
Read Article >
The Surface Laptop Ultra eventually has a publish date — and a starting cost of $2,599
Photo by Tom Warren / The Verge
Months following revealing its Surface Laptop Ultra, Microsoft has announced that the Nvidia RTX Spark-equipped equipment volition initiate on October 16th. Pricing starts at $2,599 for the basis configuration, featuring an 18-core CPU, 24GB of RAM, and 512GB of storage.
The Surface Laptop Ultra ships alongside a 15-inch HDR touchscreen display alongside up to 2,000 nits of highest brightness, alongside alongside a larger trackpad that supports haptic feedback. The equipment uses Nvidia’s new RTX Spark chip, an Arm-based processor alongside up to 128GB of unified memory. Both Microsoft and Nvidia are positioning RTX Spark laptops at the extremely premium end of the laptop market, designed for elevated achievement throughout imaginative software, gaming, and local AI tasks.
Read Article >
Surface RTX Spark Dev Box is accessible for preorder for $5,999
Image: Microsoft
Microsoft’s Nvidia-powered Surface RTX Spark Dev Box is accessible for preorder now directly, and slated to container in November for fair concerning $6,000. It’s pricier than the DGX Spark mini PC Nvidia launched final year, but PC prices have been climbing because of shortages of RAM and another components.
The Dev Box’s flat, 3D-printed anodized aluminum chassis doubles as a heatsink and resembles the top vents on an Xbox Series X. It’s launching alongside the new Surface Laptop Ultra and runs on Nvidia’s Arm-based RTX Spark phase and 128GB of unified memory. With that much memory, alongside alongside a 100-watt thermal letter cover and Nvidia’s Tensor cores, you could likely get an notable gaming cognition on the Dev Box. But as its name suggests, it’s chiefly aimed at developers. It’s optimized for operating local AI, including “models exceeding 120B parameters,” for tasks akin evaluation AI models, prototyping AI agents, or operating AI coding tools on-device.
Read Article >
Microsoft’s Surface Laptop Ultra has built-in magnetic USB-C charging
Image: Microsoft
Microsoft has created a magnetic charging resolution for its Surface Laptop Ultra that uses USB-C. After scrapping its proprietary Surface Connect magnetic charging on its smaller Surface devices final year, the Surface Laptop Ultra has a charging cable that attaches magnetically to the correct flank USB-C port.
During Microsoft’s Windows event on Wednesday, Windows and Surface chief Pavan Davuluri stated that you can fair “bring the connector close, and it snaps correct into place.“ It’s motionless a proprietary solution, but the USB-C harbor it slots into motionless plant for video, data, and another USB-C connectivity akin you’d expect. Microsoft is calling it Magnetic Connect, and I’m amazed the business hasn’t shortened that to Mag-C.
Read Article >
Muse is coming to Windows.
Meta’s new AI delegate volition be getting a native app on Windows, Windows and Surface chief Pavan Davuluri announced at today’s event. No timeline on when, though. Meta launched a Mac Muse app in September.
Windows and Surface live blog: On the dirt at Microsoft’s event
Image: Microsoft
We’re in San Francisco today to comprehend what’s next for Windows and Surface. Microsoft CEO Satya Nadella, Nvidia CEO Jensen Huang, and Windows and Surface chief Pavan Davuluri volition all be holding a “conversation on how local AI volition form the next division of the PC.”
Microsoft and Nvidia have been operating together on the new RTX Spark platform, which is focused on boosting local AI models, imaginative apps, and equal gaming on a sequence of new laptops. Nvidia’s GPU ability is getting squeezed into laptops akin the Surface Laptop Ultra, and we’re concerning to discover out exactly what it’s capable of.
Read Article >

Don't Miss These Last-Minute October Prime Day Deals on Anker Tech

support@mycoding.id (Daniel Oropeza) — Wed, 07 Oct 2026 19:41:36 +0700

Anker has really made a name for itself exterior of their batteries, expanding to headphones, speakers, projectors, and another tech products. Their power stations are motionless among the most recognized in the industry, but their another products are climbing up their corresponding ladders as well. There are many Anker products on transaction correct now during the October Prime Day sale, and I've rounded up the best power banks, headphones, and power stations I could find. The transaction ends tonight, so don't young female out.

The finest Anker power position deals during the October Prime Day sale

The finest agreement on a power position is the Anker SOLIX S2000, which is 46% off correct now, landing at $649.99 (originally $1,199). I own an Anker power position that is slightly bigger than this one, and I can vouch for their norm and practicality. The S200 is awesome for anyone who lives in a home that is prone to losing power during a storm or anyone looking for a compact but mighty portable power position they can obtain to a backyard or camping. It can power an average fridge for 35 hours, according to Anker, which gives you an idea of how mighty the S200 is. The finest period to buy a power financial institution is whenever they're massively discounted, not whenever the food in your fridge is spoiling from a power outage.

Anker SOLIX S2000 1500W Solar Portable Power Station

$649.99 at Amazon

$1,199.00 Save $549.01

Get Deal

$649.99 at Amazon

$1,199.00 Save $549.01

Other Anker power position deals

Anker Solix C300 DC Portable Power Station $199.99 (originally $249.99)
Anker Solix C200 Power Station alongside 60W Solar Panel $229.99 (originally $259.99)
Anker SOLIX C1000 Gen 2 Portable Power Station $469.99 (originally $599.99)
Anker SOLIX C2000 Gen 2 Portable Power Station $849.99 (originally $1,499)

The finest power financial institution deals during the October Prime Day sale

There is item concerning having a charging position for all of your devices that gives me a awareness of peace. Maybe it's practicality or organization, but I affection it. The Anker Qi2.2 Foldable MagSafe Charger can do that for your phone, smartwatch, and earbuds all at once. It additionally props your phone up as a stand. Right now, it's $94.74 (originally $149.99), following a 37% discount.

Anker Prime 3-in-1 Wireless Charging Station, MagSafe Charger Stand Compatible, Qi2.2 25W Certified Palm-Sized Foldable Charger for iPhone 17/16, Apple Watch, AirPods (Non-Battery, Adapter Included)

Other power financial institution deals

Anker 167.5W Max 3-Port Ultra-Compact USB C Fast Charging Car Charger $32.29 (originally $53.99)
Anker 100W Max USB C Charger, 3-Port GaN Phone Charger alongside Smart Display $45.99 (originally $69.99)
Anker 313 Qi-Certified 10W Max Wireless Charger Stand $15.99 (originally $25.49)
Anker Prime Charging Station, 200W 6-Port GaN Desktop Charger $69.99 (originally $79.99)

The finest Anker headphone deals during the October Prime Day sale

The earth power have you convinced that you need to expend upwards of $100 to get fine headphones, but the Anker Soundcore Q20i headphones interrupt that notion alongside a $37.97 (originally $69.99) pair. These headphones have most of the features you'd anticipate from a flagship headphone, akin ANC, High-Res audio, lengthy power division existence of up to 40 hours alongside ANC on, and an amazing app. You really don't need to expend big to get fine headphones in 2026.

Soundcore by Anker Q20i Hybrid Active Noise Cancelling Headphones, Wireless Over-Ear Bluetooth, 40H Long ANC Playtime, Hi-Res Audio, Big Bass, Customize via an App, Transparency Mode (White)

Other Anker headphone deals

Soundcore by Anker P20i True Wireless Earbuds $18.99 (originally $39.99)
Soundcore P40i by Anker Noise Cancelling Earbuds $41.99 (originally $59.99)
Anker Soundcore Liberty 4 Noise Cancelling Earbuds $66.49 (originally $99.99)
Soundcore AeroClip by Anker Open Ear Earbuds $94.99 (originally $169.99)
Anker Soundcore Sleep A30 Special Earbuds $159.99 (originally $229.99)

Amazon October Prime Day FAQs

How lengthy is Prime Day?

October Prime Day is a two-day event that starts Oct. 6 and ends on Oct. 7.

What period does Prime Day start?

October Prime Day starts Tuesday, October 6, 2026, at 12:00 a.m. PT / 3:00 a.m. ET.

Is Prime Day formerly a year?

Prime Day happens all summer. Prime Big Deal Days (or October Prime Day) happens all October. Big Spring Sale happens all spring.

What do you think so far?

Is Anker a dependable brand?

Yes, Anker is among the finest brands whenever it comes to batteries and power banks. They've additionally been making awesome projectors and headphones complete the final few years.

Is Anker a fine brand for chargers?

Anker makes several of the finest chargers in the industry. Its archetypal merchandise that put them on the map was their batteries and power banks, so its chargers are additionally dependable and recommendation awesome value.

Do Anker's Prime Day discounts use to all their merchandise lines, or fair choose items?

Unfortunately, not all Anker products are on sale. However, there are many Anker products on sale, and you can discover them all on the Amazon landing page.

Our Best Editor-Vetted Prime Day Deals Right Now

Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $179.00 (List Price $249.00)

Sony WH-1000XM5 — $198.00 (List Price $399.99)

Ring Indoor Cam Plus 2K Wired Security Camera (2-Pack, White) — $59.98 (List Price $119.98)

Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $399.00 (List Price $449.00)

Blink Outdoor 4 1080p 3-Camera Kit With Sync Module Core + Doorbell — $65.99 (List Price $259.98)

Ring 2nd Gen 2K Wired Video Doorbell With Chime (2026 Release) — $49.99 (List Price $114.98)

Fire TV Stick 4K Plus Streaming Player With Remote (2025 Model) — $37.99 (List Price $69.99)

Apple Watch Series 12 — $349.99 (List Price $399.00)

Deals are selected by our commerce team

Covering tech deals and reviewing TVs, headphones, speakers, and projectors.

Elon Musk took heat at chaotic Memphis data center moratorium vote

support@mycoding.id (Natalie Musumeci) — Wed, 07 Oct 2026 19:26:48 +0700

A Memphis City Council gathering that took concentration on data centers turned chaotic. USA TODAY Network via Reuters Connect

Elon Musk and his company's data center footprint in Memphis, Tennessee, often came under blaze Tuesday during a packed city assembly gathering that descended into chaos.

The heated Memphis City Council meeting, attended by approximately 200 residents — many of whom held signs opposing data centers — was ultimately close downward following assembly members voted 7-5 to postpone a ballot on a projected data center moratorium in the city.

Police were called to the environment as shouting from attendees consumed the room. Livestream footage of the gathering showed a individual alongside a bullhorn prompting a assemblage to chant, "ain't no power akin the power of the people."

In online cellphone video footage, several activists were seen screaming at assembly members, alongside one often yelling, "You're a sellout." A bodily combat additionally bankrupt out between two group in the City Hall lobby, although it was unclear what prompted the brawl.

The tumultuous end to the city assembly gathering offered a snapshot into the fury fueling a expanding nationwide backlash to AI data center development.

Absolute anarchy at Memphis City Council correct now. This is the environment following they voted to shove the data center moratorium downward the line. Council members being ushered out, dense constabulary existence and advocates are not happy. https://t.co/BQZBsMbpP3
— Annie Goldman (@AnnieSGoldman) October 6, 2026

Ahead of the vote, city councilman JB Smiley Jr. asked community members to remain if they supported the projected 12-month data center moratorium in Memphis. Nearly all attendants got out of their seats. Some held signs reading, "people complete billionaires," "pause data centers," and "data center moratorium now."

Councilwoman Jerri Green, who voted against delaying the ballot on a projected data center moratorium, urged her colleagues to greenlight the intermission during criticizing tech titan Musk.

Green, the Democratic nominee for Tennessee governor, pointed to the many locales that have already imposed data center moratoriums "because they see the damage that is happening about the country."

"That is the entire item of the moratorium — is for us to obtain a intermission to get the community input, which was overlooked entirely by Elon Musk and xAI whenever they came in," Green stated to cheers from the audience.

Musk's missile and AI company, SpaceX, operates two enormous data center accommodation in the Memphis area and is evolving a third. SpaceX, which acquired xAI before this year, did not immediately react to a petition for comment on this story.

About 200 attendees packed the Memphis City Council meeting. Neil Strebig/The Commercial Appeal / USA TODAY NETWORK via Imagn Images/Reuters

Green was not the lone councilmember to obtain aim at Musk during the meeting.

Councilwoman Rhonda Logan, who voted in favor of postponing the vote, stated Memphis' zoning laws opened the entrance to Musk's projects and another data center betterment in Memphis.

"We do not have safeguards to defend our people," Logan said.

She added, "If you don't location your zoning and decide anywhere you desire things in your city, you're continually going to be susceptible to those that have prosperity and power and can arrive in and do what they desire to."

Another councilwoman, Yolanda Cooper-Sutton, additionally referenced Musk whenever she warned: "You improved observe out since you're dealing alongside a trillionaire in this city that's current correct now."

"There's several material that went on," Cooper-Sutton, who voted to postpone, said. "There was additional prosperity going out than was coming in whenever xAI was here."

The Memphis City Council is expected to ballot on the projected data center moratorium on October 20.

The most famous diner in every state

support@mycoding.id (Erin Mcdowell) — Wed, 07 Oct 2026 19:17:01 +0700

Chrome stools, bottomless coffee, and a list filled alongside leaf upon leaf of traditional comfort foods — there's no argument: Diners are quintessentially American.

Diners nationwide have been recognized for their historic pasts, award-winning list items, and elevated quantity of affirmative reviews, making them must-stop destinations on any cross-country highway trip.

While diners are disappearing throughout America — because of rising rents and labor costs, declining gain margins, and changing client habits — several have remained fixtures gratitude to loyal locals, cherished list items, and distinctive atmospheres.

From decades-old landmarks akin Tops Diner in New Jersey to no-frills lunch counters that have quietly rotate into traditional icons in their corresponding towns, these are the most iconic diners in all state.

ALABAMA: Duck's Diner in Orange Beach

Duck's Diner. Sandra P./Yelp

Duck's Diner is a laid-back Alabama eatery that's rotate into a go-to halt for locals and vacationers.

The informal place is finest known for its hearty dawn meal plates, Southern comfort food, and traditional diner favorites akin grits and French toast, served fair minutes from the beach.

ALASKA: Kriner's Diner in Anchorage

Kriner's Diner. Yun-Wen L./Yelp

Kriner's Diner offers a traditional diner cognition in the bosom of Anchorage.

The longtime favorite draws crowds for generous portions, traditional dawn meal plates, and traditional American comfort food, all served in a retro setting.

ARIZONA: Welcome Diner in Phoenix

Welcome Diner. Glen L./Yelp

Welcome Diner puts a contemporary rotation on the traditional diner during staying true to its roots.

Set inner a restored 1945 diner car, the Phoenix favorite is known for its imaginative comfort food, accomplishment cocktails, and a nostalgic ambiance alongside a contemporary edge.

ARKANSAS: White House Cafe in Camden

White House Cafe. Chantelle S./Yelp

White House Cafe is a longtime Camden institution, serving diners since 1907.

The historic eatery is known for its traditional Southern comfort food, affable service, and old-school diner atmosphere.

CALIFORNIA: Mel's Drive-In in West Hollywood

Mel's Drive-In. Richard L./Yelp

Mel's Drive-In is among the most recognizable diners in California, gratitude to its retro decor and Hollywood history.

The West Hollywood outpost draws crowds for its milkshakes, burgers, and all-day dawn meal served in a traditional 50s-inspired environment that nods to the aureate age of drive-ins and diners.

COLORADO: Sam's No. 3 in Denver

Sam's No. 3. Casey D./Yelp

Sam's No. 3 is a Denver staple that has been feeding locals since the 1920s.

The bustling diner is celebrated for its gigantic portions, green chile-smothered dishes, and extended list that spans traditional dawn meal plates to comfort-food favorites.

CONNECTICUT: Laurel Diner in Southbury

Laurel Diner. Alejandra S./Yelp

Laurel Diner delivers representative roadside diner diet in a traditional setting, located conveniently fair off I-84 for all roadtrippers passing through the state.

The famous halt is known for its extended menu, including its corned beef hash and dawn meal plates.

DELAWARE: Smyrna Diner in Smyrna

Smyrna Diner. Ha O./Yelp

Smyrna Diner has been slinging up dawn meal favorites in Delaware since 1956, and is motionless celebrated for its all-day breakfast, made-to-order comfort food, and informal environment that may not be the height of luxury, but is certainly value a halt alongside the way on a highway trip.

FLORIDA: Peter Pan Diner in Fort Lauderdale

Peter Pan Diner. Michael G./Yelp

Peter Pan Diner is a retro roadside staple that has been serving Fort Lauderdale since 1979.

The traditional diner is known for its dawn meal plates, old-school oppose service, and burgers.

GEORGIA: The Dwarf House in Hapeville

The Dwarf House. Chris W./Yelp

The Dwarf House holds a particular location in fast-food former as the first Chick-fil-A restaurant.

The quirky, low-ceilinged place draws visitors for its acquainted Chick-fil-A list items, exclusive Dwarf House items, array service, and its function as the birthplace of the nationwide chain.

HAWAII: Liliha Bakery in Honolulu

Liliha Bakery. Bailey I./Yelp

Liliha Bakery is a cherished Honolulu institution that blends diner classics alongside local flavors.

Open since the 1950s, the bakery-restaurant is particularly celebrated for its signature Coco Puffs, hearty dawn meal plates, and Hawaiian comfort food, served about the clock and fine value the delay in line.

IDAHO: Dixie's Diner in Idaho Falls

Dixie's Diner. Dixie's Diner/Yelp

Dixie's Diner brings Southern-inspired comfort food to east Idaho in a cozy, 1950s-inspired setting. The famous place is finest known for its burgers, homemade pies, and traditional diner dishes served alongside a flank of small-town charm.

ILLINOIS: Lou Mitchell's in Chicago

Lou Mitchell's. Leang E./Yelp

Lou Mitchell's is a Chicago dawn meal institution located near the commencement of Route 66.

Open since 1923, the historic diner is known for its big, fluffy omelets, house-baked pastries, and old-school hospitality, including complimentary Milk Duds for guests.

INDIANA: Oasis Diner in Plainfield

Oasis Diner. Oasis Diner/Yelp

Oasis Diner is a meticulously restored 1950s diner completely brought rear to life.

Located in Plainfield, the retro place attracts diners alongside its traditional American diet and preserved piece of midcentury history.

IOWA: Drake Diner in Des Moines

Drake Diner. Clair G./Yelp

Drake Diner is a retro-style neighborhood favorite located near Drake University. The lively place is known for its comfort-food menu, imaginative milkshakes, and traditional diner vibes, example the two students and locals.

KANSAS: Doo-Dah Diner, Wichita

Doo-Dah Diner. Duong N./Yelp

Doo-Dah Diner is a famous Wichita dawn meal place known for its imaginative takes on traditional diner diet and for being one of Yelp's top 100 brunch spots in America.

The locally owned eatery draws crowds for scratch-made dishes and a list that puts a playful rotation on comfort food, specified as its cancer pie eggs Benedict and banana-bread French toast.

KENTUCKY: Ramsey's Diner in Lexington

Ramsey's Diner. Rodger S./Yelp

Ramsey's Diner, a Lexington institution celebrated for its homestyle Southern cooking, has been functioning for complete 30 years. The cherished local sequence is finest known for its hot brown sandwiches, "meat-and-three" plates, and relaxed atmosphere.

LOUISIANA: The Camellia Grill in New Orleans

The Camellia Grill. Brian C./Yelp

The Camellia Grill is a New Orleans landmark alongside a former courtship rear to the 1940s.

Famous for its lively oppose service, bow-tie-wearing servers, and pecan waffles, the diner remains a must-visit place for locals and tourists.

MAINE: Palace Diner in Biddeford

Palace Diner. Jason M./Yelp

Palace Diner may be small, but it is entirely value the cramped quarters. The restaurant, housed in a erstwhile train dining car, has been functioning since 1927.

Visitors flock to the distinctive eatery for a traditional diner breakfast, fried poultry sandwich, and another diner specialties in vintage surroundings.

MARYLAND: Papermoon Diner in Baltimore

Papermoon Diner. Faith Maya O./Yelp

Papermoon Diner stands out for its whimsical, art-filled inner and eclectic decor.

The Baltimore landmark pairs traditional diner dishes it calls "bold comfort food" alongside a colorful, surreal ambiance that has made it among the city's most distinctive restaurants.

MASSACHUSETTS: South Street Diner in Boston

South Street Diner. Becky K./Yelp

Built in the 1940s, South Street Diner serves traditional diner diet 24 hours a day. The sleek place is known for its dependable comfort food and position as a go-to halt for night owls.

MICHIGAN: Fleetwood Diner in Ann Arbor

Fleetwood Diner. Jessica L./Yelp

Fleetwood Diner is an Ann Arbor institution that's been feeding the city about the clock for decades.

The retro diner is finest known for its "Hippie Hash" — a hearty mix of hash browns, vegetables, and flesh — and its loyal late-night following.

MINNESOTA: Mickey's Diner in St. Paul

Mickey's Diner. S E./Yelp

Mickey's Diner, among the most iconic diners in the Midwest, is housed in a stainless-steel dining car that's been functioning since the delayed 1930s.

Open 24 hours a day, the St. Paul landmark is known for its traditional dawn meal plates, old-school oppose service, and enduring function as a comfort-food spot.

MISSISSIPPI: Ajax Diner in Oxford

Ajax Diner. Nikki D./Yelp

Ajax Diner is a longtime Oxford favorite that's been open for nearly 30 years.

It's known for its Southern comfort food, generous portions, and laid-back atmosphere.

MISSOURI: Mel's Hard Luck Diner in Branson

Mel's Hard Luck Diner. Sabrina B./Yelp

Mel's Hard Luck Diner combines traditional diner diet alongside live amusement in the bosom of Branson.

The retro-themed eatery is celebrated for its burgers, towering ice lotion sundaes, milkshakes, and chanting servers.

MONTANA: Betty's Diner in Polson

Betty's Diner. David M./Yelp

Betty's Diner is a small-town favorite overlooking Flathead Lake. The cozy place draws diners for hearty breakfasts, homemade baked goods, and traditional comfort food, served in a welcoming diner setting.

NEBRASKA: Hi-Way Diner in Lincoln

Hi-Way Diner. Bruce K./Yelp

This no-frills institution was included on the Food Network's list of the finest diners in the country, and during it lacks a glitzy atmosphere, it makes up for it alongside traditional comfort food and hearty plates.

NEVADA: Vickie's Diner in Las Vegas

Vickie's Diner. Darren S./Yelp

Vickie's Diner is a Las Vegas late-night staple that caters to bar-crawling night owls, casino workers, and first risers.

The old-school place is known for generous portions, affordable prices, and traditional retro vibes in Sin City.

NEW HAMPSHIRE: Red Arrow Diner in Manchester

Red Arrow Diner. Jason G./Yelp

Red Arrow Diner is one of New Hampshire's most celebrated restaurants, serving customers since the 1920s.

The small but mighty diner has earned national acknowledgment for its comfort food, governmental memorabilia, and visits from presidential candidates on the run trail.

Eater reported that Al Gore, Hillary Clinton, Barack Obama, John Kasich, Ted Cruz, and Donald Trump have all visited the eatery at several item through the years.

NEW JERSEY: Tops Diner in East Newark

Tops Diner. Ruth K./Yelp

New Jersey is the unofficial diner chief of the world, so it's perchance no astonishment that the most celebrated eatery in the state is additionally a diner.

Tops Diner in East Newark, New Jersey, opened in 1942 and has been serving its iconic burgers, meatloaf, and lobster mac and dairy merchandise always since.

In 2017, Time Out named Tops the finest diner in the country, and in 2015, Thrillist called it the "most iconic" eatery in New Jersey.

NEW MEXICO: 66 Diner in Albuquerque

66 Diner. Mary B./Yelp

66 Diner is a Route 66 landmark that celebrates midcentury Americana in complete force.

The traditional diner is known for its retro decor and signature fare, including juicy burgers, milkshakes, and more. It additionally has profound ties to the former of the nearby highway.

NEW YORK: Ellen's Stardust Diner in New York City

Ellen's Stardust Diner. littlenySTOCK/Shutterstock

Ellen's Stardust Diner is as much a achievement venue as it is a restaurant.

The Times Square institution is celebrated for its chanting servers — many of whom go on to Broadway careers — and has rotate into a must-visit attention for theater fans looking for traditional diner diet alongside a show.

NORTH CAROLINA: Poole's in Raleigh

Poole's. Sarah M./Yelp

Poole's puts a modern, chef-driven rotation on the traditional diner concept.

Led by James Beard Award-winning chef Ashley Christensen, the Raleigh eatery is finest known for its gooey baked mac and cheese, seasonally driven list of comfort food, and function in assisting put the city on the national dining map.

NORTH DAKOTA: Kroll's Diner in Fargo

Kroll's Diner. Jim A./Yelp

Kroll's Diner is a Fargo institution known for its German-Russian comfort food. The retro-themed eatery has been open since 1969, and among its most famous offerings are its award-winning knoephla soup, hand-scooped milkshakes, and another diner classics.

OHIO: Tommy's Diner in Columbus

Tommy's Diner. John C./Yelp

Tommy's Diner has been serving Columbus locals since 1989 and has been featured on "Diners, Drive-Ins, and Dives."

The retro landmark is known for its Greek, family-recipe-inspired list and signature dishes akin pastitsio, gyros, and traditional burgers.

OKLAHOMA: Jimmy's Round-Up Cafe in Oklahoma City

Jimmy's Round-Up Cafe. Michael D./Yelp

Jimmy's Round-Up Cafe is a fuss-free Oklahoma City favorite alongside profound ties to the local cowboy and rodeo scene.

The longtime diner is known for its hearty breakfasts, hand-breaded chicken-fried steak, and house-made fried pies, which have helped cement its reputation.

OREGON: Otis Cafe in Lincoln City

Otis Cafe. Leslie H./Yelp

Otis Cafe is a cherished Oregon institution that has drawn devoted fans since it opened in the 1920s. The eatery briefly closed following a 2019 fire, but reopened in a new location in 2021.

The eatery is nationally known for its enormous pancakes, German potatoes, and from-scratch cooking, earning common praise as among the finest dawn meal spots in the state.

PENNSYLVANIA: Bingham's Family Restaurant in Kingsley

Bingham's Family Restaurant. J D./Yelp

Named the finest roadside diner in the nation by USA Today, Bingham's Family Restaurant is a agrarian Pennsylvania staple that's built a position far beyond its small-town location.

The family-run diner is known for its traditional desserts, including homemade cinnamon bread French toast, as fine as another dawn meal favorites.

RHODE ISLAND: Modern Diner in Pawtucket

Modern Diner. Otniel L./Yelp

Modern Diner is among the most iconic dawn meal spots in America's smallest state.

One of the oldest living diners of its kind, the Pawtucket eatery is celebrated for its traditional breakfasts and for its architectural importance as the archetypal diner to be listed on the National Register of Historic Places.

SOUTH CAROLINA: Early Bird Diner in Charleston

Early Bird Diner. Rocky W./Yelp

Early Bird Diner brings a Southern twist to traditional diner diet in Charleston.

It's particularly known for its brunch menu, comfort-food favorites akin shrimp and grits, and its position as a go-to destination for locals seeking elevated diner classics.

SOUTH DAKOTA: Phillips Avenue Diner in Sioux Falls

Phillips Avenue Diner. Zoe C./Yelp

Phillips Avenue Diner is a downtown Sioux Falls fixture that blends retro manner alongside contemporary touches.

Set in a restored diner car, the eatery is known for its imaginative yet traditional comfort food dishes, including chicken-fried steak, meatloaf, dawn meal plates, and more.

TENNESSEE: Sunliner Diner in Pigeon Forge

Sunliner Diner. Cindy R./Yelp

Sunliner Diner is a neon-lit throwback set in a 1950s-style diner.

The Pigeon Forge eatery stands out for its retro design, hand-spun milkshakes, and all-day dawn meal menu, making it a famous halt in one of Tennessee's busiest tourist destinations.

TEXAS: Blue Bonnet Cafe in Marble Falls

Blue Bonnet Cafe. Slagle A./Yelp

Blue Bonnet Cafe is one of Texas' most celebrated diners.

Open since 1929, the Marble Falls institution is legendary for its pies, homemade soups, and common appearances on national "best diner" and "best breakfast" lists.

UTAH: Ruth's Diner in Salt Lake City

Country-fried steak from Ruth's Diner. Katie W./Yelp

Ruth's Diner in Salt Lake City allows guests to dine in a railroad car that formerly operated in the first 1900s, but has since been moved and restored. The eatery focuses on brunch foods, serving cinnamon rotate French toast, huevos rancheros, and deep-fried mac and cheese.

When "Diners, Drive-Ins, and Dives" presenter Guy Fieri visited the restaurant, he stated he couldn't get adequate of the fluffy biscuits.

VERMONT: The Blue Benn Diner in Bennington

The Blue Benn Diner. Summer W./Yelp

The Blue Benn Diner is a traditional Vermont roadside halt housed in a vintage 1940s dining car. The small but mighty diner is known for its hearty breakfasts, maple syrup-forward dishes, and enduring fame alongside locals and travelers.

VIRGINIA: Virginia Diner in Wakefield

Virginia Diner. Natalie M./Yelp

Virginia Diner is a longtime roadside institution that has been serving travelers since the delayed 1920s.

The newer Wakefield eatery is finest known for its traditional Southern diet akin nation ham, brisket and eggs, and grits, as fine as its world-famous peanuts.

WASHINGTON: Frank's Diner in Spokane

Frank's Diner. Stephanie B./Yelp

Frank's Diner is a Spokane landmark housed inner a erstwhile railroad dining car from the first 1900s, featuring magnificent timber paneling and stained-glass windows that volition transport you rear to another era.

Voted the finest dawn meal in Spokane by local publish Inlander, Frank's is among the oldest diners of its benevolent in the country. The eatery is celebrated for its crispy deviled eggs, dawn meal platters, and chicken-fried steak dinner.

WEST VIRGINIA: Dolly's Diner in Princeton

Dolly's Diner. Marsha B./Yelp

Dolly's Diner is a retro-style favorite that brings traditional diner vibes to southernmost West Virginia. The Princeton place is known for its nostalgic decor, traditional association sandwiches, and affable atmosphere.

WISCONSIN: Franks Diner in Kenosha

Franks Diner. Gregory M./Yelp

Franks Diner is one of Wisconsin's most iconic restaurants, functioning out of a restored 1926-era railroad dining car.

The Kenosha institution has earned national acclaim — including a place on "Diners, Drive-Ins, and Dives" and acknowledgment from Tasting Table as among the finest diners in the nation — for its hearty breakfasts and dedication to preserving diner history.

WYOMING: Johnny J's Diner in Casper

Johnny J's Diner. Robert F./Yelp

Johnny J's Diner is a cherished Casper institution that blends traditional diner diet alongside a lively, old-school atmosphere.

This '50s-style diner is celebrated for its extended list of diner favorites, from stacked-high pancakes to juicy burgers, pot roast, broasted chicken, and milkshakes.

When the machine boots but the reply disappears

support@mycoding.id (Putri Silvia) — Wed, 07 Oct 2026 19:10:27 +0700

← Engineering blog

October 7, 2026 · Mainbrella Engineering

You ask a server to create a Linux machine. The device boots. The answer disappears. From the client’s chair, this looks much akin a petition that never reached the server. Retrying is reasonable. Starting a second device would create the improvement additional costly than the failure.

This is a helpful way into Mainbrella’s backend. Follow one device far adequate and the identical issue keeps returning: a command can run without its visitant seeing the result; a personal petition can outlive a network membership; a disk grasp can win without leaving us the grip needed to reconstruct it. Each border needs a decision concerning what a retry is allowed to do.

Let’s prosecute an explanatory job that runs analysis.py, says data from another container, and writes metrics.csv. Its device occupies slot c17. The filenames and slot are examples; the mechanisms below arrive from the open-source backend. We’ll commencement before Linux boots, since that is anywhere ownership and prosperity have to be decided.

One location decides who gets the final slot

Two create requests can attain during an document has one slot left. Reading a counter, booting a machine, and updating the oppose afterward gives the two requests a chance to win. By the period we notice, the costly part has already happened.

We provision all document a Cloudflare Durable Object: a persistent coordinator alongside its own storage. The community API resolves the authenticated person and paid entitlement, afterward addresses that coordinator as account:. Each device slot has a distinct Durable Object. For c17, its name is user::slot:17. The archetypal slot retains the older name user: and the community ID small; that ID does not choose the machine’s size.

The document coordinator serializes admission. A petition must reserve its slot, monthly start, and compute allowance before it can ask the runtime to boot. The next petition hence sees occupied capability equal during the archetypal device is motionless starting. The account controller implements the queue explicitly alongside a commitment tail; an await inner an admission decision doesn’t let the next decision stumble former it.

Holding this fastener until all device was prepared would additionally serialize all their footwear times. We publish it following the durable booking and provision exterior it. One document makes the decisions in order; its runtimes can footwear together.

The abbreviated shared decision precedes the longer autonomous work. Time is schematic: the overlapping bars explain concurrency, not measured startup latency.

There’s a particularly helpful test for this distinction. It sends six concurrent requests on a Builder account, which has five slots, and holds all runtime’s preparedness inspect rearward a gate. Five machines attain footwear before that entrance opens. The sixth petition receives a conflict, and the document records five starts. It checks the two halves of the design: exclusive admission and parallel provisioning.

Ownership is established before this coordination begins. The authentication adapter accepts an API key or a login session. An explicitly invalid Bearer credential fails authentication equal if a valid browser biscuit accompanies it. The internal petition builder supplies the document character and entitlement itself. Letting the visitant choose an x-mainbrella-user header would undo the document border we fair built.

A receipt exists before the device does

For our analysis.py job, the client supplies an Idempotency-Key alongside POST /containers. That key method “this particular attempt to create a machine.” The document records which slot and booking pertain to it, together alongside a fingerprint of the requested configuration. Changing the image, size, or another fingerprinted choice during reusing the key produces a conflict.

The crucial compose is small. Here is the applicable part of container-account-core.js, alongside the surrounding validation omitted:

const reservationId = ++state.nextReservationId; state.reservations[slot] = reservationId; const innovation = { id: crypto.randomUUID(), slot, reservationId, fingerprint, expiresAt: this.now() + CREATION_RETENTION_MS, }; await this.ctx.storage.put({ [KEY]: state, [CREATION_PREFIX + idempotencyKey]: creation, });

That multi-key compose commits the charged booking and innovation receipt atomically. We don’t desire a receipt for a slot we never reserved, or a charged slot that a keyed retry cannot find. Only afterward does the controller dispatch the boot.

Now endure the reply. A matching retry finds the receipt before attempting caller admission. While the booking is pending, it can come back starting. Pending reservations have a ninety-second reconciliation window; following that, the coordinator asks the runtime what really exists. If it finds the operating machine, it returns that device without charging another start. The retry never dispatches the ambiguous booking a second time.

The receipt lasts twenty-four hours. If the device has stopped or its slot has been reused, that identical retained key returns creation_no_longer_running. It doesn’t quietly initiate a replacement. A client that wants a replacement makes a new innovation attempt alongside a new key. This is additionally why the client should preserve its key and petition before sending them: server-side deduplication is small assistance if the client forgets the character it needs to ask about.

What establishes readiness? The runtime controller starts the selected depiction alongside sleep infinity as its entrypoint, afterward executes uname -a. The command must exit successfully inside sixty seconds. This establishes that the visitant can execute a command. Our Python inspection motionless needs its own requirements and checks; an answering kernel cannot certify a financial calculation.

Yesterday’s communication can attain at tomorrow’s machine

Suppose the dispatch for our archetypal footwear is delayed. Meanwhile, the document cancels the reservation, releases c17, and assigns that slot to a replacement. The old dispatch eventually arrives. Its mark is motionless the identical runtime object. Looking up the slot by name cannot inform us whether this communication is entitled to commencement anything.

Each admitted commencement receives an expanding booking number. At the runtime, we persist two high-water marks: the newest accepted commencement and the newest cancellation. A footwear at or below either grade is rejected. Cancellation writes its barrier equal whenever there is no operating visitant to destroy, so a afterward arrival cannot resurrect canceled work.

Follow the dashed diagonal: the archetypal footwear arrives following the replacement. The cancellation barrier and accepted booking create its age apparent to the runtime.

The reverse competition matters too. A delayed cleanup for booking 41 must not halt the device from booking 42. The runtime’s DELETE path advances the cancellation grade but leaves the visitant solitary whenever the cancellation is older than the accepted start. Back at the account, the completion of a footwear must motionless equivalent the current slot booking before it can apparent pending state. An old prosperous answer has no authority complete a replacement either.

Reservation numbers defend the inner lifecycle messages. Public commands and document requests acknowledge a operating generation alongside { id, createdAt }. The slot ID is reusable; the generation is not. Despite its timestamp-shaped representation, createdAt is computed as max(now, previousCreatedAt + 1). Recreating a device in the identical millisecond, or moving the partition clock backward, motionless gives the new visitant a distinct identity.

Keep the two values from the returned operating container. A cleanup petition for fair c17 cannot province which life you mean. The lifecycle tests deliberately halt and reuse a slot before releasing an old footwear dispatch, including without advancing the clock. This is a additional revealing inspect than another prosperous hello-world launch.

The difficult deadline is part of admission

Our device additionally needs approval to keep spending compute. A monthly oppose checked lone at initiate would let many simultaneous machines consume the identical remaining allowance. We reserve the runtime they may use before any of them starts.

Machine sizes have weights in plan-policy.js: Lite uses one compute unit, Medium uses ten, and XL uses twenty-eight. The document reserves unit-milliseconds. Its lease ends at the earliest of four boundaries:

hard deadline = min( commencement period + scheme meeting limit, paid admission expiration, next UTC duration boundary, commencement period + remaining unit-ms / device weight )

For an arithmetic example, reserving a Medium device for one hr commits ten compute-unit-hours. Confirm a halt following five minutes and the consumed amount is 10 × 5 / 60, concerning 0.833 compute-unit-hours; the unused booking is released. A unsuccessful halt or unreadable runtime keeps its reservation. Treating “couldn’t communication it” as “it must be free” would authorize the document to expend that allowance twice. A unsuccessful admitted initiate motionless consumes its monthly start; runtime colony is a distinct calculation.

The runtime persists this difficult deadline and an idle deadline. Real action can move the idle deadline, capped by the difficult deadline. Status polling doesn’t. A Durable Object alert enforces expiration equal whenever the client has gone away. Plan changes can shorten an existing lifetime, but cannot broaden its first difficult deadline.

Stopping activity should remain imaginable whenever the billing lookup is unavailable. The community DELETE way authenticates ownership without requiring a caller billing resolution; the coordinator uses its saved entitlement for cleanup whenever it remains valid. Likewise, a newer voluntary study strikes an older paid one. Otherwise a delayed inspect could reauthorize a device we had already revoked.

A detached spectator shouldn’t own a process

With a operating generation in hand, we can commencement analysis.py. A abbreviated foreground command has a sixty-second maximum. For activity whose outcome we desire to discover following a disconnect, we use a managed execution. Its identifier belongs to a particular receptacle generation, and its innovation requires an idempotency key of its own.

// device is the exact { id, createdAt } returned for a operating guest. // Persist executionKey and this petition before sending them. const query = new URLSearchParams(machine); const reply = await fetch(`${apiOrigin}/containers/executions?${query}`, { method: 'POST', headers: { Authorization: `Bearer ${apiKey}`, 'Content-Type': 'application/json', 'Idempotency-Key': executionKey, }, body: JSON.stringify({ argv: ['python3', '/workspace/analysis.py'], timeoutMs: 120_000, }), }); if (!response.ok) throw new Error(`Execution HTTP ${response.status}`); const implementation = await response.json(); // Save execution.id.

The argv form supplies literal arguments alternatively of assembling casing text. In executions.js, the implementation document is saved before the procedure starts. A matching retry finds that retained identity. An aborted innovation petition or a detached event stream doesn’t get the correct to slay the managed job; definitive cancellation does.

Output events have expanding sequence numbers, committed alongside the record’s updated cursor. A client reconnects to the events endpoint alongside its final processed sequence as cursor. It says the stored suffix fairly than depending on a particular socket having seen all byte. The stream itself is bounded to thirty seconds, so reconnecting is average operation. The procedure can run for up to fifteen minutes, additional constricted by its requested timeout and the container’s remaining difficult lease.

These records are finite resources. Each runtime retains up to thirty-two implementation records, alongside a one-hour preservation deadline measured from job admission. Managed jobs portion a pond of four concurrent operations alongside foreground commands and document transfers. Output is bounded to one MiB and a finite event count. Hitting the output bounds terminates the job and marks it truncated; finding a few plausible lines in stdout is hence insufficient. We inspect terminal status, exit code, timeout, and truncation before trusting the result.

Here is the uncomfortable boundary: durable records don’t create procedure handles durable. When a runtime entity restarts, improvement marks unfinished executions interrupted. If they pertain to its current visitant generation, it destroys that visitant fairly than depart untracked activity running. It never silently reruns the command. For our inspection this method an break can discard an unsaved CSV; for a command that sends invoices, automatic replay could do item worse. Restart improvement is deliberately additional disruptive than reconnecting a viewer.

The data petition arrives alongside an character the visitant can’t choose

Suppose analysis.py says a shard from http://data.internal/shards/west. We enroll its generation as a associate of a personal assistance network. In that identical network, another generation owns the assistance name data and harbor 8080. The origin may be a caller-only member, alongside no listening port.

The guest’s petition names neither an document nor a network. private-services-runtime.js installs an outbound HTTP interceptor for *.internal. Its relay removes reserved character headers and supplies trusted account, slot, and generation values from the runtime entrypoint’s configured properties. Sending an invented ownership header from Python doesn’t choose a distinct customer.

The account’s private assistance registry finds the network containing that exact origin generation, afterward resolves data inside it. Another account—or another network in this account—can reuse the name. The destination rechecks its operating generation and registration under its lifecycle fastener before beginning the registered use port. Resolving the name is lone the archetypal approval check.

Why inspect again? Our data assistance could be detached or replaced during it is answering. The destination buffers the bounded reply and checks its registration again. The document rechecks origin liveness and the two memberships before releasing the response. A petition admitted under yesterday’s affiliation must not provision bytes under today’s arrangement.

Those checks don’t undo an use flank consequence that already happened. If the petition changed the data assistance before its reply was denied, the use motionless needs a way to reconcile that change. Immutable shard says are uncomplicated here; a project queue or fee assistance would need its own procedure identities.

This characteristic is bounded personal HTTP routing: one-MiB petition and reply bodies, a ten-second timeout, and no WebSocket upgrade or arbitrary TCP connection. A PostgreSQL client won’t rotate into private-service-aware since its hostname ends in .internal. Deployment enablement and the capability advertised by GET /capabilities must additionally be current before we build a workflow about it.

The CSV needs a existence exterior the command’s output

Our job writes /workspace/metrics.csv. We recover it alongside a generation-bound document petition during the visitant is motionless running. The document endpoint transfers raw bytes, alongside a one-MiB limit, fairly than decoding binary data as content or hiding an export inner a truncated stdout stream.

The compose way in files.js demonstrates another helpful ordering choice. It writes a impermanent document in the destination’s existing genitor directory, afterward renames it complete the target. Readers shouldn’t detect a half-uploaded regular file. The way is passed as a positional argument, not interpolated into casing code. Writes refuse symlink targets; says may prosecute links inner the owned guest.

These guarantees are narrower than a transaction complete the analysis. A prosperous document transfer doesn’t demonstrate the job used the correct input or completed all its rows. The use should inspect the artifact’s schema and provenance, and copy helpful output exterior the ephemeral device before teardown. If we desire to come back to the surroundings itself, we need a saved workspace.

A snapshot can be without being recoverable

Saving appears akin one operation: grasp the disk, recall the result, halt the machine. It really crosses three owners of state—the account, the runtime, and the provider—and none of them can atomically commit the another two.

In workspaces.js, the document reserves preserve capability and persists the procedure before requesting capture. At the runtime, a receipt containing the preserve character is persisted before calling snapshotContainer(). After grasp returns, the runtime saves the provider grip in that receipt. The document afterward commits the grip to its workspace record. Only following that commit may stop: true demolish the source.

Lose the answer between the runtime and document following the runtime has saved the handle, and a retry can peruse the receipt. We regain the identical grasp without taking another one. But interrupt the runtime following the provider accepts grasp and before its grip is saved, and the receipt contains lone an intent. We cognize we tried; we don’t cognize which provider entity to restore.

The location of the misplaced data changes the recovery. A provider-side disk solitary isn’t enough: we need its grip on our flank of the durable boundary.

The runtime refuses to recapture that unresolved procedure and returns workspace_save_unavailable. The preserve way leaves the origin intact, topic to its average lease. Choosing a new key fair to create the error go distant would be a new grasp attempt, not improvement of the old one. That difference is the bounds of the idempotency promise.

Save quotas document for the disbursal of doubt too. Admission reserves the origin size’s complete disk capability before capture. Deleting a workspace frees its live saved-workspace quota, but doesn’t refund the historic grasp budget: the provider may already have done the work. A unsuccessful or ambiguous call cannot rotate into a cheap way to reiterate captures indefinitely.

Restoring a prepared workspace goes through average receptacle admission and consumes a new start. The restored visitant receives a caller generation and must use the saved size and net policy. The depiction digest must motionless match; an incompatible depiction or unsuccessful provider reconstruct produces an error fairly than silently substituting an bare machine.

The saved province is a filesystem. RAM, operating processes, previews, and private-service memberships do not come back alongside it. Our Python job needs advancement in records if it is to resume, and a restored assistance must commencement its procedure and enroll its new generation. Quiescing writers before grasp is an use duty too. We can maintain a disk complete of mutually inconsistent records perfectly.

Make the delayed communication arrive

The quickest way to inspect these choices is to run the lifecycle tests from a backend checkout. They postpone dispatch, autumn replies following flank effects, rebuild controllers from saved storage, and reuse slots before delivering the old messages:

node --test containers/container-account.test.mjs \ containers/user-container.test.mjs \ containers/workspaces.test.mjs \ containers/private-services.test.mjs

Start alongside stopping and reusing a slot fences old delayed dispatches equal in the identical millisecond. Then peruse misplaced snapshot reply reconciles receipt without recapture beside uncertain grasp cannot be repeated in the workspace tests. The archetypal recovers a saved answer. The second preserves the fact that an answer is missing. That is the decision an delegate needs from its compute backend before it can safely decide what to do next.

Source review: backend commit 6e5bef3, October 7, 2026. Examples and diagrams explain authority flow; they are not manufacturing traces or latency measurements. The lifecycle tests use simulated provider state. Public petition shapes and deployment capabilities are documented in API.md and the agent workflow.

AI Model Groupthink

support@mycoding.id (Putri Silvia) — Wed, 07 Oct 2026 19:08:38 +0700

Ask multiple AI models for a comparable opinion, and Chinese models appear to be additional apt to react in row alongside the wider consensus.

I lately built/vibed a small web tool that asks a panel of 12 AI models any benevolent of “top three” inquiry and tallies the answers akin an Olympic award table. The idea is to have a quick way to fetch hivemind recommendations on item from a fine publish to read, things to do in a city, or a low-stakes purchase.

The scheme immediate is uncomplicated and built about this request:

You are answering a ranking inquiry alongside your own autonomous opinion. Give your top 3 answers, ranked from 1 (best) to 3.

The call explicitly asks all example for its own view, not to conjecture what the assemblage thinks.

There is several normalization required: if we ask for the finest castles in Ireland and Luna votes “Rock of Cashel” during Gemini votes “Cashel Rock”, we desire to treat that as a consensus. The app uses Gemini Flash to adjudicate this.

The results – from conformist to contrarian

A term on study the chart. Long bars and a victor at the top create it appearance akin a leaderboard, as if additional agreement is better. It isn’t necessarily. However, having clicked about a few of the queries: outlier responses are additional apt to be interesting than to be an insightfully accurate reply that bests the responses of all the another models. I akin that Gemini recommends you coat an grownup area terracotta during all the another models propose green, cream, and greige, but I comprehend that many group volition desire their bots to rod to the traditional mainstream appreciate you extremely much.

Each example is scored against the agreement of the another eleven, getting complete credit for the correct item in the correct podium place and fractional credit for the correct item in the incorrect spot. A mark of 1.0 would average ideal accord alongside the winning conclusions of the remainder of the group; 0 would average total contrarianism.

The top four conformists are all Chinese: DeepSeek, Kimi K2, Tencent’s Hy3 and GLM.

Group the scores by nation and the gap holds. The five Chinese models average 0.47, the six American models 0.38, and Europe’s solitary entrant, Mistral, scores 0.36.

The elimination is Qwen, Alibaba’s model, which scores 0.38 and sits among the American models, fair rearward Grok and Nemotron (both 0.40). At the another end, the two most contrarian models are Meta’s Llama 4 Scout (0.34) and Anthropic’s Claude Haiku (0.32).

Detailed table:

Model	Maker	Region	Model ID	Released	Knowledge through	Reasoning	Score
DeepSeek	DeepSeek	CN	deepseek-v4-flash-0731	2026-07	2025-05	Default	0.59
Kimi K2	Moonshot	CN	kimi-k2	2025-07	2024-12	Default	0.47
Hy3	Tencent	CN	hy3	2026-07	Not published	Off	0.46
GLM	Zhipu AI	CN	glm-5.3-flash	2026-08	Not published	Off	0.45
Gemini	Google	US	gemini-3.1-flash-lite	2026-05	2025-01	Default	0.42
Grok	xAI	US	grok-4.3	2026-04	2025-12	Off	0.40
Nemotron	NVIDIA	US	nemotron-3-super-120b-a12b	2026-03	2025-06	Off	0.40
Qwen	Alibaba	CN	qwen-plus	2026-08	2025-03	Default	0.38
Luna	OpenAI	US	gpt-5.6-luna	2026-07	2026-02	Off	0.37
Mistral	Mistral	EU	mistral-small-2603	2026-03	2024-11	Default	0.36
Llama 4	Meta	US	llama-4-scout	2025-04	2024-08	Default	0.34
Haiku	Anthropic	US	claude-haiku-4.5	2025-10	2025-02	Off	0.32

Why would Chinese models concur more?

I don’t know. Here are several explanations I discover plausible, approximately in order.

1. Distillation

Distillation method training a example on another model’s outputs, basically a cloning technique. US labs, including OpenAI and Anthropic, have publically accused Chinese labs of distilling their models at scale. Earlier this twelvemonth Anthropic named DeepSeek and Kimi-maker Moonshot (and additionally MiniMax, which is not represented in the example here) as operating ample distillation campaigns against Claude. That does not established that distillation caused the form here, or equal that these models were trained that way. But if a example was trained heavily on outputs from another models, one expected outcome is that its preferences converge alongside those of origin models, particularly whenever they converge. A example built that way is partially a agreement machine. It is striking that DeepSeek and Kimi, archetypal and second in the table, are among the labs most frequently named in those accusations.

2. Chinese models learning from all other

The Chinese open-weight ecosystem is tightly knit. Labs publish weights, publish methods and train on synthetic data produced by all other’s models. That could be giving the five Chinese models a family resemblance.

This matters since of how the mark works. Five of the dozen models current are Chinese, so if they portion a style, they assistance build the agreement they are scored against. A bloc that votes together volition continually appearance conformist. (Qwen breaking from the bloc is a item against this, or at smallest a sign the family isn’t that close.)

3. Model size and tier

The base of the array is crowded alongside smaller, cheaper models: Llama 4 Scout, Claude Haiku and Mistral Small. Smaller models clasp small of the shared traditional canon in memory, so their picks are additional scattered. Gemini Flash-Lite and DeepSeek’s Flash example are counter-examples, so size can’t be the entire story.

4. Knowledge cutoff

About half of new content appearing on crawl-worthy URLs is written by humans, and fractional by AI. A example trained additional lately has peruse additional of the slop. Most of the Chinese models current are mid-2026 releases. Again there are counter-examples: Kimi (knowledge through 2024-12) is second, during Luna has the newest cutoff on the panel and sits ninth.

5. Post-training personality

Perhaps US labs are investing in post-training in a way that gives additional distinctive character, additional willingness to choice the small apparent answer. If there’s a trade-off between character and benchmark-maxxing that may additionally perform into the flipside, anywhere the Chinese labs are plausibly focusing additional on hitting benchmarks.

6. The English canon

All prompts are in English. A example whose English training data leans on the most extensively syndicated sources would lean to provision the most canonical English-language answers, which is exactly what agreement rewards.

Caveats

More activity needed, because…

Small dataset. This is according to the archetypal few hundred questions from my own use and several humans in the untamed who clicked from Reddit.
Arbitrary panel composition. The measure of which answers are normal is itself defined via the panel’s composition. 6 US, 5 Chinese, and 1 European was an arbitrary choice by me according to my awareness of the industry breakdown. More applicable decisions were to have max one example per lab and evade costly models. Plausible additions would contain models from MiniMax and ByteDance. At a stretch, and in the soul of geo-diversity, the panel could additionally contain Aleph Alpha (Germany), Apertus (Switzerland), Cohere (Canada), Falcon (UAE), Sarvam (India) or LG’s Exaone (South Korea). Adding flagships akin Claude Sonnet, alongside the cheap tiers, power additionally display whether cost tier matters.
Agreement isn’t accuracy. A elevated mark method a example says what others say, not that it’s right. On “best” questions there is frequently no correct answer at all.
English-language questions. The questions so far lean towards an English-speaking, Western frame.

Conclusion

Back to that area recommendation:

11 x models recommended green, lotion or greige
1 x example recommended terracotta

Which of these is additional correct, and which is behavior we desire to encourage? I doubtful most of us desire an AI ecosystem that isn’t a groupthink borg. We akin a bit of Temperature. We desire models to disagree, astonishment us, occasionally shove for the terracotta bedroom. I additionally doubtful that, as users, we lean to reward models that provision us answers that awareness safe. These two instincts are going to be pulled distinct by a lot of prosperity complete the next few years.

Multiply this out to millions of users seeking suggestions and it becomes item bigger: a quiet, changeless force towards a lab-mediated agreement middle.

Commercially, being included in that agreement center is already lucrative. For two decades companies have poured huge amounts of chief into efforts to position fine in hunt engines (SEO), and the astute ones have already switched to competing complete placement in AI responses (AIO/GEO). Self-reinforcing loops volition escalate the value of this prize. If the labs are competitively exfiltrating all other’s responses, getting a merchandise extremely placed in one model’s answers could allow it to stream into the next model’s training data, and the next. Consensus that was gamed formerly can be copied until it looks akin a fact concerning the world.

Paint colours are a harmless starting point, but the identical machinery volition answer questions concerning which applicant to trust, which news origin is reliable, which former is true. Decorating recommendations are evidently not equal to governmental or actual judgments, and models may behave extremely alternatively throughout domains, but the identical essential machinery increasingly mediates all of them. When the models are copying all other’s opinions and feeding those opinions rear into the genuine world, a agreement doesn’t need to be right. It lone needs to be first.

For additional decorating or governmental advice, you can ask the robots for recommendations here.

Links

Run queries here: top3.best

Stats leaf here: top3.best stats page

References for example data:

Implementation notes: The dozen models were called through OpenRouter, mostly in their cheaper “flash” or small variants, alongside reasoning switched off anywhere the provider allows it. “Default” method the example was run alongside any reasoning behavior the provider ships. I did not contact the Temperature parameter, nor did I examine what defaults the distinct models use.

Claude Haiku 5.5

support@mycoding.id (Putri Silvia) — Wed, 07 Oct 2026 19:01:32 +0700

Introducing Claude Haiku 5.5: the cheapest, fastest, and most capable small example we’ve always released.

Claude Haiku 5.5 is designed for high-volume, cost-sensitive tasks. It reliably handles quick and repetitive workloads (like summaries, compactions, repository queries, and classification requests). It pairs fine alongside Opus 5.5 and Sonnet 5.5 as a subagent on coding work. And, since it’s additionally our fastest example to date, it plant particularly fine for speed-sensitive tasks akin live client assistance and browser use.¹

Haiku 5.5 is accessible at a much lesser cost than Haiku 4.5. On average, it now expenses about 75% small to run.²

Along alongside this launch, we’re making improvements to the value of our example range. We’re halving the cost of Claude Sonnet 5.5’s cache reads, which method Sonnet 5.5 now runs about 20% cheaper on most agentic work. And we’re introducing a new monthly API credit for our Claude Max and Team subscribers, designed to assistance our users in construction new agents and applications that run on the Claude Platform.

Performance

Here’s how Claude Haiku 5.5 performs throughout a range of benchmarks:

Knowledge workGDPval-AA v2.1
	Haiku 5.5	Haiku 4.5	GPT-6 Luna	Sonnet 5.5For reference
Knowledge workGDPval-AA v2.1	1620	735	1437	1840
Knowledge workAA-Briefcase v1.1
Knowledge workAA-Briefcase v1.1	1578	614	1336	1824
Computer useOSWorld 2.1
Computer useOSWorld 2.1	72.4%Offline subset	15.7%Offline subset	48.9%Offline subset	83.9%Offline subset
Multidisciplinary reasoningHumanity’s Last Exam
Multidisciplinary reasoningHumanity’s Last Exam	45.9%no tools	10.2%no tools	—	56.9%no tools
Multidisciplinary reasoningHumanity’s Last Exam	57.4%with tools	18.7%with tools	—	64.5%with tools
Agentic codingTerminal-Bench 4.0
Agentic codingTerminal-Bench 4.0	39.2%	0.0%	16.4%	70.6%
Agentic codingFrontierCode 1.1 (Main)
Agentic codingFrontierCode 1.1 (Main)	46.4%	—	42.4%	52.1%Xhigh
Visual reasoningChartography
Visual reasoningChartography	46.4%no tools	6.4%no tools	29.1%no tools	61.6%no tools

For particulars on how we run our evaluations, see the Haiku 5.5 System Card.

Haiku 5.5 is our archetypal Haiku-class example to arrive alongside an adjustable attempt setting. This method that, as alongside our another models, users can decide whether to optimize for disbursal or intelligence. The charts below display how Haiku 5.5 performs on three benchmarks at all attempt setting:

Computer use: OSWorldKnowledge work: GDPval-AAMultidisciplinary reasoning: Humanity’s Last Exam

OSWorld 2.1 (offline subset)Accuracy vs. cost

In first testing, our customers reported results accordant alongside the achievement and disbursal improvements shown above. Here’s what they told us concerning the new model:

AsanaHubSpotAlphaSenseBoxRogoCognition

Quote

“We’re extremely impressed alongside Claude Haiku 5.5, particularly its speed. We ran it through our eval suite for AI Teammates, our AI delegate product, covering use cases akin triaging bugs, environment up projects, and searching ample portfolios to exterior high-risk or overdue work. Compared alongside the example we use today, we saw complete a 30% decrease in latency for project completions and up to 2.5x faster conclusion per delegate turn. It’s a noticeably snappier experience.”

CompanyAsana

AuthorAaron Vinh, Staff Software Engineer

Quote

“At HubSpot, we use simulated portals to measure new models on CRM tasks akin reporting on deals. We mostly test the smaller, additional productive models, and Claude Haiku 5.5 got the finest mark we’ve seen on this suite yet, at 92.8% averaged complete three runs. One CRM audit project asks models to acknowledge old but ambiguous records. Across all of the models we tested, Haiku 5.5 was fastest to complete the task, and had the highest hit charge and the lowest false affirmative rate.”

CompanyHubSpot

AuthorZe’ev Klapow, Distinguished Software Engineer

Quote

“Our customers use Box AI throughout ample volumes of their endeavor content. With general use comes the need to oversee effectiveness and cost, and to discover the finest example to lawsuit the project at hand. In first testing, Claude Haiku 5.5 scored 11 points higher than Haiku 4.5 at concerning fractional the latency. We’d put it to use on analytical activity that runs at scale, from disbursal reports to financial summaries and weekly recurring reviews.”

CompanyBox

AuthorYashodha Bhavnani, VP of AI Products

Quote

“The abbreviated and high-volume activity is anywhere Claude Haiku 5.5 fits for us, akin quick lookups, subagents, and summaries. While a bigger example builds the deck, a Haiku 5.5 subagent goes into the 10-K and pulls the section income row the phase needs. It’s exact adequate that we’d rely it there, and accelerated and cheap adequate that we can run it a lot.”

CompanyRogo

AuthorAlex Wang, Applied AI

Pricing

The array below shows how Claude Haiku 5.5’s pricing compares to our another models. Haiku 5.5 is particularly fine value whenever used for tasks alongside prompts up to 100,000 tokens, which create up about 90% of requests to our former Haiku model.

Price per 1 million tokens	Haiku 5.5 prompts up to / complete 100k	Haiku 4.5	Sonnet 5.5
Cache reads	$0.01 / $0.05	$0.10	$0.10
Cache writes	$0.125 / $0.625	$1.25	$2.50
Input tokens	$0.10 / $0.50	$1.00	$2.00
Output tokens	$0.50 / $2.50	$5.00	$10.00

Safety

Alignment. Claude Haiku 5.5 shows important improvements throughout nearly all of our alignment evaluations related to Haiku 4.5. In particular, we established far small instances of misaligned behavior, and a lesser willingness to cooperate alongside misuse. The model’s system card describes our evaluation procedure and results in additional detail.

Safeguards. Consistent alongside its capabilities, Haiku 5.5’s cybersecurity safeguards are additional restrictive than Haiku 4.5’s, but slightly small restrictive than those we’ve applied to another latest models. In cybersecurity, they authorize a wider range of protective tasks than our safeguards for Sonnet 5.5, but they motionless obstacle intrusion evaluation and another techniques additional apt to be used by attackers.

Haiku 5.5’s existence discipline safeguards are the identical as for Sonnet 5, Sonnet 5.5, and Opus 5. They authorize investigation existence discipline questions but restrict admission to requests that we fairness as apt to logic harm. Organizations operating on wider-ranging existence discipline and cyber activities can use to our Life Sciences Verification Program and Cyber Verification Program.

Availability

Claude Haiku 5.5 is accessible now on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure. On the Claude Platform, developers can get started alongside claude-haiku-5-5.

See our migration guide for details.

Further updates

Alongside our new pricing for Claude Haiku 5.5, we’re making additional improvements to the value of our models and products.

First, starting today, we’re lowering the cost of cache says on Claude Sonnet 5.5. Cache says now disbursal 50% less: $0.10 per myriad tokens fairly than $0.20. Because cache says create up a ample portion of models’ token consumption, this reduces the disbursal of Sonnet 5.5 on most agentic tasks by about 20%.

For instance, here’s what the cost cut method for Sonnet 5.5’s achievement related to disbursal on Terminal-Bench 4.0:

Terminal-Bench 4.0Accuracy vs. cost

This diagram illustrates an crucial difference between Haiku 5.5 and our larger models. Sonnet 5.5 and Opus 5.5 remain improved choices for complex agentic coding tasks akin those measured by Terminal-Bench 4.0. By contrast, Haiku 5.5 is finest suited to additional narrowly scoped tasks that power alternatively have been cost-prohibitive alongside former versions of Claude—like compaction, summarization, or subagent work.

Second, this week, we’ll rotate out a new monthly API credit to all Max and Team subscribers for use on the Claude Platform. Max 5x users volition get $100 in credits per month, Max 20x users volition get $200, and Team subscribers volition obtain up to $500, pooled throughout their users. These credits are designed to authorize our users to test alongside construction tools, apps, and agents that call our API. They can be used on any of our models. For additional information, see our Help Center article.

For developers, we’re additionally updating our Claude Python and TypeScript SDKs to add assistance for device use and browser use in beta. Haiku 5.5 is particularly well-suited to these tasks, stated its blend of speed, capability, and price. You can peruse additional concerning this in our Claude Platform docs.

Microsoft is giving Copilot more control over Windows and your files

support@mycoding.id (Jay Peters) — Wed, 07 Oct 2026 19:01:20 +0700

Jay Peters

is a elder newsman covering technology, gaming, and more. He joined The Verge in 2019 following nearly two years at Techmeme.

At today’s Windows and Surface event, Microsoft showed off an upgrade to its Copilot AI scheme that volition provision it admission to local records on your PC and the capability to obtain actions throughout the OS. It’s part of an idea Microsoft is calling “Hybrid Intelligence,” anywhere apps and tools depend on a mix of local and haze AI models to accomplish tasks efficiently.

To display off how Hybrid Intelligence works, Jacob Andreou, Microsoft’s EVP of Copilot, walked through a video demo on phase asking Microsoft’s Autopilot tool to assistance alongside filing taxes. Andreou told the AI delegate that he got an email from his accountant and asked Autopilot to get her what she needs. Autopilot afterward used Hybrid Intelligence to hunt throughout distinct folders to discover the documents, rename the files, zip them into a folder, and outline an email to dispatch to the accountant alongside the zip document attached.

Features powered by Hybrid Intelligence volition be coming to Copilot complete the “next brace months,” Andreou said.

Microsoft additionally showed off a new Windows hunt cognition that lets you obtain quick actions from the hunt bar, akin turning on dreary mode, turning up your mic quantity alongside an in-line slider, or equal sending a text. The new cognition volition be accessible starting this autumn on Windows 11 PCs, according to Windows and Surface chief Pavan Davuluri.

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Jay Peters

GPT‑6 and Intelligent UI for everyone

support@mycoding.id (Putri Silvia) — Wed, 07 Oct 2026 19:00:58 +0700

Comments

Amazon's New 'About You' Page Lists Everything It Knows About You

support@mycoding.id (Meredith Dietz) — Wed, 07 Oct 2026 19:00:33 +0700

Meredith is a marathon runner and stand-up comedian. As Lifehacker’s Senior Staff Writer, she covers individual fitness tech, residence gym equipment, and more.

It shouldn't arrive as a astonishment that Amazon collects data concerning you according to what you buy. And now, you can get a straightforward appearance at what the business has concluded from all that activity.

Amazon's "About You" page, currently in beta following launching this May, uses data from customers' action to create particulars concerning them in categories akin Product Preferences, Interests & Hobbies, and Home & Family. Amazon uses those particulars to personalize the buying experience. Here's how to navigate and personalize your "About You" leaf in your Amazon account.

What Amazon thinks it knows concerning you

The results can be oddly specific. My editor-in-chief, Jordan Calhoun, shared his page, which includes these entries:

"Likely has 2 adults"
"Owns a PlayStation 5 console"
"Prioritizes plant-based flesh alternatives complete traditional options"
"Subscribes to multiple streaming services continually"
"Owns a ample dog"
"Likely has a cat"

Full disclosure: I try to never use Amazon personally. I beautiful much exclusively use it to circular up deals for you, my beloved reader. That being said, here's what Amazon thinks it knows concerning me: "Values durable journey gear," "prefers sporty and informal garments styles," "practices yoga regularly," and "listens to music frequently."

What counts as data

In its Privacy Notice, Amazon lists all action that provides person data to the company. That includes the obvious, akin searching for items and placing orders. It additionally includes actions you may not acknowledge are being tracked, akin interacting alongside Alexa Voice Service, participating in conversation boards, or linking an Amazon document to a third-party business.

How to perspective your own "About you" page

On desktop:

Hover complete anywhere Amazon says "Hello, [your name]" in the high correct corner.
Under the "Your Account" section, click "Account."
Under the "Ordering and buying preferences" section, click "Your Shopping preferences."

From here, you can add data of your own, akin your footwear size, interests, and dietary preferences. Scroll to the base of the page, and you'll see a blue hyperlinked choice that says, "Manage your information." Click it, and you'll see what dirt Amazon has on you.

On the mobile app:

What do you think so far?

Tap the hamburger icon in the base list bar, afterward go to Account > Shopping preferences > About you.

You can edit it, but not opt out

Shoppers can't immediately opt out of the "About you" feature. They can, however, customize the data by adding particulars they desire Amazon to cognize and deleting assumptions they regard inaccurate or too personal.

Importing data from another AI chatbots

On the "About you" page, customers additionally have the choice to "make Amazon equal additional individual to you" by importing individual data they've shared alongside another AI agents. Amazon provides a immediate for you to nourish to your chatbot to create a buying profile, afterward asks you to copy the bot's reply and paste it rear into Amazon.

Whether that's value doing is up to you. Given how much Amazon already infers from your browsing and buying, handing complete a overview from another AI assistance is a choice value thinking through. Either way, taking a few minutes to assessment your leaf and delete item inaccurate or too individual is a uncomplicated way to see and form what Amazon knows concerning you.

Covering individual fitness tech, residence gym equipment, and more.

How AI search optimization works for modern marketers

support@mycoding.id (Cassie Wilson Clark) — Wed, 07 Oct 2026 19:00:03 +0700

Today, whenever a buyer asks ChatGPT, Perplexity, or Google’s AI Mode a question, they rarely see a catalog of suggested links. They see one synthesized answer that cites a fistful of sources. If your brand is one of those citations, you win attention, traffic, and trust. If it isn’t, you’re invisible, equal whenever you position on leaf one.

That change matters for income teams who need to attain those buyers. Referral traffic from AI tools akin ChatGPT and Gemini has tripled complete the former year, and 44% of marketers say they’ve made a endeavor acquisition according to a brand they archetypal discovered in an AI answer. Nearly 1/3 have done it additional than once. The spectators didn’t disappear; it moved into the answer.

In this guide, we explain how AI hunt optimization really works: How AI answer engines retrieve, ground, cite, and measure content, and what brands need to do to create their satisfied easier for AI systems to retrieve, understand, and cite. Also included: A side-by-side difference of AI hunt optimization versus traditional SEO, quick wins you can execute this week, and expert tips from practitioners on the Found in AI podcast.

Table of Contents

TL;DR: AI Search Optimization

AI hunt optimization makes satisfied easier for AI systems to retrieve, understand, and cite. While traditional SEO focuses on keywords to position higher in hunt results, AI hunt optimization prioritizes context, frequently using retrieval-augmented generation (RAG) to recover and citation live satisfied according to citations, entities, summaries, and Q&A structure.

How does AI hunt optimization activity under the hood?

To optimize for AI search, it helps to cognize what happens between the immediate and the answer. As Pat Reinhart, vice chairman of expert services at Conductor, explained on Found in AI, “An LLM does not run the identical way that a traditional hunt motor akin Google or Bing does. They’re reaching into an indicator and trying to semantically nexus a query to a part of content. An LLM is operating off of its own model. If it doesn’t cognize the answer, or doesn’t awareness it’s complete enough, it’s going to go out and Google things to discover it in genuine time.”

For this procedure to work, two mechanisms do most of the dense lifting: Retrieval-augmented generation and query fan-out.

Retrieval-Augmented Generation (RAG)

Retrieval-augmented generation enhances the accuracy and norm of an LLM’s output. LLMs are trained on an first dataset and create answers from their inner cognition base. So it can quickly rotate into out of date or hallucinate answers. RAG fixes that by adding external search, combining live sources alongside generated answers.

In practice, the scheme fetches relevant, current web pages, afterward writes its reply restricted in what it fair retrieved. Grounding is the connective tissue. It ties the answer to origin matter that supports the response, which is why you see clickable citations next to a generated answer.

Google describes its own AI features this way in its guide to optimizing for AI features: Systems recover relevant, up-to-date web pages from the Search indicator to dirt responses, and a leaf must be indexed and eligible to appear alongside a snippet to be used at all.

In another words, satisfied must be crawlable, indexable, and snippet-eligible to be included in an AI-generated answer.

Query Fan-Out

Where RAG focuses on the anywhere (sources), query fan-out focuses on the why (user intent). Query fan-out enhances LLM answer output by breaking a person query into connected subqueries, analyzing them for contextual criteria specified as pricing or timeline, and synthesizing the results into a sole answer according to those refinements.

According to Search Engine Land, a sole inquiry can trigger dozens of sub-queries throughout predictable patterns, including equal phrasings, follow-ups, broader and narrower versions, and logically implied questions. Google confirmed its systems may matter multiple connected searches throughout subtopics and data sources during a reply is generated.

This is why environment strikes keywords. Prompts are longer and additional conversational than searches, so a leaf that answers a entire collection of connected questions has additional surfaces to be retrieved against. As Reinhart put it, the average Google query is three to four words, during the average ChatGPT immediate runs about 23, which is a complete conversation’s value of environment for the example to activity with.

Where You Show Up in AI Search (and How to Qualify)

In AI-powered search, you’re competing to be cited throughout multiple AI engines, and all rewards slightly distinct content.

AI Overviews: The summarized answer boxes at the top of many Google results. They drag from indexed pages and citation a few sources inline.
AI Mode: Google’s conversational, fan-out-driven hunt experience, anywhere a sole immediate spawns many sub-queries and a synthesized, citation-rich answer.
AI conversation and answer engines: ChatGPT, Perplexity, Gemini, and Copilot answer conversationally and exterior citations or brand mentions depending on the tool and whether live retrieval is on.

The satisfied types most apt to appear portion a few things in common:

They answer a particular inquiry early.
They’re cleanly structured.
They’re uncomplicated to extract.

Definitions, step-by-step how-tos, difference tables, FAQs, first data, and plainly attributed expert commentary all meet requirements well. As Reinhart noted on the Found in AI podcast, the bots desire to arrive in, get the answer as quickly as possible, chunk it out, and put it rear to the user.

How AI Search Optimization Differs From Traditional SEO

Traditional SEO focuses on ranking pages and earning clicks, during AI hunt optimization emphasizes citations, entities, summaries, and Q&A structure.

AI hunt is an additional tier on top of SEO, not a replacement. The specialized fundamentals motionless matter, and a contemporary generative motor optimization scheme is mostly SEO alongside a new structural site bolted on.

As Reinhart stated on Found in AI, “It’s not concerning ranking for a particular keyword. It’s concerning how frequently am I showing up and being mentioned and cited for this topic that group are talking about.”

Side-by-Side: Classic SEO Tasks vs. AI Search Optimization Tasks

How to Improve AI Search Optimization for Content Structure and Q&A Content

Answer engines lift passages fairly than regurgitating entire pages. So the component of optimization shifts from the leaf to the extractable block. When a obstacle plainly states a assertion and immediately supports it, an AI example can catch it, rely it, and citation it.

Here’s how to build satisfied that is effortlessly extracted.

(For a deeper penning tutorial, see HubSpot’s guide on how to compose for AI search.)

1. Write assertion statements alongside contiguous citations.

Lead a division alongside a direct, self-contained claim, afterward assistance it correct distant alongside data, a source, or a named example. This claim-then-evidence form mirrors how a restricted answer is assembled, so it’s uncomplicated for a example to reuse a passage and nexus a citation.

Pro tip: Avoid burying the answer three paragraphs down. Put the extractable declaration first, afterward add the nuance a individual audience wants.

2. Use question-based optimization in subheads.

Write subheads as the questions group really ask, afterward answer them in the archetypal two or three sentences underneath. Query fan-out generates follow-up and clarification queries, so a leaf organized about genuine questions gives the example additional matchable surfaces.

Think of your H2s and H3s as a map of the intent cluster, not fair keyword slots.

What the experts say: Romana Kuts, originator of SaaStorm, stated on the Found in AI podcast that she asks writers to provision extremely straightforward answers in their content. She said, “Most of the traffic that is coming from GPT is coming from a extremely abbreviated and saccharine FAQ.”

3. Add FAQ schema to fortify Q&A blocks.

Marking up Q&A satisfied alongside FAQPage schema labels the question-and-answer association for machines, assisting systems parse and reuse it.

One crucial accuracy note: Google has deprecated FAQ affluent results, so schema volition no longer acquire you the expandable FAQ snippet in the SERP. But you should keep the Q&A content, since it motionless serves readers and gives answer engines clean, tagged pairs to extract. Just don’t add it expecting a rich-result characteristic that no longer exists.

What the experts say: As Kuts describes it, Google sees satisfied through the lens of code, snippets, and schema: internal-link signals, FAQ markup, and author schema that says a genuine individual wrote this. Schema won’t rescue lean content, but it removes ambiguity from fine content.

How AI Search Optimization Works for Entities and Internal Linking

In AI search, authority is small concerning domain-authority scores and additional concerning entities, or the people, brands, and organizations a example recognizes and trusts.

Grounding connects an answer to sources the scheme trusts, and confidence is built through consistency. That consistency gets built in two places: how you depict yourself on your own property, and how consistently you’re described that way everyplace else.

Internal links do the identical activity inner your own site. When you nexus an author to a genuine bio page, or a definition to the deeper guide that expands it, you’re telling a example which pages pertain to the identical being and how they relate. Consistency is the signal, and inner links are how you display your work.

1. Standardize author and institution entities.

Pick one canonical clarification of your brand and your experts, and reiterate it everywhere. That includes:

Your site.
Author bios.
LinkedIn.
Podcast bios.
Third-party profiles.

Pro tip: Add author schema and an institution entity, nexus authors to a genuine bio page, and keep titles and business names identical throughout surfaces. Consistent repeat strengthens the being a example associates alongside your topic.

2. Build assessment and citation signals off-site.

On-page activity makes you eligible. Off-site mentions create you credible. Getting cited, quoted, and discussed on third-party sites, podcasts, and communities teaches AI systems that your brand exists beyond its own website.

Reddit deserves particular notice since of how heavily it feeds these models. As of August 2026, Google and OpenAI motionless have partnerships alongside Reddit, definition those platforms heavily exterior user-generated content.

The capture to making Reddit, or any off-site mention, activity is authenticity. Communities, and the models trained on them, punish satisfied that says as manufactured. Show up as a person, not a media release. As Beth Chernes, J.D., an SEO strategist, stated on Found in AI, “If you audio akin AI on Reddit, no one volition akin you. They’ll say things concerning you being AI, and afterward you get banned. You should display up and be a person.”

Pro tip: Run your brand name through ChatGPT and Perplexity and appearance at what gets cited — not whether you’re mentioned, but whose leaf the example pulled from. Roundups, assessment sites, Reddit threads, and industry publications keep popping up. Those third-party sources are your placement targets, and that catalog is normally additional helpful than a keyword report.

How does AI website optimization activity on the specialized side?

Technical AI website optimization is mostly fine specialized SEO, applied alongside extraction in mind. HubSpot’s guide to AI specialized SEO and its overview of AI website optimization go into additional depth, but current are the two levers that matter most.

1. Use organized data anywhere it matters.

Structured data is helpful, but it isn’t a magic switch. Google is definitive that it doesn’t necessitate particular machine-readable records for AI features, and that organized data supports understanding fairly than guaranteeing inclusion.

Prioritize the schema types that explain meaning:

Organization and Person for entities
Article or BlogPosting alongside a genuine author
Product and Review anywhere relevant
Breadcrumb for structure

Use it to eliminate ambiguity, not as a substitute for substance.

2. Optimize JavaScript and rendering for crawlability.

AI crawlers desire to get in, extract, and depart quickly. If your chief satisfied lone appears following dense client-side JavaScript, many crawlers may never see it.

Here’s how to fix it:

Serve meaningful satisfied in the first HTML (server-side render or pre-render key text)
Keep crucial copy out of images and script-dependent widgets
Make certain your robots rules aren’t accidentally blocking the answer engines you desire to reach

Pro tip: Turn off JavaScript in your browser and reload your top page. Whatever’s motionless on the display is approximately what an AI crawler sees. If your key explanations, comparisons, or FAQ answers disappear, that’s the satisfied you’re not getting cited for.

AI Search Myths to Skip Right Now

There is a lot of AI-search direction that is folklore. Here are five myths to drop, all checked against current chief guidance.

Myth: You need an llms.txt document for Google.

There’s a lot of conversation about whether brands need the llms.txt file. As of August 2026, Google has stated plainly that you don’t need to create new machine-readable records for AI features, and that Google Search ignores records akin llms.txt.

Pro tip: Spend the period on satisfied and crawlability alternatively of a document important engines don’t currently read.

Side note: In first May 2026, Google released llms.txt direction for developers. That’s Chrome tooling aimed at AI agents navigating your site, not Search direction — which is why it doesn’t refuse the above. Even there, the document is optional. Lighthouse marks the audit “Not Applicable” if you don’t have one. If agentic browsing is on your roadmap, it may be value adding. However, it is not part of an AI hunt optimization strategy.

Myth: Chop everything into small chunks.

Extractability is concerning apparent structure, not shredding your satisfied into fragments. Google explicitly says there’s no necessity to interrupt satisfied into small pieces for AI to comprehend it.

Pro tip: Use spotless headings, abbreviated guide paragraphs, and tagged sections, not a partition of one-sentence blocks.

Myth: Rewrite your satisfied fair for AI.

Rewriting solely for machines is wasted attempt since models comprehend synonyms and natural phrasing. The winning move is penning that serves group archetypal and is uncomplicated to extract.

Pro tip: Humanize your content, add genuine perspective, afterward construction it well.

Myth: Manufacture mentions and you’ll get cited.

Inauthentic mentions and spammy nexus schemes don’t build durable being authority, and communities emblem them fast. Earned, genuine mentions throughout dependable channels are what power inclusion in AI-generated answers. Quality and consistency attack volume.

Myth: Schema solitary is a shortcut.

Schema clarifies fine content, but it can’t industry authority for lean content. Treat it as labeling, not leverage. If the underlying passage doesn’t answer the inquiry well, no markup volition create a example citation it.

Pro tip: Run marked-up pages through Google’s Rich Results Test. A valid schema on a leaf that isn’t getting cited rules out markup as the logic and points you rear to whether the passage really answers the question. And for schema types that aren’t rich-result eligible, use the Schema Markup Validator. (Important: Google’s Rich Results Test isn’t a visibility tool. It’s fair a helpful check.)

Quick Wins for AI Search Optimization You Can Ship This Week

Here are three high-leverage moves that can enhance AI hunt optimization inside days.

1. Add abbreviated Q&A blocks.

Source

On your top five business pages, add a two-to-four-question FAQ that answers all inquiry in three sentences or less. Short, straightforward answers are exactly what gets pulled into AI responses.

2. Standardize being names.

Audit how your brand and authors are described throughout the site, social profiles, and third-party bios. Pick one canonical descriptor and create all overview equivalent it this week.

What the experts say: David Kirkdorffer, a partial marketer, gave a apparent alert on Found in AI: “We can say the identical item alongside distinct words and motionless have the identical meaning. But if we alter the words enough, we jump out of one benevolent of definition into another.” Reuse the identical descriptor everywhere.

3. Add author bios.

Source

Give all key part a real, credentialed author byline connected to a bio page, alongside author schema attached. It’s a fast, durable indication of cognition and ability for the two readers and models.

Want the data rearward all of this? HubSpot’s State of AEO study breaks downward how AI hunt is changing buyer behavior, including citation data from 4,000+ marketers and six answer engines so that you can pressure-test your own scheme against the benchmarks.

How to Measure AI Search Visibility and Impact

You can’t oversee what you don’t measure, and AI visibility needs its own scoreboard since rankings no longer inform the story. Set a monthly benchmark and track the trend, not the regular noise. Here are the KPIs that matter for your AI hunt optimization efforts.

Share of sound and citation share: How frequently your brand is cited for mark topics versus competitors.
Mentions and sentiment: How frequently you’re named throughout ChatGPT, Gemini, and Perplexity, and whether the framing is positive.
AI-referred traffic: Sessions arriving from AI answer engines, tracked separately from traditional organic.
Presence quality: Are you cited as a chief origin or a passing mention? Are the facts concerning you accurate?
Downstream impact: MQLs, pipeline, and deals influenced by AI-search sessions, which are the metrics that nexus visibility to revenue.

For a quick baseline, run a one-time audit using a tool akin HubSpot’s AI Search Grader, which scores brand visibility throughout answer engines. Then track regular movement alongside HubSpot AEO. The item is to established a benchmark you can enhance against all month.

Pro tip: Tying AI visibility to pipeline in supplement to citations is what earns AEO a prosperity line. Within two years of investing in first AEO tactics, HubSpot reported a 1600% lift in qualified leads from AI and 2x improved conversion from those leads, alongside a 411% betterment in brand citations. That’s the benevolent of figure that moves a CFO.

Frequently Asked Questions About AI Search Optimization

Should I authorize GPTBot and another AI crawlers?

To be cited, AI engines have to be capable to peruse your content. Allow OAI-SearchBot, ChatGPT-User, and Google’s norm crawler in your robots.txt. GPTBot is OpenAI’s training crawler, and Google-Extended governs Gemini training. Some brands authorize those too for broader presence, during others restrict training use as a matter of policy. Whatever you choose, do it deliberately. Accidentally blocking search-and-citation bots is the most average mistake.

How frequently should I refresh satisfied for AI search?

For AI search, freshness method demonstrating that a leaf is actively maintained. AI engines favor current, well-maintained pages, so refresh precedence satisfied on a rolling monthly-to-quarterly cadence, including:

Update stats.
Add “as of [date]” context.
Incorporate new examples.
Prune item stale.

What’s the finest way to construction Q&A for AI extraction?

To optimize FAQs for AI extraction, use the genuine person inquiry as the subhead, answer it in the archetypal one to three sentences, afterward expand. Keep all answer self-contained so it makes awareness out of context, and add FAQPage schema to tag the pairs. Remember that affluent results are deprecated, so the value current lies in device clarity versus a SERP feature.

Can I optimize existing posts, or should I create new ones?

Start alongside what you have. Optimizing existing posts that already have traction is faster and compounds freshness signals:

Add Q&A blocks.
Tighten claim-and-citation passages.
Standardize author entities.
Confirm crawlability.

How do I nexus AI hunt visibility to revenue?

Segment AI-referred sessions, afterward prosecute them through your chimney to MQLs, pipeline, and closed deals, the identical way you’d trait any channel. The form to appearance for is conversion quality, not fair quantity — Similarweb established AI referrals converting at 11.4% versus 5.3% for integrated hunt in earth ecommerce as of September 2025.

Where to Start With AI Search Optimization

AI hunt optimization makes your satisfied uncomplicated for machines to retrieve, understand, and cite. Answer engines use retrieval-augmented generation to dirt answers in live sources, and query fan-out to fulfill a collection of connected questions at once. AI hunt engines favor pages that create apparent claims, assistance them immediately, construction Q&A cleanly, standardize their entities, and remain crawlable and up to date.

AI hunt optimization doesn’t substitute SEO. It adds citations, entities, summaries, and Q&A construction on top. You can use HubSpot’s AEO tools to track brand visibility throughout ChatGPT, Gemini, and Perplexity and rotate that data into prioritized recommendations.

One final note from the field: When I spent weeks in delayed 2025 operating the identical prompts throughout ChatGPT, Perplexity, and Google’s AI features, the pages that got cited weren’t the highest-authority domains. They were the ones that were fresh, cleanly structured, and ridiculously uncomplicated to extract. Optimize for the answer, and you optimize for the forthcoming of search.

The best enterprise email marketing software in 2026

support@mycoding.id (Jenny Romanchuk) — Wed, 07 Oct 2026 19:00:03 +0700

Enterprise email promotion application is built for high-volume programs that extend teams, brands, and regions. With so much application available, the difficult part comes before and following the dispatch — whether governance keeps all squad inside the rules, CRM-native data surfaces the correct consented audience, and attribution connects email involvement to pipeline and revenue.

A feeble email promotion phase pushes the activity of governance, data surfacing, and attribution rear onto people. A powerful endeavor email phase absorbs this complexity instead. With a powerful phase handling these tasks, marketers can initiate faster, rely their data, and demonstrate their impact. This guide compares endeavor email platforms, specified as HubSpot’s email promotion tools, that provision on that promise.

Table of Contents

What Enterprise Email Marketing Software Must Do

Enterprise email marketing application must assistance complex, multi-team programs without weakening control. The phase should create campaigns easier to measure during keeping client data, consent, brand standards, and reporting intact. These six capabilities distinct enterprise-ready platforms from email tools alongside generous communication limits.

Enforce governance and safety controls.

Consent records must display when, where, and how all communication subscribed. Consent records that display when, where, and how all communication subscribed defend the business whenever data moves throughout brands, regions, or integrations. Enterprise promotion teams cannot oversee to underestimate safety controls. For example, in the UK, two companies were fined £150,000 for sending 7.5 myriad unwanted messages. Third-party suppliers were unable to demonstrate valid consent.

Enterprise email promotion teams have to justify their application has these features:

Role-based permissions
SSO and two-factor authentication
Campaign approvals
Audit logs
Asset partitioning
Sandbox environments

Global businesses should additionally inspect local data hosting, encryption, data retention, and assistance for deletion requests.

Connect email action to CRM income data.

Email metrics endure value whenever run data sits distinct from the CRM, making it difficult to trace results to revenue. CRM-native email promotion platforms forestall this by keeping engagement, lifecycle stage, business data, deals, and income on connected records, enabling apparent income attribution.

Marketing Hub, functioning on HubSpot Smart CRM data, lets marketers create attribution reports and nexus email promotion interactions to agreement innovation and won revenue, giving promotion and revenue one dataset to activity from.

Support ABM and multi-brand operations.

Account-based marketing (ABM) targets companies, but email reaches idiosyncratic people. Enterprise email application must nexus those two levels. It should collection consented contacts under an account, acknowledge their roles, and modify nurture emails as the agreement progresses.

Enterprise email application enables this coordination. For example, it can vigilant revenue whenever multiple stakeholders engage, toggle satisfied following an chance opens, or intermission promotion emails during energetic revenue conversations.

The identical coordination matters throughout multi-brand companies. Each brand may need its own domains, consent preferences, templates, and sender reputation, during guidance motionless needs shared client data and reporting. HubSpot’s multi-account management, accessible at the Enterprise level, solves this by keeping endeavor accounts distinct during allowing data, assets, workflows, and reports to move throughout them according to configured connections.

Apply AI to high-friction workflows.

Personalized email at endeavor measure requires additional than a fine topic line. AI in endeavor email marketing handles the infrastructure rearward it: spectators creation, CRM data classification, workflow design, run QA, and send-time optimization.

HubSpot’s AI tools can assistance marketers build section filters, afterward map and create workflows, summarize CRM data, and update or categorize records. This automation frees teams from the workflow setup that slows endeavor campaigns down.

Protect deliverability throughout domains and IPs.

Enterprise deliverability starts alongside SPF, DKIM, DMARC, spotless lists, accordant volume, and accelerated unsubscribe processing. For example, Yahoo now requires bulk senders to use SPF and DKIM, publish a valid DMARC policy, and assistance uncomplicated unsubscribes.

A dedicated IP gives a business authority complete sender reputation, but it additionally transfers complete duty for maintaining that reputation. An endeavor email phase should assistance gradual warm-up, distinct promotion and transactional streams, and brand-level infrastructure. HubSpot, for example, applies a 40-day automated warm-up to new dedicated promotion IPs.

Fit the endeavor data architecture.

Enterprise email application may need data from the CRM, warehouse, ecommerce platform, and customer-success stack. A lengthy integration directory method small if those connections endure fields, create duplicates, or neglect without warning. When choosing an email promotion platform, inspect for:

Two-way sync
Custom objects
Field mapping
APIs
Webhooks
Test environments

HubSpot Data Sync gives teams visibility into which records are syncing, flags issues before they power your data, and lets teams configure site mappings and sync direction without coding. That turns integrations into manageable infrastructure alternatively of imperishable cleanup work.

The 5 Best Enterprise Email Marketing Software at a Glance

The Top Enterprise Email Marketing Software

No email promotion phase wins all endeavor use case. The following five solutions all recommendation distinctive capabilities suited to distinct endeavor needs. HubSpot leads for CRM-connected B2B marketing. Adobe and Braze go deeper into real-time person journeys. Salesforce makes the most awareness for teams already set up inside the Salesforce ecosystem, during Klaviyo remains the finest for commerce.

1. Marketing Hub Enterprise

Marketing Hub Enterprise connects email promotion immediately to Smart CRM. All the crucial sectors — communication activity, business data, deals, lifecycle stages, and run involvement — live on connected records. Marketers can build exact audiences and trace email power through contact, deal, and income attribution without rebuilding the client journey in a distinct reporting tool.

Marketing Hub additionally covers send-time optimization, run approvals, and multi-account management. Meanwhile, HubSpot’s AI tools can create segments and workflows from plain-language instructions.

HubSpot provides dedicated IP and transactional email options to assistance teams alongside additional advanced sender requirements. Those emails can run as one-off campaigns or act automated nurture workflows according to live CRM changes.

Key Features

Multi-touch income attribution and omni-channel endeavor promotion automation
Automated insights for high- and low-performing promotion messaging
Marketing email sole dispatch API and email approvals
Customer journey analytics
Behavioral event triggers and reporting
Email health reporting
CRM-powered segments
A/B tests
Enterprise email deliverability tools

Pricing: Starts at $3,600 per month, billed annually. The scheme includes five Core Seats and 10,000 promotion contacts. Required Enterprise onboarding expenses $7,000.

Best for: B2B enterprises that desire marketing, sales, and income data in one system.

2. Salesforce Marketing Cloud Engagement

Source

Salesforce Marketing Cloud Engagement uses CRM and Data 360 data to build audiences, personalize promotion emails, and trigger follow-ups according to client behavior. Marketers can use Agentforce to rotate a run concise into email and landing-page content, afterward dispatch the email as a standalone run or location it inner an automated journey. Opens, clicks, and another responses remain connected to Salesforce client records, giving revenue and assistance teams the identical involvement context.

Key Features

Personalized email campaigns
Agentforce satisfied creation
Automated email journeys
Send-time optimization
Engagement tracking
Salesforce CRM connections

Pricing: Corporate starts at $4,200 per institution per month, billed annually. Enterprise-level plans necessitate a tradition quote.

Best for: Large organizations alongside established Salesforce architecture and inner Salesforce expertise.

3. Adobe Journey Optimizer

Source

Adobe Journey Optimizer supports scheduled campaigns and event-triggered emails from Adobe Experience Platform profiles. Marketers can build emails alongside reusable content, energetic personalization, and recommendation decisioning. Preview, proofing, satisfied checks, frequence rules, and subscription administration assistance earth teams capture problems before a ample send.

Adobe additionally provides the sender controls expected from endeavor email software. Teams can oversee subdomains, suppression lists, IP pools, and phased IP warm-up plans.

Key Features

Email Designer
Real-time audiences
Dynamic satisfied and recommendation decisioning
Email proofs or automated satisfied checks
Frequency caps and send-time optimization
Data use labeling and implementation (DULE) governance
Suppression lists and IP warm-up management

Pricing: No community liberated plan; Adobe provides pricing lone by quote.

Best for: Global B2C enterprises that already use Adobe Experience Platform and need strict authority complete high-volume email programs.

4. Braze

Source

Braze is built for ample person brands and turns live merchandise and client behavior into triggered email campaigns. Marketers can create emails through drag-and-drop tools, reusable blocks, templates, or native Figma and Canva integrations. Dynamic satisfied can drag in products, promotions, recommendations, and another customer-specific data at dispatch time. Braze additionally supports interactive AMP emails.

Key Features

Real-time segmentation
Behavioral triggers
Drag-and-drop editing and reusable satisfied blocks
Dynamic recommendations and AMP email
BrazeAI assistance
IP warm-up and deliverability monitoring

Pricing: Custom quote; A complete 14-day liberated test is available.

Best for: High-volume person and mobile-first brands that need email to react to live merchandise behavior.

5. Klaviyo

Source

Klaviyo turns commerce action into ready-to-use email segments, flows, and income reports. It can trigger messages from browsing, cart, purchase, product, and predicted customer-value data. Marketers can afterward test campaigns, propose products, difference achievement through earth holdouts, and nexus email action to attributed revenue.

For endeavor senders, Klaviyo supports tagged sending domains and distinct domains for marketing, transactional, and assistance email. Eligible managed accounts can use dedicated IPs alongside automated warm-up. Deliverability and RFM tools assistance teams place position or involvement problems before they drag downward a important campaign.

Key Features

Commerce-focused profiles
Segment AI
Automated flows
Predictive analytics
Product recommendations
Attribution
350+ integrations

Pricing

Standard Klaviyo plans renew monthly and measure alongside energetic profiles and email volume. Larger customers may move to tradition contracts formerly their plans total $2,000 or additional per month. Contract billing can run monthly, quarterly, semi-annually, or annually
Free scheme for up to 250 energetic profiles and 500 monthly email sends.

Best for: Ecommerce and retailing enterprises that desire accelerated activation of transaction and merchandise data.

How to Choose Enterprise Email Marketing Software

A polished demo can create any phase appearance easy. The correct choice lone becomes apparent whenever teams test it against their data, endorsement process, integrations, and run workload.

Define requirements and governance. Map the center seven features — brands, regions, dispatch volumes, person roles, consent rules, endorsement paths, and transactional email needs. Separate must-haves from nice-to-haves so flashy features aren’t distracting.
Validate integrations and data quality. Trace how client data moves from its origin into segments, campaigns, CRM records, and income reports. Confirm sync speed, site mapping, copy handling, API limits, and which phase wins whenever records conflict.
Run a evidence of concept. Build a genuine segment, initiate an endorsement workflow, automate a nurture path, test personalization, and inspect the resulting attribution. Use delegate data and period all project — the item is to disclose any manual work.
Score vendors and decide. Weight all phase against the requirements that power regular email execution. Then add migration, implementation, add-ons, and inner staffing to the cost. Speak alongside vendors that resemble the business in size, regions, and tech stack before making the final call.

Free resource: How to Launch a Successful Email Marketing Campaign

Enterprise Email Marketing Software Migration and Change Management

Teams migrating from a phase akin Salesforce or Adobe to HubSpot should evade treating the project as one ample data transfer, as this creates risk. Instead, move the program in five controlled stages and keep the old phase accessible until the new phase can run a complete run correctly.

1. Audit what must move.

Decide what HubSpot needs for regular activity and what can realistically be archived. Importing years of unused data creates clutter and can addition the figure of billable promotion contacts. Export the following:

Contacts
Companies
Consent records
Suppressions
Custom fields
Templates
Workflows
Reports
Campaign history

2. Build the CRM construction first.

Create the required properties, lifecycle stages, objects, and contact-to-company associations before importing data. Test a small lot alongside email addresses or another distinctive identifier, since HubSpot uses these identifiers to prevent duplicates and nexus connected records.

3. Move consent and suppressions before energetic audiences.

Import the existing opt-out list, afterward map subscription types and keep consent sources and timestamps. Moving consent and suppressions before energetic audiences prevents the new phase from emailing group the former phase had already suppressed.

4. Prepare the sending infrastructure.

Authenticate all sending domain alongside MX, DKIM, SPF, and DMARC records before launching campaigns. If the business uses HubSpot’s dedicated IP, authorize for its 40-day automated warm-up alternatively of moving the complete dispatch quantity on day one.

5. Rebuild, test, and cut complete in waves.

Start alongside the templates, segments, workflows, and reports that assistance energetic campaigns. Send archetypal to an busy audience, verify recipient counts and CRM updates, afterward gradually addition volume. Keep the former phase in read-only manner until attribution and deliverability checks continue on the new platform. Assign an owner to all live workflow before shutting downward the bequest platform.

Frequently Asked Questions About Enterprise Email Marketing Software

What is the difference between endeavor email promotion application and SMB tools?

The difference between endeavor email promotion application and SMB tools is operational complexity. Enterprise platforms add granular permissions, endorsement controls, and assistance for multiple brands or endeavor units. They have advanced automation, dedicated sending infrastructure, and attribution tied to CRM revenue.

How do we grip data residency and consent throughout regions?

To grip data residency and consent throughout regions, choose the hosting area first, afterward document anywhere integrations, subprocessors, and distant users may move or admission the data. HubSpot offers hosting in the U.S., Canada, Australia, and the EU, but regional hosting does not justify that all handling action stays in the chosen region. Track consent source, date, region, channel, and subscription category on all record. Then use local suppression rules and have lawful advise validate the setup.

How lengthy does a immigration typically obtain and how do we decrease risk?

HubSpot says customers typically complete its Marketing Hub onboarding inside three months, which is a sensible starting point. Multi-brand programs alongside tradition integrations, dedicated IPs, or years of bequest data may need longer.

Reduce immigration hazard by locking the data example early, evaluation one complete campaign, warming the new sending infrastructure, and keeping the old phase accessible through a rollback window.

Can endeavor email promotion application assistance the two content and email channels?

Yes, but SMS safety and consent rules differ by country, so “multichannel” needs a nearer appearance during procurement. HubSpot can coordinate email and SMS through shared CRM segments and workflows, but its current SMS add-ons use U.S.-based numbers.

Long-code messages can attain the U.S. and Canada, during short-code sending is constricted to the U.S. High-volume short-code admission additionally requires Marketing Hub Enterprise and additional add-ons, alongside endorsement taking eight to dozen weeks.

Which endeavor email promotion application should you choose?

Enterprise email promotion looks uncomplicated from the exterior — compose a fine email, dispatch it to the correct people, measure what happens. The difficult part is everything underneath: keeping consent records spotless throughout regions, connecting involvement data to income without rebuilding the client journey in a distinct tool, maintaining sender position throughout brands, and making certain all squad stays inside the rules.

The five platforms in this guide all grip high-volume programs. Where these platforms differ is in how much of that underlying complexity they assimilate and how fine they nexus email to the remainder of the business.

Adobe and Salesforce create the most awareness whenever client data already lives in those ecosystems; switching expenses are real, and the attribution degree they recommendation is difficult to replicate elsewhere. Braze is the correct call for fast-moving B2C brands anywhere email has to react to live merchandise behavior in genuine time. Klaviyo remains the category chief for commerce — if your segments run on acquisition former and predicted life value, it’s difficult to beat.

For complex B2B, I keep coming rear to Marketing Hub since it operates on CRM-native data. It turns that unified client environment into deeply personalized email experiences and clear, defensible income attribution. If email has to demonstrate income as fine as create it, Marketing Hub Enterprise belongs at the top of your shortlist.

The Meta Quest 3S gets a rare discount during October Prime Day

support@mycoding.id (Brad Bourque) — Wed, 07 Oct 2026 19:00:00 +0700

Brad Bourque

is a tech newsman and commerce author based out of Portland, Oregon. He’s contributed to sites akin Digital Trends, Business Insider, and WIRED.

Until the end of Amazon’s October sale afterward tonight, you can catch the 128GB Meta Quest 3S for fair $297.49 (usually $349.99) at Amazon, Walmart, and Best Buy. While the lenses and displays aren’t fairly as keen as the Quest 3, the underlying chipset is the same, and this is a much additional sensible cost for informal VR gaming and movies. In another words, it’s a big upgrade complete the Quest 2. You’ll additionally get three months of Horizon Plus, which gives you admission to a huge archive of games.

$298

The Meta Quest 3S is a battery-powered standalone VR headset that has the identical chipset as the pricier Quest 3, but alongside the identical lenses and display resolution as the Quest 2. In supplement to being capable to perform many games from the Meta Store, it can additionally be connected to a gaming PC to perform VR games akin Half-Life Alyx. Read our review.

If you buy the headset from Amazon, the agreement additionally includes the “Cardboard Monkenaut” cosmetic set for Gorilla Tag VR, as fine as 2,000 “Shiny Rocks” to expend on another in-game items. This famous multiplayer equivalent is liberated to perform on Quest headsets, and volition have you chasing allies or matchmade players through the trees in a high-flying equivalent of tag.

Verge Shopping

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Brad Bourque

How Microsoft built its MacBook Pro competitor

support@mycoding.id (Tom Warren) — Wed, 07 Oct 2026 19:00:00 +0700

Before Microsoft releases a laptop to the public, it needs to put the equipment through its paces. That all happens inner a windowless, warehouse-like lab on the company’s Redmond, Washington, campus, anywhere the squad evolving Surface devices programs robots to media their buttons thousands of times, pelts devices alongside broadcast waves from elephantine antennas, and builds contraptions that autumn objects from increasingly daring heights to see whether the products can clasp up.

Its latest laptop, the merchandise I’m current to see, really needs to clasp up. The Surface Laptop Ultra isn’t fair another high-end config of the Surface Laptop, it’s the debut phase for Nvidia’s RTX Spark — Nvidia’s entrance into the earth of Arm-based PC chips, and a chance to attack expectations out of the h2o whenever it comes to what a Windows laptop is capable of.

Microsoft’s final big laptop shove — the Copilot Plus PC undertaking from 2024, focused initially on Qualcomm chips — “was really aimed at MacBook Air,” says Brett Ostrum, company vice chairman of Surface at Microsoft. Microsoft additionally wanted to go head-to-head alongside the MacBook Pro, but existing chips weren’t capable enough. “We knew that was not going to attain MacBook Pro-level compute.”

Around that time, Nvidia began privately showing off what its forthcoming chips could grip whenever it came to AI, and Microsoft jumped at the possibilities. “It exactly made a ton of awareness for us in conditions of how to go and vie alongside the MacBook Pro,” Ostrum says. “Nvidia was a logical choice.” The two companies have spent the years since operating hand in hand, resulting in today’s launch.

The Surface Laptop Ultra can additionally perform games.

The “nightfall” color choice looks a lot akin Apple’s area gray.

Much akin the MacBook Pro, the Surface Laptop Ultra is a high-end device. It has a CNC-machined aluminum body, a huge trackpad, chicklet keys, and fan vents tucked underneath its slightly elevated base. There’s an gathering of ports, including HDMI and an SD cardstock slot, and a high-res touchscreen that looks awesome up close. A example alongside 24GB of RAM starts at $2,599.99, and if you desire the extremely top of the row alongside 128GB of memory, you’re looking at $5,899.99.

Some of that cost comes from the Ultra being among the most polished laptops you can buy in the Windows world. But several of it comes from the all-new part inside: the archetypal of Nvidia’s RTX Spark line, which is expected to bring essential components of Nvidia’s workstation-level power downward to a portable device. The RTX Spark chips inner the Surface Laptop Ultra are geared toward local AI workloads and imaginative tasks. Microsoft says it’s mighty adequate to grip compressed 280 billion-parameter AI models operating locally — models that needed to run in the haze lone a twelvemonth ago. The RTX Spark is the two CPU and GPU, and the GPU have to be capable to grip Blender 3D objects alongside comfort and cruise through another creator workloads in Premiere or Photoshop gratitude to the system’s use of unified recollection — the identical method Apple takes on its M-series chips.

Microsoft is mostly positioning the Ultra at developers who desire a mighty GPU for local AI compute, but it’s additionally targeting the creatives and professionals who would buy a MacBook Pro. “It is built for us,” says Jit Hirani, guide decorator for Surface devices. “We arrive to activity to build a merchandise for ourselves.”

1/5

The Surface Laptop Ultra parts aren’t held together alongside glue.

Because Nvidia blended the CPU and GPU on the RTX Spark, Microsoft was capable to create its Surface Laptop Ultra motherboard smaller and addition the size of the fans on the device. The area inner the device is maximized for battery, alongside components neatly arranged in a dreary grid. Microsoft has additionally focused on repairability, alongside no components glued downward and plainly marked instructions and QR codes throughout for disassembly.

As this is an Nvidia laptop, you can additionally use it for gaming, but I get the awareness that Microsoft is treading carefully concerning positioning this as a gaming laptop. The RTX Spark is an Arm chip, which method most games aren’t native and volition have to be emulated. Still, I got a chance to briefly perform an emulated type of Gears of War: E-Day on the Surface Laptop Ultra, and it ran buttery smooth, equal transitioning between the laptop being plugged in and operating off power division without a achievement hit.

The Surface Laptop Ultra has the world’s archetypal built-in magnetic USB-C charging on a laptop.

Microsoft put a lot of attention into making certain the Ultra’s scheme was as premium as a MacBook’s, too. One item in particular stood out to me: the way Microsoft has cleverly reworked its magnetic Surface Connect charging port.

“I think we gave our engineering squad likely concerning 300 iterations on this journey since it’s the world’s archetypal built-in magnetic nexus for USB-C,” says Hirani. “The sole constraint from day one whenever we designed the merchandise was that we could not alter the worldwide USB-C [port].”

Instead of losing a USB-C harbor to several tradition solution, Microsoft has built a magnetic nexus about the USB-C harbor instead. It feels extremely akin to the first Surface Connect, complete alongside a charging ray and no need to exactly guide it into place. You can equal disconnect the cable from the 140-watt charging block, reverse it, plug it rear in, and use the regular USB-C harbor on the another end to accusation all of your another devices.

Ostrum tells me that Microsoft spent years “grinding on this” to create a magnetic USB-C charging solution, so my inquiry to him is: Will we see this on additional Surface devices? “We’ll delay and see,” he says. “We have been excellent passionate concerning that experience. This is the location anywhere we wanted to current it to the world.”

The amount of evaluation and merchandise repeat that went into getting this charging harbor correct is mirrored in the remainder of the Surface Laptop Ultra. Microsoft has an Automated Experience Lab (AXL) tool that helps the teams measure the responsiveness of a device, beyond fair regular benchmarks. That’s item from measuring how lengthy it takes to initiate Microsoft Teams to how accelerated it is to category alphabet on a keyboard.

The “BB8” robot that tests the Surface Laptop Ultra.

This is all automated through an Arduino commission that can inject code onto a scheme and measure its reply times. Microsoft has created what it affectionately calls its own BB8, a robot that helps the thousands of engineers operating on getting the stability fair correct for the RTX Spark platform.

“We have engineers at Nvidia that are operating on power, performance, graphics, stability, and Wi-Fi,” explains Ostrum. “When they activity on all of those things, they have to complete their code, inspect it into Nvidia. Once Nvidia is satisfied alongside the stability and the achievement of that chunk of code, it flows into the next branch.”

That procedure creates a lag, sometimes enduring weeks, between Nvidia, Surface, and Windows all getting code prepared for a new phase akin RTX Spark. To speed things up, Microsoft has got Nvidia engineers uploading code remotely to this small robot that automates tasks that regular consumers do alongside a laptop. The miniature robot can unplug USB-C devices, use the touchscreen, pen, and trackpad, and open and near the device.

“By allowing our silicon partners to download onto this setup, we greatly accelerate [testing],” explains Ostrum. “It power have been weeks from the period they were done alongside their code to the period they were prepared to autumn it to us. They can have that data rear the next day.”

Microsoft’s lessons of construction Surface hardware for nearly 15 years have additionally been applied to the Surface Laptop Ultra in ways I’ve never heard concerning before. I’ve seen several of Microsoft’s hardware labs complete the former 15 years, but the one I visited this week was eye-opening. It’s so secretive that I wasn’t capable to obtain photos of the exterior of the construction or the lobby, and it lacks windows so nobody can see inside.

It houses the unsung heroes of Microsoft’s Surface squad who expend hours creating new ways to emphasis test new Surface devices. That includes uncomplicated tests akin automated autumn tests or rows of robots beginning and decision laptop lids thousands of times, but it additionally includes electromagnetic compatibility and RF compliance testing, and X-ray machines and expert speck microscopy equipment that are used to discover failures at nanometer scale.

1/6

Machines flip laptop lids rear and forth.

Microsoft additionally has what it calls a “CSI lab” to execute inspection on hardware failures and justify the results are fed direct rear into the manufacturing process. This can acknowledge faults alongside component suppliers. In one case a few years ago Microsoft established contact failures on several of the displays it was using. The Surface squad traced it rear to sulfur and another halogens established on the display, following the provider had changed the gloves that the manufacturing operators were using.

The evaluation has helped Microsoft get to the item anywhere it now has the confidence to obtain on the MacBook Pro. It additionally gets at the bigger logic Surface continues to be inner Microsoft. Surface isn’t fair a regular hardware endeavor for Microsoft, it’s a way to display its OEM partners what Windows hardware have to be capable of. Surface has helped shove the industry onward on trackpads, displays, pen support, performance, and design. Without Microsoft’s own efforts, Windows laptops and tablets would have fallen equal additional rearward Apple’s MacBooks.

The Surface Laptop Ultra is the clearest example yet of that role. Microsoft is using its own hardware to demonstrate that Windows can vie at the extremely highest end of the laptop market, during giving its OEM partners a mark to beat. That makes Surface far additional than a showcase for Microsoft’s application and hardware. It’s among the ways Microsoft makes certain Windows itself keeps moving forward.

Follow topics and authors from this narrative to see additional akin this in your personalized homepage nourish and to obtain email updates.

Tom Warren

When Business Picks Up, the Instinct Is to Hire. Here’s How That Can Backfire.

support@mycoding.id (David Peterson) — Wed, 07 Oct 2026 19:00:00 +0700

Opinions expressed by Entrepreneur contributors are their own.

Key Takeaways

If a function exists lone to notice, collect and provision data the activity already knows, it’s a postpone alongside a pay — not added capacity.
Look at the final function you opened, and compose downward what they’ll really do on a Tuesday. Separate activity that changes the client outcome from the activity that lone moves data concerning the outcome.
A helpful test is: “If this individual disappeared Wednesday, would the activity halt — or would lone the study stop?”
If lone the study stops, you don’t have a group problem. You have a iteration that depends on person remembering to run it.

The archetypal period person told me to hire, I did.

We had fair taken Bud Authority from nothing toward a genuine publish of business. The activity was piling up — satisfied that needed to go live, client sites that needed a specialized look, broken links, a catalog of findings that had to get rear to us and afterward to the client.

The apparent move was a person. Someone whose job was to post, crawl, inspect and arrive rear alongside a report. I idea of it as an aide seat. It was not. It was a messenger seat. We hired for it.

Capacity was the plan. A queue was the result.

On paper, the place looked clean. Open the CMS. Push the pages. Walk the site. Note what broke. Put it in a doc. Bring the doc to the group who could really alter the work. That is a complete Tuesday if you compose it that way. It is additionally a clarification of a courier route, not a manufacturing role.

About two months in, the work was motionless slow. Not since the individual was a villain. Because the job we had designed was: Go discover out, afterward arrive inform us. Every finding had to delay on a individual to notice it, compose it downward and stroll it throughout the room. The place was expected to add capacity. It added a queue.

I watched the queue form in small ways. A damaged nexus sat until person remembered to check. A missing leaf sat until person opened the list. A client inquiry waited on the next study sequence since the lone way from “known” to “ours” was a individual carrying it. The procedure was not abbreviated on eyes. It was abbreviated on a norm that made the finding display up without a handoff.

We did not need a improved hire. We needed the findings to be without a messenger.

There is a type of this narrative that starts alongside the number. We went from $0 to $1 myriad in small than a year. I volition not guide alongside that, since the figure is what made the bad hire awareness responsible. When income moves, you commencement purchasing seats so the shop looks akin the number. That is how you inherit a slower business than the one that made the money.

The issue wasn’t headcount

I had already watched a distinct business try to measure output by adding writers and afterward developers to suspend the pages. More drafts. More tickets. More group position between the idea and the live page. Throughput did not increase alongside headcount. It rosy whenever the way from compose to publish stopped depending on a sequence of “tell the next person.” This was the related of that mistake. Not additional producers. A courier. Same instinct: If we are behind, add a individual to the gap.

That is the part most agency owners get backward whenever the publish starts to grow. You awareness behind, so you buy a brace of hands. The hands do not fix the delay. They rotate into the delay. The study is lone as accelerated as the individual who has to recall to create it.

The messenger place trains the entire shop to wait. Producers delay for the list. Clients delay for the update. You delay for the gathering anywhere person says the findings out loud. Everyone gets busy. Nothing gets earlier. Busy is not the identical as closed.

I am not going to attire this up as a application story. We changed how the procedure ran. What we built is our business. What I volition say in community is the decision: If a job exists lone to notice, collect and provision what the activity already knows, that job is a postpone alongside a salary.

A iteration is distinct from a report. A iteration method the inspect happens on a agenda or a trigger, the outcome lands anywhere the fixer already works, and the next act does not necessitate a briefing. A study method person has to collect the truth, afterward agenda the area anywhere the fact gets heard. One of those is ops. The another is theater that feels akin ops since there is a individual attached to it.

The $1 myriad twelvemonth is not the lesson. Plenty of firms hit a figure and employ their way into a slower shop. The instruction is that the archetypal ops place we bought was a individual position between the issue and the group who could fix it. Two months was lengthy adequate to see it. We did not need that person. We needed the iteration to near without a meeting.

Hire for the activity that changes the client outcome

If you run a services business, appearance at the final function you opened since you were underwater. Write downward what that individual volition really do on a Tuesday. If the catalog is article this, inspect that, inform us what you found, afterward you are not hiring capacity. You are hiring a postpone and calling it help.

Be specific. Separate the activity that changes the client outcome from the activity that lone moves data concerning the outcome. Publishing a leaf changes the outcome. Logging that the leaf is live is information. Fixing a 404 changes the outcome. Pasting the 404 into a weekly panel is information. Hire for the archetypal kind. Automate, standardize or slay the second benevolent before you put a pay on it.

Ask an uglier inquiry than “Can we oversee them?” Ask: “If this individual disappeared on Wednesday, would the activity halt existing, or would the study halt existing?” If lone the study stops, you do not have a group problem. You have a iteration that depends on person remembering to run it.

That inquiry is uncomfortable whenever you akin the person. Like them anyway. The scheme of the place is motionless the scheme of the seat. Loyalty to a hire does not rotate a messenger function into production. It fair makes you slower to acknowledge what you bought.

Do not confuse a client update alongside a client result. A finding that sits in a doc until Friday is not norm control. It is latency. The client does not buy your headcount. They buy the damaged item getting named and fixed. If naming it requires a full-time messenger, you volition continually be late, and you volition continually think the answer is one additional body.

I motionless employ people. I employ for judgment, for accomplishment and for activity that dies whenever the individual walks out. I do not employ group to transport data the procedure should already have. That appears apparent until you are the one who posted the job, onboarded the place and spent two months wondering why the activity motionless felt slow.

Fix the loop

Speed is not a character trait. It is whether the activity has to delay for a individual whose lone job is to notice it. Cut that wait, and the place frequently disappears. Keep the seat, and you can grow the revenue and motionless awareness akin a $0 shop that fair got louder.

The norm matters additional than the hire. Once the inspect is required, timed and apparent without a courier, you halt arguing concerning who forgot to look. You contend concerning the fix. That is the correct argument. The incorrect disagreement is staffing a hall so fact can stroll from one area to another.

Operators affection to say they hire dilatory and blaze fast. Fine. The helpful type is: Hire lone for activity that disappears if the individual does. Do not employ for activity that is really a report.

If your next employ is a messenger, do not employ them. Fix the loop. If you already hired them, two months is not a failure. It is the archetypal honest appearance at the job you really bought.

MC Project

Here's how the largest fraternities earn and spend their millions

Every semester, thousands of students hurry to associate fraternities throughout the US.

Member dues are a important income source.

Contributions, including alumni gifts, can be another origin of earnings for national Greek organizations.

Greek life's biggest resources can be its houses.

National fraternities expend heavily on hazard management.

Executive pay can additionally be a important disbursal for national organizations.

Housing costs, including food, are a important expense, too.

Maintaining a social existence on evidence can be a important prosperity item.

Supporting alumni, including politicians, is another crucial expenditure.

National tax filings are lone a small opening into the finances of Greek existence organizations.

Read next

Google Opens Its SynthID Watermark Detector To The Public

What The Detector Checks

What A Result Says

Why This Matters

Looking Ahead

The Best Last-Minute Deals on Tablets and iPads During October Prime Day

The 11th-gen iPad is $399 correct now

A like-new Kindle Scribe is nearly fractional the cost of a new one

The TCL NXTPAPER 14 is $120 off

The Xteink X4 Classic pocket e-reader is fair $76

The Fire HD 10 tablet is 53% off

Other tablet deals to consider:

FAQ for October Prime Day

When is Prime Day in October?

What goes on transaction during October Prime Day?

Is Prime Day formerly a year?

Are tablets really cheaper on Prime Day?

What are the finest deals on tablets correct now?

Is there a transaction on Fire tablets for Amazon Prime Day?

ChatGPT’s ‘Intelligent UI’ update fills its responses with pictures, charts, and buttons

The first Nvidia RTX Spark laptops cost up to $7,000

ICANN Reveals 2026 Round Applications for New Generic Top-Level Domains

Reveal Day 2026 Data Snapshot

Additional Resources

Why Legacy PPC Account Structures Are Sabotaging Your Smart Bidding Strategy

Why Legacy Structures Harm Modern Algorithms

How Excessive Segmentation Fragments Data

The Cost Of Low-Volume Data Starvation

Where Consolidation Goes Too Far

High-Impact Preserved Segmentations

How Platform Automation Changes the Stakes

Action Plan: Focus On Signal Quality Over Granular Control

Meta and Microsoft Limit Employee Use of Claude AI Tools

Microsoft Reduces AI Expenditure Allowances

It appears .agent and .agi are about to be the hot new domains

Push Ifs Up and Fors Down: The Idiom, Its Algebra, and Its Limits

Introduction

Analogy in Database Queries: Projections Early, Joins Late

Analogy in Functional Programming and Category Theory

Pushing-Ifs-Up as a Restriction to a Subobject

Filter, Map and the Law That Relates Them

Summary

Everything announced at Microsoft’s Surface Laptop Ultra event

How Microsoft built its MacBook Pro competitor

Microsoft is giving Copilot additional authority complete Windows and your files

The Surface Laptop Ultra eventually has a publish date — and a starting cost of $2,599

Surface RTX Spark Dev Box is accessible for preorder for $5,999

Microsoft’s Surface Laptop Ultra has built-in magnetic USB-C charging

Windows and Surface live blog: On the dirt at Microsoft’s event

Don't Miss These Last-Minute October Prime Day Deals on Anker Tech

The finest Anker power position deals during the October Prime Day sale

Other Anker power position deals

The finest power financial institution deals during the October Prime Day sale

Other power financial institution deals

The finest Anker headphone deals during the October Prime Day sale

Other Anker headphone deals

Amazon October Prime Day FAQs

How lengthy is Prime Day?

What period does Prime Day start?

Is Prime Day formerly a year?

Is Anker a dependable brand?

Is Anker a fine brand for chargers?

Do Anker's Prime Day discounts use to all their merchandise lines, or fair choose items?

Elon Musk took heat at chaotic Memphis data center moratorium vote

Read next

The most famous diner in every state

ALABAMA: Duck's Diner in Orange Beach