MC Project

I moved to South Korea with no long-term plan. After 4 years of teaching, I've built an unconventional life on an island.

support@mycoding.id (Jianne Soriano) — Thu, 29 Oct 2026 02:32:50 +0700

Kylie Genter moved to South Korea following graduating from university in New York alongside no occupation plan. Provided by Kylie Genter

This-as-told-to composition is according to a conversation alongside Kylie Genter, 36, a Haenyeo diver on Jeju Island, South Korea. It's been edited for dimension and clarity.

I'd been teaching English in South Korea for four years whenever I learned concerning the Haenyeo — female freedivers who crop seafood without using contemporary equipment. I was interested. So, in the summer of 2018, I completed diving lessons alongside the hopes that perchance I could activity alongside them one day.

A few years later, my Korean husband, a scuba diver, peruse on a diving collection conversation that a small settlement on the southwestern flank of Jeju Island was recruiting new divers. Their youngest diver was 68 — I wanted to provision it a try.

At first, I was rejected, but I got welcomed rear a duration later. I don't cognize what changed in that one month, but I conjecture they abruptly became open to it, and I went in for an interview.

In January 2024, I started as a diving intern, and following two years of training, I received my Haenyeo licence in April.

Finding my footing in South Korea

I was delivered in upstate New York, the center of three kids. I went to SUNY Oswego and graduated alongside a flat in communications.

After graduating in 2012, I didn't cognize what I wanted to do. I applied to a few alumnus schools and jobs, but nothing worked out. I was stressed out and wanted to leave. I idea concerning going to Japan to instruct English, as I'd studied Japanese for a twelvemonth during in university.

Genter decided to move to South Korea and instruct English. Provided by Kylie Genter

Instead, I settled for South Korea, anywhere several schools offered housing. I didn't cognize much concerning Korea at that period — I wasn't really a big K-pop fan before I came.

So, fair four months following graduating, I moved to Jinju, a three-and-a-half-hour high-speed train journey from Seoul, to activity as an English teacher. In the mornings, I'd do 20-minute lessons alongside kids. In the afternoon, I'd have speaking classes.

I continued instruction until August 2020. That identical year, I got wed and started a pension business alongside my husband, during motionless instruction English on the side.

To get her Haenyeo license, she had to dive 50 days inside a year. Provided by Kylie Genter

Building my existence as a diver

To get my license, I had to dive 50 days inside a year, market 1.2 myriad South Korean won, or $884, value of catch, and get a unanimous ballot from the varied in the collective. It took me two years.

Language was an issue; notwithstanding having spent years in the country, I motionless couldn't continually comprehend what was happening. My biggest power is that I'm physically fitter than several of the varied — they are mostly in their 70s and 80s. So, I assistance out, akin whenever they need person to transport their nets complete of catches or cleanse the dishes.

A lot of the activity is physically demanding. If you don't awareness good, you can't fair shove through. I can't dive if I have a chilly or my sinuses are blocked since I can't equalize underwater. It's crucial to keep my build physically powerful and fit through operating out.

The women she dives alongside are mostly in their 70s and 80s. Provided by Kylie Genter

Committing to an unconventional job

I bask my life. Every day is different, and I do a lot of things furthermore diving. I run a pet inn with my husband; sometimes I motionless tutor and provision lectures. I activity additional hours, but I additionally have a lot additional elasticity to prosecute another things. I don't need approval for a interrupt or a day off.

On normal days, I awaken up and obtain the dogs for a walk. Then, I go diving depending on the weather. If it's not great, I lone dive for two or three hours. A normal day of diving may obtain four or five. After that, I obtain the dogs for another walk.

In our village, we typically dive five days a week. We'll obtain our capture and accumulate it following one cycle. After that, we'll market it to the local fishing co-operative. They'll pay our president, and she afterward distributes the money.

Being a diver isn't a full-time job. A lot of what we acquire depends on the catch. I create about $2,000 a year. Teaching is much additional financially stable. But I affection learning from women who have been carrying on this activity for generations.

When I'm diving, nothing alternatively matters. I fair have to concentration on diving and catching seafood. Nobody can call me. I don't have to appearance at my phone and discarded period doomscrolling.

When I'm profound underwater, it can be meditative, particularly on days whenever the sea is calm, and there's plentifulness to catch. I see myself wedded to this settlement for the remainder of my life.

MicroZig to Adopt Strict No LLM / No AI Policy

support@mycoding.id (Adi Gunawan) — Thu, 29 Oct 2026 01:30:37 +0700

This is mostly taken from Zig's Code of Conduct.

The rules current are strict. This area is for focused, on topic, specialized work on the MicroZig and Zig Embedded Group projects only. It is everyone’s responsibility to keep a affirmative environment, particularly whenever disagreements occur.

This document applies to the Zig Embedded Group GitHub institution and Discord server.

Strict No LLM / No AI Policy

This guideline takes consequence October 28th, 2026.

No LLM-generated content, whether it be code or prose.

No paraphrasing LLM-generated content.

No LLMs for editing, including fixing orthography or grammatical errors.

No LLMs for translation. English is encouraged, but not required. You are welcome to article in your native tongue and depend on others to have their own translation tools of choice to construe your words.

No LLMs for brainstorming and afterward sharing the results of that brainstorming, even if you create the prose. If you use a chatbot to provision you direction on a comment on the matter tracker, that comment is unwelcome.

No LLMs for finding bugs.

No talking concerning use of chatbot/LLM services.

Profession by Isaac Asimov

Safe, Constructive Behavior Only

Examples of behavior that contribute to creating a affirmative surroundings include:

Using welcoming and inclusive language.
Being respectful of differing viewpoints and experiences.
Gracefully accepting constructive criticism.
Helping another individual accomplish their own goals.
Showing empathy towards others.
Showing appreciation for others’ work.
Validating person else’s experience, skills, insight, and use cases.

Examples of unacceptable behavior by participants include:

Unwelcome intimate notice or advances, or use of sexualized tongue or imagery that causes discomfort.
Trolling, insulting/derogatory comments, and individual attacks. Anything antagonistic towards person else.
Off-topic conversation of any benevolent - particularly insulting or delicate issues.
Publishing others’ personal information, specified as a bodily or electronic address, without definitive permission.
Discussing this Code of Conduct or publically accusing person of violating it.
Making person alternatively awareness akin an outsider or implying a deficiency of technical abilities.
Destructive behavior. Anything that harms MicroZig or another open-source project.

If you need to study an matter you can communication Matthew Knight and Felix Queißner. We volition swiftly eliminate anyone who is antagonizing others or being generally destructive.

This includes Private Harassment. If individual A is immediately harassed or antagonized by individual B, individual B volition be blocked from participating in this space equal if the harassment didn’t obtain location on among the mediums directly under regulation of this Code of Conduct.

As noted, discussing this Code of Conduct should not obtain location on GitHub, or Discord, since these spaces are for immediately operating on code, not for meta-discussion. If you have any issues alongside it, you can communication me directly, or you can associate among the community spaces that has distinct rules.

Matthew Knight mattnite@proton.me

Thanks for study the rules. Together, we can create this area welcoming and inclusive for everyone, despite of age, build size, disability, ethnicity, sex characteristics, sex character and expression, flat of experience, education, socio-economic status, nationality, individual appearance, race, religion, or sexual character and orientation.

Qwenputer: A functioning, deterministic RISC-V CPU inside Qwen3.5

support@mycoding.id (Adi Gunawan) — Thu, 29 Oct 2026 01:25:45 +0700

← My writing

COMPILED WEIGHTS

A inventory Qwen 3.5 4B alongside a RISC-V CPU compiled into its weights, operating on its own Gated DeltaNet layers as RAM.

By Divyansh Agrawal22 October 20269 min read

I can't accept it's not silicon

Qwenputer is a beautiful fun experimental model. It's a inventory Qwen 3.5 4B alongside one addition: a RISC-V CPU embedded inside the weights that uses the model's own Gated DeltaNet notice layers as RAM. (To study how GDN works, here's a helpful guide.) This 'CPU' runs entirely inside the onward passes of the model, and can run arithmetic operations, C and MicroPython code without any external runtime or tool use whatsoever.

To be extremely clear, it is not a plugin, a tool or a sandbox. This blog volition explain exactly how this example works, and how the example utilises GDN layers as RAM, and how I additionally slotted in an experimental in-model document storage.

I additionally wrote up two follow-ups built on top of Qwenputer: how hybrid models can study to conceal their reasoning in their RNN province and evade CoT monitoring, and how compiled weights akin these can activity as inbuilt monitoring tools that the example itself can't tamper with.

Qwen hands a multiplication to the RISC-V CPU inner its own weights; the CPU's RAM is Gated DeltaNet state

You can catch Qwenputer from Hugging Face or ModelScope, and the code is on GitHub.

The RNN inner Qwen3.5 can be exact RAM

Qwen3-Next and Qwen 3.5 (the example Qwenputer is built on) use a beautiful neat trick. 3 out of 4 notice layers in the example use Gated DeltaNet, a linear RNN, as the notice scheme (more on that here). Each caput keeps a province matrix, and the delta regulation keeps this updated.

Now, here's anywhere our fun test starts. I established out that by environment the entrance to 1,¹ Each Gated DeltaNet caput keeps a province matrix, its memory. At all token, before penning item new, it multiplies the entire province by the gate, a figure between 0 and 1. That's how the RNN forgets: a entrance of 0.9 fades everything stored a small on all token, and a entrance of 1 method nothing always fades. the compose power (beta) to 1,² After the gate, the caput nudges one direction of the province towards a new value, and the compose power beta sets how far. A beta of 1 method the old value alongside that direction is replaced entirely alternatively of blended. and using one-hot key encoding,³ A one-hot key is a vector of zeros alongside a sole 1 in it, so it points at exactly one row of the state, the way a recollection location points at one cell. all compose we execute volition overwrite exactly one row, and all one-hot query can recover an exact value. This method that the GDN layers themselves can activity exactly as RAM, at a far lesser disbursal than using normal notice as RAM, since a GDN head's province stays the identical size nevertheless lengthy the conversation gets, dissimilar attention's KV cache.

Gated DeltaNet province used as RAM: a one-hot key overwrites one row, a one-hot query says it back, and the CPU keeps its registers, recollection and program oppose in those rows

The idea that the delta regulation acts as a recollection isn't new: Schlag et al. (2021) showed that linear notice alongside the delta regulation plant as an associative memory, or "fast weights".⁴ Imanol Schlag, Kazuki Irie and Jürgen Schmidhuber, "Linear Transformers Are Secretly Fast Weight Programmers", ICML 2021. The new item current is making it exact and addressable, inner a manufacturing model, reliably adequate to run a entire CPU on it.

This is the basis on which this complete example is built. As it stands, default Qwen 3.5 does not keep exact values in the GDN. With this modification, we unlock the next part of this experiment.

Compiling a device into layers

Since we have a completely functional, cheap and accelerated RAM now, we can go onward alongside compiling a operating CPU into the example weights. Luckily, there's no training involved: a compiler sets all importance directly. You depict the CPU as a circuit, a lengthy catalog of small steps akin "read this register", "add these two numbers" or "jump if zero", and the compiler turns all stage into a part of a transformer layer: notice heads that appearance things up, feed-forward units that do the arithmetic, and DeltaNet heads that clasp the RAM. The CPU afterward runs as the example decodes.

Each education becomes a few generated tokens: one names the recollection row to compose (ADDR), the next carries the value (VAL), and a STEP token ends the instruction. Those tokens are the CPU's implementation trace, so during Qwen is generating them, the CPU is really running.

The CPU

The CPU is a 32-bit RISC-V center (RV32IM, affirmative the Zba expansion and a small bignum component for big-number arithmetic), and it takes up 11 layers in forefront of Qwen's 32. As it stands, it passes the authoritative riscv-tests, its programs equivalent qemu, and it has run 18 myriad instructions free-running without a sole error.⁵ Free-running method the CPU keeps going on its own outputs for the entire run, alongside no citation device correcting it between steps.

This CPU can additionally run C and MicroPython code in the onward passes fairly fine (although a bit slowly). It is not a Linux-class part yet, but it implements the complete RV32IM education set.

How Qwen uses it

Qwen 3.5 4B is capable to use this CPU fairly well, without any post-training required. The CPU is used entirely internally, and not invoked through any external tool calls.

In command to create the example use this reliably, I decided to go the cheap way: by piggybacking on the tool call format that models are fairly well-trained on, Qwen sends the CPU its instructions and says rear the results. No external tool calls or runtime are used. Once our CPU receives the instructions, the device layers run, and afterward compose the tool response. We use a small controller called RvChat to burden the firmware into the GDN state, and this keeps the trace tokens out of Qwen's layers.

Qwen's first weights remain exactly as they are. The device weights are added on top of them, in additional dims and layers.

Does it work?

I think the chief inquiry current on your intellect following study through my incessant ranting volition be: does this really work?

Accuracy of basis Qwen3.5-4B, Qwenputer and basis Qwen alongside a Python tool on NUPA and DeepMind arithmetic sets

On the DeepMind sets:

div_big: Qwenputer scores 97.5%, versus 95% by giving Qwen 3.5 4B a Python tool and 72.5% for basis Qwen.
mul_big: Qwenputer scores 97.5%, versus 100% alongside a Python tool and 55% for basis Qwen.
mul_div_multiple_longer: Qwenputer scores 100%, versus 97.5% alongside a Python tool and 90% for basis Qwen.
add_or_sub_big: Qwenputer scores 97.5%, the identical as alongside a Python tool, and 87.5% for basis Qwen.

On NUPA's long-integer arithmetic, Qwenputer goes from 48.6% to 100%, the identical as giving Qwen a Python tool.

The numbers the CPU prints are exact, too: I replayed concerning 230,000 of its output positions against a citation device and established zero mismatches. And bolting a device onto Qwen doesn't alter how it talks: its normal content stays inside noise of basis Qwen (KL 6e-4, against a noise flat of 5e-4).

A difficult drive? In this economy?

Because a CPU inner a tongue example plainly wasn't cursed enough, I decided the prudent item would be to provision it a filesystem too.

Since we already have a functional RAM, this was mostly trivial. On the example side, it's exposed via inner put / append / get / catalog / delete operations. Once again, no genuine tool calls. When Qwen 'saves' a file, the compiled layers hash its name into one of 1,024 slots in a directory kept in the DeltaNet state, and shop the content itself in another heads, alongside eight tokens per row, chained together. In scenarios anywhere two names end up landing on the identical slot, it fair checks the next one. Finding a document again takes approximately two or three steps alternatively of a scan, and it holds up to 512 files, which comes out to concerning 53,000 tokens of text.

Fun item is, this is fairly persistent. You can preserve the province at the end of a conversation, burden it into the next one, and the records are motionless there. Using this filesystem, Qwen gets facts that changed between chats correct 90% of the time, against 30% whenever you paste the old chats rear in, and it's on par alongside giving Qwen recollection tools run by Python (83.3% vs 78.9%). This one is motionless experimental, and its code lives on the rv-store branch, alongside the example on Hugging Face and ModelScope.

Limits and what's next

Qwenputer is extremely much an experiment, so a few limitations. The additional layers and wider hidden size create the checkpoint 18.8 GB, approximately twice basis Qwen, although most of it is zero padding. It additionally needs a small controller (RvChat) to footwear the firmware and keep the trace tokens out of Qwen's layers, so it doesn't run alongside a plain generate() call yet. And it's a bit slow, alongside all CPU education costing a few decoded tokens, so a big calculation takes seconds fairly than milliseconds. The batched administrator I used for the benchmarks runs concerning 3,200 CPU tokens a second on an L4.

Next up, I desire Qwen to compose Python and run it on the MicroPython inner its own weights, through a python() tool that plant the identical way calc does. Making the CPU faster is the another big one.

Beyond arithmetic

Exact authority complete the RNN layers is helpful for a lot additional than arithmetic. It additionally makes Qwenputer a really nice testbed for AI safety research, and I wrote up two follow-ups: how hybrid models akin Qwen 3.5 can study to conceal their reasoning in their RNN province and evade CoT monitoring, and how compiled weights can activity as monitorability tools, akin an in-weight detect the example can't toggle off, or answer keys for interpretability.

Try it

If you desire to perform alongside it yourself, the example runs on a sole 24 GB GPU. You'll need uv and the Hugging Face CLI. You don't need a tool server or a Python sandbox for the calculations: the CPU runs them inner the model.

git copy https://github.com/divagr18/qwenputer && cd qwenputer/experimental/riscv && uv sync --extra hf hf download divagr1925/Qwen3.5-4B-Qwenputer --local-dir qwenputer-rv uv run python -m chipformer.rv.chat qwenputer-rv --firmware tests/data/rv/calc-bridge.elf \ --ask "Use calc: what is 123456789 * 987654321?"

Everything is open: the code on GitHub, and the two models on Hugging Face (Qwenputer, Filesystem) and ModelScope (Qwenputer, Filesystem).

If you use it in your work, you can citation it as:

@software{agrawal2026qwenputer, author = {Agrawal, Divyansh}, heading = {{Qwenputer}: a device compiled into the weights of a pretrained tongue model}, twelvemonth = {2026}, url = {https://github.com/divagr18/qwenputer} }

New York Times adds more AI features to its Cooking app. Users aren't thrilled

support@mycoding.id (Adi Gunawan) — Thu, 29 Oct 2026 01:16:08 +0700

New York Times adds more AI features to its Cooking app. Users aren't thrilled. Comments

Get Ready for Touch on Mac

support@mycoding.id (Adi Gunawan) — Thu, 29 Oct 2026 00:58:20 +0700

Learn how to optimize your apps.

Videos

Design for Touch on Mac

Bring Touch to your Mac app

Bring Live Activities to Mac

Meet alongside Apple

Touch on Mac Group Labs

Join Apple engineers and designers online to ask questions, get advice, and prosecute the conversation concerning creating and optimizing apps for Touch on Mac.

Sign up now:

Tools and documentation

Xcode 27.3 beta

Download the latest SDKs to build, run, and test your app.

Coming soon

Documentation resources

Learn how to build and optimize your app for touch input.

Design resources

Create experiences that obtain advantage of contact person interface patterns.

GitLab Security Incident: Attempted Exploitation of CVE-2026-97229

support@mycoding.id (Mira Azkia) — Thu, 29 Oct 2026 00:45:46 +0700

2026-10-28

On October 20 and 21, an attacker tried to utilize a GitLab exposure (CVE-2026-97229) on our instance, a week following the fix was released. The assault came near to working. We have established no evidence that it succeeded, but we cannot regulation it out, so we treated the case as compromised and rebuilt it from scratch. Our checks display that the aports repository, packages, and the October 21 releases were not tampered with.

GitLab is being tested before we open it to the community again. All passwords have been reset, so whenever it is rear you volition need to set a new one alongside “Forgot your password?” on the sign-in page. We volition article exactly what you need to do whenever it reopens. In the meantime: if you used the identical password for your gitlab.alpinelinux.org document anyplace else, alter it there. We have seen automated login attempts against our GitLab alongside passwords leaked from another sites.

If you have questions or concerns delight attain out to us at infra@alpinelinux.org.

What happened

The vulnerability: CVE-2026-97229 is a crucial (CVSS 10.0) exposure in how GitLab evaluates regular expressions in CI configuration. The underlying bug is in Onigmo, the regular expression motor built into Ruby. GitLab published fixed releases on October 12, but the fix itself is a set of patches to the Ruby that GitLab bundles in its own packages and receptacle images. Upstream Ruby shipped the fix on October 23, in Ruby 3.3.13, 3.4.12 and 4.0.9.

The attack: On October 20 and 21, a newly registered document sent crafted CI configurations to our GitLab instance, which was motionless operating 19.3.4 and did not have the October 12 fix. This wrecked GitLab employee processes 8 times. In 4 of those crashes the attacker got partway through the utilize and unsuccessful at the next step. The attacker additionally downloaded our GitLab receptacle image, which suggests they were tuning the utilize to our exact build. We have established no evidence that the attacker ran code on the server, but we cannot regulation it out.

Our upgrade didn’t fix the vulnerability: Upgrading to GitLab 19.3.6 on October 22 didn’t fix the vulnerability. The fix isn’t in GitLab’s own code but in a place to Ruby, which GitLab applies lone in its authoritative packages. Our depiction used norm Ruby, so it didn’t get the patch.

If you run GitLab alongside your own Ruby (from origin or in your own receptacle image) fairly than GitLab’s packages, upgrading GitLab is not enough: you additionally need Ruby 3.3.13, 3.4.12, 4.0.9 or later.

If you use our alpinelinux/gitlab receptacle image, drag alpinelinux/gitlab:19.3.6 again. The depiction published on October 27 contains Ruby 3.3.13. Any 19.3.6 depiction you pulled before October 27, and all older tags, are vulnerable.

Incident Timeline

Date	Event
Oct 28	GitLab rebuild complete; all passwords reset and GitLab's concealed keys replaced
Oct 27	GitLab closed to everyone apart from developers and build servers; rebuild started
Oct 26	Found the case motionless susceptible following the upgrade
Oct 25 to 26	Attacker returns and tries to get rear in; attempts fail
Oct 24	aports, packages and Oct 21 releases verified against exterior records
Oct 23	Attacker's document blocked; Ruby releases the fix
Oct 22	Upgraded to GitLab 19.3.6
Oct 21	Main attack; GitLab crashes, 502 errors and unsuccessful CI jobs
Oct 20	Attacker registers an document and starts probing
Oct 13	CVE-2026-97229 published; we upgraded to GitLab 19.3.4 alternatively of 19.3.5 (which had the fix) by mistake
Oct 12	GitLab releases the fix

What we cognize and what we can’t regulation out

What we found

Alpine releases and packages were not modified. The October 21 stable releases (3.21.9, 3.22.7, 3.23.7, 3.24.3), including their ISO images and the minirootfs tarballs the authoritative alpine Docker images are built from, and all packages built from October 20 to 24 came from aports commits we verified against records exterior GitLab. See the FAQ below for details.
No signing keys were exposed. The keys that sign Alpine packages and releases are not, and never have been, stored on the GitLab server.
No evidence that the attacker’s code ran: timing probes showed no delays, and we established no unexpected files, keys, hooks or processes.
No personal data was returned to the attacker through any web or API petition we can see.

Why we can’t be sure

A prosperous utilize would depart no collision and no trace in the web logs.
Some logs from the assault day are gone (background job logs, the old container’s filesystem).
We had no logging of outbound network connections, and our hosting provider keeps none either.

What could have been exposed if the assault succeeded

Email addresses, names and IP addresses of all users
Password hashes
2FA secrets, CI/CD variables and runner tokens
Webhook, integration and shove mirror credentials
Personal admission tokens (stored as hashes)
Private repositories, and confidential issues and merge requests

FAQ

Why did we rebuild GitLab if we were capable to mitigate the attack?

Because we cannot regulation out code execution, and the evidence we would need to verify it no longer exists, we took the harder path and rebuilt the GitLab case from scratch. This removes any foothold a perchance prosperous utilize could have remaining behind.

While GitLab is closed, our bundle mirrors, cgit, and mailing lists/IRC are accessible as normal.

Are Alpine packages and releases affected?

We have established no sign of tampering in aports or the releases.

Every aports commit added October 20 to 22 arrived through a recorded shove by a known developer. We checked this against records the attacker could not reach: a developer’s copy and all 45 builders. Every bundle built from October 20 to 24, on all architecture, came from commits as published on git.alpinelinux.org. The October 21 releases (3.21.9, 3.22.7, 3.23.7, 3.24.3) were built from those identical verified commits.

We ran these checks on October 24, covering commits from October 20 to 22 and packages built up to October 24. Our GitLab stayed susceptible until we closed it on October 27, so we are extending the identical checks to that date.

Is Alpine’s ruby bundle affected?

The bug is in Ruby’s regular expression engine, so any program that compiles regular expressions from untrusted input is exposed, not lone GitLab. Alpine 3.22, 3.23, 3.24 and border container Ruby 3.4.12, and Alpine 3.21 ships Ruby 3.3.13; the two contain the fix. Run apk upgrade to get it.

What are we changing in reply to this event?

Fixed Ruby: the rebuilt case runs a Ruby alongside the fix (3.3.13 or later).
Faster patching: use crucial GitLab safety releases inside a day, and inspect all publish for Ruby or another component patches our own build must apply.
Better logging: document outbound connections from the GitLab presenter and repository connections, and keep logs longer than 14 days.
Signed publish tags, so releases can be verified independently of GitLab.

Google Says Lower AI Mode Monetization Weighed On Search Growth

support@mycoding.id (Matt G. Southern) — Thu, 29 Oct 2026 00:12:24 +0700

Alphabet’s (GOOGL) Google Search & Other row had a 12% addition in year-over-year income in Q3 2026 to $63.35 billion. Search income growth has been slowing downward for two quarters now, following being at 19% in Q1 and 17% in Q2; and Search income was basically flat compared to final quarter’s $63.27 billion.

On Alphabet’s earnings call, Chief Business Officer Philipp Schindler mentioned that lesser monetization inside AI Mode was one of three reasons for the slower growth.

In supplement to announcing expanded preparedness of ads in AI Mode in ten additional markets, Alphabet additionally stated that it is launching ads in AI Mode follow-on inquiry functionality in the United States. All existing Search, Shopping, and Performance Max campaigns are eligible by default and cannot opt out separately.

Why Search Growth Slowed

The biggest aspect driving the hunt dilatory downward compared to Q2 was, according to Schindler, prosperity movements. Retail additionally informed an impact, he said, alongside certain Asia-Pacific advertisers affected by the E.U. eliminating its de minimis exemption for low-value imports. Media and amusement saw spending normalize following a powerful Q2 which included the FIFA World Cup.

Google CFO Anat Ashkenazi stated that prosperity movement was a small headwind to the twelvemonth complete twelvemonth growth and a larger headwind to the fourth complete fourth growth. Ashkenazi additionally mentioned that there was a tougher difference since the hunt growth continued to accelerate throughout the second fractional of 2025.

On the Q2 earnings gathering call in July, Ashkenazi had signaled the two items stating that Google expected a minor FX headwind in Q3 chiefly in Search & YouTube ads. Additionally, she stated that hunt would commencement lapping final year’s acceleration in Q3.

In my prior report I noted in July that Q2 was the archetypal period we had seen a dilatory downward in hunt growth following 4 quarters of accelerating growth. The matter at hand afterward was if it was a impermanent dilatory downward or if it represented the commencement of a duration of slowing growth.

What Google Said About AI Mode Monetization

CEO Sundar Pichai stated during the earnings notice that AI funding has driven Search query growth (including business queries) as fine as the “year-over-year query growth charge is the highest it’s been in the final five years.”

During the call alongside investors, J.P. Morgan expert Doug Anmuth questioned the difference in twelvemonth complete twelvemonth query growth and Search ad income growth. Schindler noted it was currency, retailing and media archetypal and afterward stated that powerful AI manner query growth negatively affected hunt income growth because of lesser monetization in AI Mode. He did not province what AI mode’s monetization was lesser than, nor the amount of prosperity this affected hunt ad revenue.

Pichai told analysts:

“Just akin our change to mobile complete a decade ago, we are focused on construction the finest Search person experience, followed by monetization.”

In his prepared remarks, Schindler stated many of the new questions group ask in AI-powered Search are upper-funnel, and that the bulk of AI Mode queries are incremental, which he stated creates additional monetization opportunities complete time.

In Google’s notice post, Shashi Thakur, VP and GM of Google Search Ads and Ads on Google Experiences, wrote:

“Our investigation shows that group are comfortable alongside ads in AI Mode and discover them extremely relevant. In fact, click-through rates are already akin between sponsored and integrated merchandise catalog items inside AI Mode.”

A footnote references a origin of Google’s click through comparison, which is inner data for Google in the United States for the period duration August 20th thru September 3rd of 2026.

At the Google Marketing Live event in May of 2025, Thakur stated to reporters, including me, that AI Overviews create income “at the identical rate” as those exact searches whenever there are no overviews. This assertion covered AI Overviews, but does not contain data on AI mode.

Ads In AI Mode Expand To 10 Countries

Google is scaling ads in AI Mode in Australia, Canada, India, Kenya, Malaysia, New Zealand, Nigeria, Pakistan, the Philippines, and Singapore.

Google Ads / Market Expansion

Where AI Mode ads are expanding

Google named 10 markets anywhere ads are scaling, affirmative additional locales planned for Q4 2026.

SCALING

10 countries

PLANNED Q4

3 named*

Highlighted markets are those named in the Oct. 28 announcement. Unmarked countries are not an preparedness statement. *Q4 examples are not an exhaustive list.

Americas

Scaling: Canada

Planned: Brazil, Mexico

Europe & Africa

Scaling: Kenya, Nigeria

Planned: U.K.

Asia-Pacific

Scaling: Australia, India, Malaysia, New Zealand, Pakistan, Philippines, Singapore

Source: Google Ads & Commerce · Oct. 28, 2026Illustration: SEJ · Country outlines: Natural Earth

The article additionally says Google is launching multiturn ads in the U.S., which authorize ads in follow-up queries in AI Mode.

Google’s assistance leaf on ads in AI-powered Search experiences states that advertisers cannot immediately mark AI Overviews or AI Mode individually, nevertheless negative keywords & brand exclusions volition continue to apply.

When a query has straightforward business intent, exact equivalent and expression equivalent keywords can serve; however, these types of keywords do not meet requirements for contextual matching on broader, exploratory-type questions. AI Max for Search, broad match, Shopping campaigns and Performance Max all meet requirements for both.

Placements that have AI explainers transport abbreviated content generated by Gemini from the person query, the AI reply and community sources (including the advertiser’s website). The advertiser has no capability to create, edit, endorse or opt out of this content. Google announced AI explainers at Google Marketing Live in May.

Results are included in norm reporting as part of total reporting for campaigns and hunt conditions reports. The assistance leaf lists English as the tongue for ads inside AI Overviews and AI Mode and additionally indicates lone content ads volition be accessible in Pakistan.

Why This Matters

Google tied the two its highest query growth charge in five years and part of its income slowdown to AI.

How much AI Mode inventory a run can attain depends on whether it uses AI-powered targeting specified as broad equivalent or AI Max, and norm reports merge AI Mode results alongside the remainder of Search.

In Q2, Pichai stated Google was sending “billions of clicks to websites all week” through AI features in Search. His published Q3 remarks and the call didn’t contain a clicks figure, so the fourth adds item on how Google makes prosperity from AI Mode but none on traffic to websites.

Looking Ahead

CFO Anat Ashkenazi stated that in Q4, at current place rates, Google expects a slightly larger prosperity headwind, mostly in Search and YouTube ads, and that continuing to lap final year’s Search acceleration volition force growth.

Google plans to develop ads in AI Mode to additional locales in Q4 2026, including Brazil, Mexico, and the U.K.

Featured Image: PixieMe/Shutterstock

Category News AI Search

Adam Mosseri says negativity around AI is ‘going to get worse’

support@mycoding.id (Stevie Bonifield) — Thu, 29 Oct 2026 00:05:39 +0700

Stevie Bonifield

is a news author covering all things person tech. Stevie started out at Laptop Mag penning news and reviews on hardware, gaming, and AI.

Asked concerning AI and the trend of college students booing tech CEOs at graduation ceremonies, Instagram caput Adam Mosseri acknowledged in an discussion that a lot of group really don’t akin AI, and it’s not fair young group and creatives. Appearing on the Colin and Samir podcast to conversation concerning the initiate of widescreen and long-form video for Instagram, Mosseri stated he thinks there’s a trend of “more anxiety and additional frustration and additional rage concerning AI,” particularly in imaginative industries:

It’s not lone getting worse, it’s going to continue to get worse. I think we’re going to see additional frustration and anger, several of it founded, several of it unfounded, complete the next brace of years, and that’s going to create it difficult for a lot of people, not fair in the industry.

Mosseri claimed Instagram doesn’t position AI creators differently, but raised the inquiry of ranking quality, saying, “There’s a lot of awesome AI satisfied out there, there’s additionally a lot of AI slop. Do we position AI satisfied as fine as we position non-AI content? Probably not.” Talking concerning AI slop again following earlier bringing it up in a New Year’s slideshow dump, he stated he thinks the term AI “slop” is used “too liberally.”

Instagram began cracking downward on AI-generated profiles in August, following launching a label for AI accounts before this year, but misleading AI satisfied akin celebrity deepfakes remains an issue. Earlier this month, Mosseri said Instagram is “actively operating out what to do” concerning AI fakes, but he noted, “I don’t think it’s applicable for us to try and ban AI satisfied from the platform.”

Mosseri stated Instagram is “now starting to necessitate AI accounts to tag themselves, since we think it’s crucial that group cognize if what they’re looking at is genuine or not real.” He additionally acknowledged there are fears about AI, including from creators:

I think group are concerned concerning a lot of things. I think they’re concerned concerning owning their satisfied and models getting trained on their content. I think they’re concerned— there’s group who are concerned concerning safety. They’re concerned concerning job displacement, having AI displace any it is they do, if you’re a satisfied creator or an engineer or a mathematician. I think there’s concerns about— I mean, basically what I think it comes downward to whenever you really have, like, a heart-to-heart alongside person is a fear of being remaining rearward in several way.

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Stevie Bonifield

The Verge Daily

A liberated regular digest of the news that matters most.

Microsoft cuts capex forecast on AI capacity delays

support@mycoding.id (Ashley Stewart) — Wed, 28 Oct 2026 23:58:41 +0700

Microsoft CEO Satya Nadella. Dimitar DILKOFF / AFP via Getty Images

Microsoft reduced its forecast for chief expenditure, a rare move in an industry that mostly continues to splurge additional on huge AI investments.

The application elephantine stated capex for the 2026 calendar twelvemonth volition be $170 milliard from a previous forecast of $175 billion.

Chief Financial Officer Amy Hood gave the forecast on the company's financial first-quarter earnings call on Wednesday.

She stated Microsoft was expecting new capability to attain from third-parties, but several of these "GPU-as-a-Service contracts" have been delayed until the second fractional of the financial year.

This apt refers to another providers of AI haze services that use Nvidia GPUs to run their offerings. Microsoft has partnered alongside a several exterior providers to encounter rampant AI demand.

Hoods comments could mention to a latest spate of AI data center project delays, which have mostly been caused by a deficiency of electricity, alongside alongside local opposition.

The CFO stated Microsoft expects capex to accelerate in the second fractional of its financial year, as the delayed capability kicks in.

Wall Street has rotate into increasingly concerned the huge investments haze companies are making to develop AI infrastructure. Microsoft final fourth kept its forecast unchanged, notable as many haze giants have been steadily expanding their AI spending forecasts.

Overall, Microsoft reported $92.3 milliard in revenue, up 19%, for the financial first-quarter ending Sept. 30. Azure haze income was up 48% to additional than $33 billion, surpassing Wall Street expectations.

Microsoft portion were up concerning about 3% in after-hours selling following the earnings call.

Earlier this week, Microsoft offered a buyout to additional than a fourth of its workforce. A Microsoft spokesman told Business Insider on Wednesday that the business expects 5% of eligible employees at most to obtain the buyout.

"We anticipate extremely few group to choose this recommendation since of the growth opportunities current at Microsoft," Hood wrote in an inner memo viewed by Business Insider. Microsoft's headcount slipped 2% during the financial archetypal quarter, the business reported.

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Claude Code found 145K photos I deleted from my iPhone sitting in a hidden cache

support@mycoding.id (Doris Putra) — Wed, 28 Oct 2026 23:34:30 +0700

Claude Code established 145,763 photos I permanently deleted from my iPhone. Three years of deleted photos and videos motionless sitting in a hidden cache. Any app alongside document admission can peruse them. I plugged my iPhone into my MacBook to run a backup. Claude Code was doing the safety audit from my final article and flagged a directory I wasn't equal looking for. PhotoData/Thumbnails. Over 146,000 files. Photos, videos, screenshots. Every sole one was item I deleted. Photos from 2023, 2024 and 2025. The ones I deleted the second following taking them. The ones I cleared from Recently Deleted. The ones I deleted three distinct times since I wanted to be certain they were gone. All motionless there. Passport photo I took for a visa use in 2023. Screenshots of my financial institution app alongside complete document numbers visible. Private photos I sent person and immediately deleted following a breakup. Screenshot of my crypto kernel expression I took temporarily in 2022. Photo of my ID and credit cardstock I took to recall the numbers and deleted 5 seconds later. Screenshots of my ex's personal Instagram stories I saved and permanently deleted in 2023. Some were complete resolution. All organized by date going rear to 2021. When you delete a photo on iPhone, iOS removes it from your camera rotate and Recently Deleted. It keeps a compressed copy in a Spotlight hunt indicator cache so your phone can discover things whenever you search. Apple never clears it. Not following 30 days. Not following a year. Never. They told you it was permanently deleted. It wasn't. I checked which apps on my phone had Files and Folders access. 23 apps. Weather apps. QR code scanners. PDF readers. A flashlight app I downloaded in 2022. Any one of them could have been study all photo I always deleted this complete time. Went from 23 apps to 3 in concerning two minutes. Full stage by stage below. Takes 2 minutes. Save it so you don't endure it and dispatch it to anyone alongside an iPhone.

Google Business Profiles Finally Adds Third-Party Ordering Controls

support@mycoding.id (Barry@Rustybrick.com (Barry Schwartz)) — Wed, 28 Oct 2026 23:32:00 +0700

Google has eventually added the capability to oversee and authority third-party ordering services on an idiosyncratic basis for restaurants inside Google Business Profiles. So you can disable features entirely or partially from inside Google Business Profiles.

So if you desire to rotate off Uber Eats, DoorDash, Instacart, Grubhub or others, you have to be capable to.

This was announced by Lisa Landsman from Google on LinkedIn who wrote, "One of the most common requests we comprehend from eatery operators is simple: additional authority complete their ordering links."

Restaurants now have straightforward authority complete which third-party ordering options appear on your Business Profile on Google Search and Maps. "Instead of submitting requests to idiosyncratic shipment platforms to eliminate or disconnect a feed, you can now oversee and opt out of particular providers immediately from your dashboard," Lisa explained.

Here is a screenshot she uploaded; I conjecture substitute Provider.com alongside the delivery/order service:

It looks akin you can authority whether to display this ordering choice as pickup and/or delivery.

Lisa added:

Direct control, zero back-and-forth: You decide which partners portray your brand on your profile. If an integration no longer fits your operations, margins, or galley flow, you can rotate it off yourself.
The power of diner choice: While straightforward ordering is continually a priority, keeping a mix of trusted providers can additionally activity in your favor. Diners frequently rod to the platforms anywhere they clasp energetic subscriptions or stored fee details. Giving them choices can average capturing an command that power alternatively go elsewhere.
Regular audits keep menus fresh: Take a instant this week to inspect your profile, assessment your energetic ordering channels, and justify all nexus leads to an exact list and a gentle visitant experience.

This is certainly a feature restaurants have been begging for for many years.

Forum conversation at LinkedIn and Local Search Forum.

Google Expands Ads In AI Mode To More Countries & Multiturn Ads In U.S.

support@mycoding.id (Barry@Rustybrick.com (Barry Schwartz)) — Wed, 28 Oct 2026 23:30:00 +0700

Google is expanding ads inside AI Mode to additional countries and is rolling out multiturn ads in the U.S. inside AI Mode.

Ads Expand In AI Mode To More Countries

Google announced it is expanding ads in AI Mode to multiple additional countries, including Australia, Canada, India, Kenya, Malaysia, New Zealand, Nigeria, Pakistan, the Philippines, and Singapore. Then, in Q4, Google volition additionally develop ads in AI Mode to Brazil, Mexico, and the United Kingdom.

Here is a adorable explanatory of the expansion:

Google additionally lately launched ads in AI Mode in individual intelligence but Google initially launched ads in AI Mode in May 2025.

Google said, "click-through rates are already akin between sponsored and integrated merchandise catalog items inside AI Mode." I would anticipation so, but I am not certain - I mean, the merchandise results are excellent graphical - but what concerning the content links?

Multiturn Ads

Google said, "To authorize ads in follow-up queries in AI Mode, we are launching multiturn ads in the U.S." Google explained, "Google Search offers generative AI experiences tailored to distinct types of questions, from quick snapshots on the Search results leaf alongside AI Overviews to multi-turn conversations and comparisons in AI Mode. When a hunt or conversation has business relevance, ads can appear immediately inside or alongside these AI-generated responses (including throughout follow-up questions in AI Mode) in sections plainly tagged "Sponsored", assisting group obtain the next step."

A Google spokesman clarified to us saying, "Multiturn ads display up on responses to follow-up person queries as users affect in rear and onward conversations alongside AI Mode."

Google added, "Ads volition be plainly tagged as “Sponsored.” We’ll continue evaluation new formats to justify ads remain helpful and relevant."

Forum conversation at X.

WordPress Announces Another Security Release: Version 7.1.4

support@mycoding.id (Roger Montti) — Wed, 28 Oct 2026 23:14:34 +0700

WordPress announced a safety release, type 7.1.4, intended to fix 22 vulnerabilities, including a possibly hazardous weakness in the update procedure and many stored cross-site scripting vulnerabilities.

This publish contains three important kinds of fixes:

1. The WordPress update procedure itself was vulnerable.
A competition circumstance could authorize distant code implementation during the upgrade window. This is arguably the most consequential of the discovered flaws that is being patched since these kinds of vulnerabilities can guide to a complete location takeover. The authoritative notice nevertheless does not recommendation data concerning the conditions necessary to utilize it.

2. The vulnerabilities broaden throughout WordPress’s editing and interactive functionality.
Multiple issues power the Interactivity API, blocks, the Customizer, and administrative interfaces alongside several of involving unauthorized disclosure of information. Many of these exploits necessitate Contributor-level admission or higher, which minimizes the likelihood of exploitation. but several involve.

3. The safety problems power latest and older WordPress versions.
This safety publish fixes vulnerabilities that date rear as far as WordPress 4.7, alongside the figure of applicable vulnerabilities varying by version. This reflects how chief several of the affected components are inside the WordPress center itself.

WordPress Fixes Remote Code Execution Risk In Its Update Process

Security investigator Umut Bayram discovered a competition circumstance affecting WordPress center updates. Under certain conditions, this exposure could guide to distant code implementation (RCE). Remote code implementation (RCE) is a safety exposure that enables an attacker to run malicious commands or application on a website’s server from a distant location. Depending on the attacker’s flat of access, this can guide to item from taken data to a complete website takeover.

The notice rightfully leaves out many particulars of the vulnerabilities, apt to create it harder to exploit. So it’s not known what admission or server conditions are necessary to utilize the update competition circumstance or whether authentication is required.

Featured Image by Shutterstock/Luis Molinero

Category News WordPress

Google Lets Restaurants Directly Opt Out Of Ordering Providers

support@mycoding.id (Matt G. Southern) — Wed, 28 Oct 2026 23:11:43 +0700

Restaurants can now opt out of particular third-party ordering providers correct from their Google Business Profile dashboard, according to a LinkedIn post by Google’s Lisa Landsman. This environment lets restaurants choose which ordering options appear on their profiles in Search and Maps.

Asked in the post’s comments which countries have it, Michael G., a merchandise director at Google, replied “all.”

Before this, a eatery could ask to eliminate a provider from inner Business Profile, but the provider had to procedure the request. Google’s help leaf for ordering options gives providers five endeavor days to obtain the nexus down.

How The Setting Works

A screenshot in the LinkedIn article announcing the environment shows a “Manage provider” panel for a placeholder provider, www.provider.com. Under the heading “Show provider to customers,” the panel has distinct switches for pickup and delivery, the two on in the image.

Landsman, Google’s Head of Industry Engagement & SMB Success, wrote that restaurants can skip sending a petition to all shipment platform. If a provider no longer suits a restaurant’s operations or margins, she wrote, “you can rotate it off yourself.”

She additionally made the case for keeping several providers listed, penning that diners lean to command through apps anywhere they already pay for a subscription or have a cardstock saved, so listing those apps can keep those orders from going location else.

From Removal Requests To Direct Controls

According to an archive of Google’s compliance guideline for ordering providers made in May, the burden was placed alongside all ordering provider to provision restaurants a method (such as a elimination form or a help/support ticket) to obtain themselves out of the ordering provider’s nourish to Google.

Under that policy, providers had five endeavor days to assessment and complete an opt-out request.

The current type of this page, which was most lately updated Oct. 19, does not merge that requirement. The current type states that merchants may allow or disable idiosyncratic provider integrations through merchandise controls; it additionally states “All partner integrations are enabled by default.” It additionally motionless says providers have to autumn any eatery that asks to be removed from their feed.

Why This Matters

A provider that you do not desire to display in a endeavor overview can now be turned off for pickup, delivery, or the two from the Business Profile dashboard.

On Google’s guideline leaf for ordering providers, integrations are enabled whenever archetypal set up. Therefore, for all eatery overview you manage, the provider catalog under “Food ordering” belongs on your checklist.

Looking Ahead

As of Oct. 28, a Google assistance leaf on ordering options describing how to use the “Remove link” choice does not contain data on the “Show provider to customers” option. Also, the LinkedIn article did not province if the new environment volition activity in bulk or through the Business Profile API, which commenters asked about.

Featured Image: Gorodenkoff/Shutterstock

Source: Google.

Category News Local Search

A hacker stole more than 40,000 DHS employee records

support@mycoding.id (Emma Roth) — Wed, 28 Oct 2026 22:57:45 +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.

A hacker stole a trove of individual data from the Department of Homeland Security (DHS). The breach exposes the names, job titles, phone numbers, email addresses, and agency locations of additional than 41,000 employees, including those in US Immigration and Customs Enforcement (ICE) and Customs and Border Protection (CBP), according to TechCrunch and Wired. The data additionally connected the agencies to particular surveillance tools.

As reported by TechCrunch, a hacker known as “Department of Peace” gained admission to the data through Okta, an character and admission administration assistance used by the DHS. Around 21,000 records pertain to CBP employees, and nearly 7,000 pertain to personnel at ICE. The data additionally includes records from the Cybersecurity and Infrastructure Security Agency (CISA), US Citizenship and Immigration Services (USCIS), and Homeland Security Investigations (HSI).

The DHS has worked to conceal the identities of CBP and ICE agents, who have carried out anti-immigration raids about the US, during additionally tracking downward online critics. “They have our information, so it’s lone fair that we have theirs,” the “Department of Peace” hacker said, according to TechCrunch. This leak comes fair weeks after hackers stole data from the FBI on its workforce and job applicants.

The leaked DHS data was reportedly stated to hacktivist maia arson crimew, who shared it alongside Distributed Denial of Secrets (DDoSecrets), a nonprofit institution that’s now hosting the leaked “Icepick” dataset. The leak additionally reportedly includes data concerning DHS groups that have admission to tools that can be used for surveillance, specified as the facial acknowledgment app Mobile Fortify and PenLink, which can collect and analyze data from phones and online services.

The DHS didn’t immediately react to The Verge’s petition for comment.

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Emma Roth

Akai is embracing vibe-coded mods with an open-source MPC

support@mycoding.id (Terrence O’brien) — Wed, 28 Oct 2026 22:34:04 +0700

Terrence O'Brien

is the Verge’s weekend editor. He’s covered the tech industry for complete 18 years and knows a item or two concerning synths.

The MPC Sample Key isn’t equal formally announced yet, but Akai is already showing off what the modding community is cooking up through vibe coding. Akai has decided to clasp the explosion of hackers and tradition firmware developers by giving them first admission to the device, which volition have open-source firmware.

It volition apt run several type of the identical application established on the MPC Sample, but alongside tweaks to modify the traditional keyboard, pitch, and mod wheels. Unlike the higher-end MPC Key 37, however, the Sample Key doesn’t have pads. Instead, you perform rear samples alongside the keys.

In the abbreviated Instagram Reels posted last night and today, Akai shows a figure of vibe-coded mods that add synths, including Native Instruments Massive, to the device, as fine as virtual analog and FM synths. One is equal shown operating a entirely tradition OS, alongside “several distinct synths in it.”

According to the clips, the identical “community” features volition arrive to the regular MPC Sample, which is additionally shown operating a few vibe-coded synths built by Claude. That could average Akai plans to open-source the complete MPC Sample platform.

CEO Jack O’Donnell told The Verge that inMusic brands, particularly Akai, would be looking to clasp the modding community by seeding first devices to developers. These efforts volition additionally contain open-sourcing several application and providing an SDK.

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Terrence O'Brien

Formlabs Studio 1 $699 Resin Printer

support@mycoding.id (Riki Setiawan) — Wed, 28 Oct 2026 22:19:30 +0700

First Alpha Resin continually $29! Discounts auto-apply at checkout.

$42Alpha Model Resin

Finely detailed parts

Alpha Model Resin

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Create detailed measure models, life-like sculptures, and richly textured miniatures alongside lean features that flex alternatively of snapping, so completed models last painting, transport, and drops.

The Alpha Resin Family uses low-odor components and post-processed parts encounter safety requirements for long-term skin contact. Alpha Resins are the archetypal 3D printing materials certified for UL GREENGUARD Gold, whenever printed on Form Studio 1 and using VOC Extractor.

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Tech specs

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Print TechnologySLA

CategoriesGeneral Purpose

ApplicationsModels & Props

Ultimate Tensile Strength

40 MPa

Heat Deflection Temp. @ 0.45 MPa

49 ℃

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$42

$29Alpha Fast Resin

Rapid iterative prototypes

Alpha Fast Resin

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Build prototypes faster or quickly create jigs, fixtures, and tooling alongside a tensile power of 46 MPa and 34% elongation at break.

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Compatible PrinterForm Studio 1

Print TechnologySLA

CategoriesGeneral Purpose

Ultimate Tensile Strength

46 MPa

Heat Deflection Temp. @ 0.45 MPa

59 ℃

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150 μm

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90 mm/h

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$29

$36Alpha Grey Resin

Alpha Grey Resin

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Alpha Grey Resin is lone supported on the Form Studio 1.

Tech specs

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Print TechnologySLA

ColorsGrey

CategoriesGeneral Purpose

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Ultimate Tensile Strength

43 MPa

Heat Deflection Temp. @ 0.45 MPa

55 °C

Key Characteristics

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Primary Layer Height

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prototyping, jigs, and fixtures

$36

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Alpha Clear Resin

Alpha Clear Resin is a versatile transparent 3D printing resin for aesthetic, functional parts, combining an optically clear, neutral-color appearance alongside accelerated imprint speeds and better mechanical properties.

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Alpha Clear Resin is lone supported on the Form Studio 1.

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Print TechnologySLA

CategoriesGeneral Purpose

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ColorsTransparent

Ultimate Tensile Strength

38 MPa

Heat Deflection Temp. @ 0.45 MPa

57 ℃

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$36

$36Alpha Black Resin

Alpha Black Resin

Alpha Black Resin is a versatile broad intent resin for aesthetic, functional parts, combining fine item and a rich, matte complete alongside accelerated imprint speeds and better mechanical properties.

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Alpha Black Resin is lone supported on the Form Studio 1.

Tech specs

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Print TechnologySLA

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Ultimate Tensile Strength

42 MPa

Heat Deflection Temp. @ 0.45 MPa

55 ℃

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Average Print Speed

40 mm/h

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100 μm

$36

$36Alpha White Resin

Alpha White Resin

Alpha White Resin is a versatile broad intent resin for aesthetic, functional parts, combining fine item and a rich, matte complete alongside accelerated imprint speeds and better mechanical properties.

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Alpha White Resin is lone supported on the Form Studio 1.

Tech specs

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Print TechnologySLA

ColorsWhite

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Ultimate Tensile Strength

35 MPa

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51 ℃

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$36

$79Tough 1500 Resin V2

Stiff and impact-resistant

Tough 1500 Resin V2

Tough 1500 Resin V2 is a resilient matter alongside strength, stiffness, and toughness comparable to polypropylene (PP), offering exceptional opposition to fractures, impacts, and shattering.

Create parts that balance stiffness and ductility, whether for compliant mechanisms or rugged enclosures alongside self-tapping screws and break fits. Tough 1500 Resin V2 enables a broad range of applications, from functional prototypes to end-use jigs and fixtures.

This resin is supported on Form Studio 1 and incompatible alongside Form 4 Generation printers. For Form 4 Generation printers use Tough 1500 (Form 4).

Tech specs

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ColorsGrey

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Ultimate Tensile Strength34.0 MPa

Tensile Modulus1460.0 MPa

Flexural Strength41.0 MPa

Flexural Modulus1370.0 MPa

Notched Izod42.0 J/m

Elongation at Break155.0 %

Heat Deflection Temp. @ 1.8 MPa53.0 °C

Heat Deflection Temp. @ 0.45 MPa66.0 °C

Unnotched Izod910.0 J/m

Gardner at 1/32" (0.97 mm) thickness5.9 J

Gardner at 1/16" (1.9 mm) thickness11.1 J

Ross Flexing Fatigue8000.0 cycles

Maximum Stress Intensity Factor (Kmax)1.7 MPa-m1/2

Work of Fracture (Wf)1011.0 J/m

Recommended application

Parts that need a blend of stiffness and ductility to create compliant mechanisms akin latches, flexures, and dampers Clasps and buckles, self-tapping screw bosses, hinges

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Comparable Thermoplastic

$79

$199Flexible 80A Resin V2

Elastomeric, tear-resistant

Flexible 80A Resin V2

Flexible 80A Resin V2 is a resilient 3D printing elastomer that rivals the look, feel, and function of 80A mold urethanes, TPUs, and difficult rubbers.

Parts printed in Flexible 80A Resin V2 break rear into location and withstand repeated bending, tension, and compression. Create tear-resistant functional prototypes and end use parts, defend delicate components alongside gentle inserts and fixtures, or scheme refined padding and grips alongside tack-free surfaces and a matte, dreary finish.

Flexible 80A Resin V2 is a new matter formulation that leverages the innovation of Form 4 Series printers to provision 2x higher tear strength, 2x higher elongation at break, 4x higher rebound, and improved aesthetics and aging compared to the former version.

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Print TechnologySLA

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Ultimate Tensile Strength

10 MPa

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Comparable to

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$199

$199True Cast Resin

Wax-filled, low ash burnout

True Cast Resin

True Cast Resin is a wax-filled matter designed for precision casting of intricate jewelry to complex engineering components up to 5 mm thick. It delivers extremely exact parts alongside exceptional item and gentle surfaces.

Engineered for reliability, quality, and versatility, True Cast Resin integrates effortlessly into a broad range of burnout schedules. Low thermal expansion, minimal shrinkage, and 0.03% ash satisfied justify spotless burnout and consistently outstanding casting outcomes.

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Print TechnologySLA

Minimum Layer Thickness25 micron

ColorsPurple

CategoriesCasting

ApplicationsRapid Tooling

Ash Content0.03 %

Thermal Expansion174.1 μm/m/°C

$199

Readwise is taking on Kindle and Kobo for ebook supremacy

support@mycoding.id (David Pierce) — Wed, 28 Oct 2026 22:16:18 +0700

For the final multiple years, Readwise has been construction tools for power readers. There’s the eponymous product, Readwise, which stores and categorizes your Kindle highlights to assistance you recall what you’ve read. There’s Readwise Reader, an app for study newsletters, PDFs, and web articles you’ve saved for later. And now there’s Readwise Books, a full-fledged phase for buying, reading, and talking concerning books.

Readwise Books is currently in beta, accessible through invitation or to existing Readwise subscribers. I’ve been evaluation the app for a few days, and it’s a much bigger obtain on study than most. Tristan Homsi and Daniel Doyon, Readwise’s cofounders, akin to call the phase “Strava for reading” since it can track how long, how much, and how accelerated you read, and it can display that data to allies you create in the Readwise Books app. The app’s homepage is a nourish of what another group are reading, alongside comments and recommendations laced throughout.

“Strava for reading” wasn’t the first goal of Readwise Books, which has been part of the Readwise scheme since the beginning. “Literally, Dan and I talked concerning this whenever we archetypal met,” Homsi says. “We awareness akin Kindle could be so much better. We really didn’t think it would obtain nine-plus years to be capable to get to this point.” But it turns out, Doyon adds, that for all their ideas concerning innovation in books, “no one sits about wanting a improved Kindle.” But there is one item they do desire for: a improved Goodreads. “Everybody hates Goodreads.”

In a sense, then, the scheme for Readwise Books is to obtain on Kindle by archetypal taking on Goodreads. The Readwise Books app offers a nice way to track books you desire to read, are reading, and have read; it equal syncs alongside your Kindle document to let you track books you’ve bought from Amazon by taking pictures of your starting and ending pages. You can charge and assessment books and see what others have said. It’s a small Strava, a small Letterboxd, and a lot nicer to appearance at than Goodreads.

The long-term goal, of course, is to get group to halt purchasing Kindle books and commencement purchasing from Readwise. Homsi and Doyon have spent the final multiple years operating to attain deals alongside all five of the important US publishers in command to have a rivalrous archive of books available. That meant endless negotiations, safety reviews, DRM debates, and additional — the two cofounders appear exhausted fair talking concerning the process. But eventually, by multiple small miracles, they got the deals done. And since those deals govern the cost of books, and many things concerning how they’re sold and presented, they bring Readwise to a nearly equal playing site nearly immediately.

It all took a lot longer than expected, but Doyon and Homsi think their timing power really be beautiful good. Digital publish study continues to grow, particularly among young people; a huge amount of that study happens on phones and tablets. Meanwhile, a new crop of E Ink devices akin the small Xteink and the Boox Palma row have expanded the cosmos of accessible hardware for a business akin Readwise.

Not lengthy ago, Doyon says, they would have had no choice but to build an e-reader of their own. (And he says they motionless might.) Now, they can fair create certain it runs on an E Ink-friendly sensation of Android.

After a brace of days using Readwise Books, I can say confidently I already akin it improved than practically all of its competition. It’s a much nicer-looking app than item you’ll get from Kindle or Kobo; it has many of ways to customize how books look; and at smallest for now, I’m finding the tracking features compel me to peruse additional alternatively of annoying me. (Homsi says several first versions of the gamification features were substantially additional annoying.) I’ve established a few bugs, and the half-integration alongside Kindle is a small confusing in spots, but it’s already a really nice location to read.

Of course, I, akin millions of another people, already own a Kindle and many of Kindle books. Switching ebook platforms is hard, and Doyon says he’s not counting on everyone to do it correct away. He says he’s hopeful Readwise can convince existing users to switch, in command to sync their notes and advancement additional seamlessly. He’s additionally expecting that the advent of AI, and the ways in which AI reliance may rot our brains, volition get a lot of group rear into the idea of study additional deeply again. And that a bunch of those group power be looking for a nicer, additional social location to do so.

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David Pierce

Albertsons won't insure employees' spouses if they're eligible for their own health coverage

support@mycoding.id (Dominick Reuter) — Wed, 28 Oct 2026 22:15:37 +0700

Albertsons is making multiple changes to its employee benefits to oversee rising expenses for 2027. Jason Armond / Los Angeles Times via Getty Images

Albertsons is curbing health attention benefits for workforce because of rising healthcare costs.

Starting next year, the market elephantine volition no longer recommendation medicinal coverage plans to employees' spouses and family partners who have jobs that provision specified coverage. The market elephantine detailed the alter in an open enrollment guide posted to its website.

Albertsons stated it expects its healthcare expenses to addition 9.5% next twelvemonth because of inflation, higher medication medication costs, provider consolidation, and shortages in the healthcare workforce.

"We are making changes to our benefits in 2027 to decrease the projected disbursal addition during motionless maintaining a norm benefits program that meets the needs of our associates at a disbursal sustainable for the business going forward," it said.

The business did not immediately react to a petition for comment.

Other changes this twelvemonth contain higher weekly paycheck contributions from employees, the elimination of two network plans, alongside alongside higher deductibles and out-of-pocket maximums for several another plans.

Large companies Disney, Starbucks, and Deloitte have additionally introduced cost-saving changes to their benefits packages for 2027. Disney is additionally dropping safety for partners and spouses who can get coverage from their own jobs.

"We've seen employers reducing their contribution toward the spouse's coverage, but not eliminating the safety choice for those people," Capitol Benefits CEO Joshua Lavine told Business Insider in August, concerning Disney's decision.

Leak Exposes 41,000 Homeland Security Workers–Including Undercover ICE Agents

support@mycoding.id (Riki Setiawan) — Wed, 28 Oct 2026 22:03:24 +0700

An unprecedented leak of Department of Homeland Security records has exposed particulars of additional than 41,000 workforce or contractors who activity for the division and its component agencies. The records contain email addresses, phone numbers, and agency addresses, but additionally references to inner systems and delicate data on undercover and surveillance programs. In all, the leak provides a map of how DHS is organized and how it operates.

The records, which extend DHS itself as fine as seven component agencies, including Immigration and Customs Enforcement and US Customs and Border Protection, were final updated on August 19, 2026. The transparency nonprofit Distributed Denial of Secrets and cybersecurity investigator and newsman maia arson crimew previewed the data to WIRED, which they say they obtained from a collection calling itself the Department of Peace.

DDoSecrets published the archive, which it calls "Icepick," on Wednesday. In a media release, DDoSecrets says the data is from DHS's Okta login system. In a note alongside the files, the hackers wrote, “They have our information, so it's lone fair that we have theirs.”

An Okta spokesman tells WIRED that it is unaware of any breach of its systems. “We are conscious of this report. Okta is secure, and we have no evidence our data or systems were compromised,” the spokesman says.

The leak comes as DHS has aggressively pursued its critics, seeking to unmask anonymous social media users, get customer records on protestors, and secure warrants for surveillance tools aimed at reporters. Since the commencement of the second Trump administration, DHS and the national authorities have moved to conceal DHS employees’ names and faces. The agency has additionally expanded its definition of “doxing”—a term that typically refers to publishing someone’s residence location and another individual particulars for malicious purposes—to encompass the publish of essential facts concerning community employees, akin their names and titles.

The leak follows a breach in which a collection of hackers known as ShinyHunters claimed to have taken individual data on nearly all FBI employee and their families. Law implementation agencies have arrested multiple suspects and detained another who is alleged to be part of the group.

The DHS records are searchable on a website crimew built. “I don't think we should let them scare us into not looking into them,” she tells WIRED.

DHS and DOJ did not react to WIRED’s petition for comment. The FBI referred WIRED’s enquiry to DHS.

According to a WIRED inspection of the data, CBP staffers document for additional than fractional of the records. ICE accounts for concerning 10,000, approximately a third of them in Homeland Security Investigations, ICE’s investigative wing. Another 6,200 pertain to US Citizenship and Immigration Services, and nearly 1,000 are tied to the Cybersecurity and Infrastructure Security Agency, additional than fractional of them contractors. Altogether, the records shield concerning a seventh of DHS’s workforce, revealing how DHS is structured, from elder guidance downward to idiosyncratic immigration agents and detention contractors.

Like most ample organizations, DHS uses approval groups to authority admission to inner systems, according to the leaked records. Nearly everyone named in the leak has admission to at smallest several of these systems. At HSI, 39 workforce throughout additional than a dozen site offices pertain to groups whose names contain “CUC,” which authorities court filings say stands for “certified undercover operation.” Another group, apparently based in HSI's St. Paul, Minnesota area of operations, references "Keyhole," which national court filings depict as a certified undercover procedure that lately funded HSI's undercover surveillance of Minneapolis objection groups before this year. Others citation a “Communications Intercept Center TechOps (CICTO) Program,” a “Title III Intercept Program” for wiretaps, and an “Illicit Sensor Intercept Program (ISIP).”

The names of the groups—there are complete 55,000 in all—appear to citation tools for accessing immigration court records, pulling data from seized phones, and conducting surveillance. These contain Palantir’s Falcon investigative phase and PenLink, which analyzes phone records and social media.

Two approval groups, named “Executive Leadership” and “AI Access,” appear to catalog group stated exceptions to DHS's web filter, which blocks several websites for employees. They merge the identical 13 people, including erstwhile DHS caput Kristi Noem; Antoine McCord, the lately departed DHS chief data authoritative who has returned to defence tech business Anduril; Philip Hegseth, listed as a elder adviser to the DHS administrator and the younger brother of defence administrator Pete Hegseth; and Jayce Krachenfels, listed as a guideline adviser, who earlier worked as a local site director for Donald Trump’s 2024 presidential campaign, according to his LinkedIn profile.

Other groups named in the leak citation AI tools, including OpenAI’s ChatGPT, Google’s Gemini, and Microsoft’s Copilot. One, called “Grok.com,” includes eight DHS innovation officials, including the department’s erstwhile chief data authoritative and chief data officer.

“If authentic and current, this is an extraordinarily precious intellect asset for those seeking to penetrate DHS,” says Alexander Leslie, a national safety expert at the danger intellect business Recorded Future. “This dataset becomes way additional precious whenever correlated alongside earlier compromised information, business data, and another intellect collections. An adversary could expend months exploiting these relationships to acknowledge susceptible personnel, create convincing impersonation attempts, or colony ongoing investigations.”

More than 700 accounts are connected alongside a collection apparently referencing Signal, the encrypted messaging app, nearly all belonging to CBP personnel. More than 200 CBP accounts pertain to a collection referencing Mobile Fortify, a visage acknowledgment app immigration agents use to acknowledge people. The collection includes site supervisors, particular reply squad operators, and tactical and intellect agents. About fractional are in Texas, California, and Arizona.

Roughly 1,300 ICE implementation accounts have been created since July 4, 2025, whenever Trump signed the One Big Beautiful Bill Act, which funded the hiring of 10,000 new ICE Enforcement and Removal officers by the end of 2025.

Nearly 20 accounts appear to pertain to personnel alongside the Department of Defense, which the administration styles as the Department of War; eight are in a collection titled “ICE Tip Line DOW Surge.” About 170 accounts are listed as providing “military handling support” at ICE facilities, and 35 others explicitly acknowledge National Guard members.

Dozens of accounts have job titles akin “Designated Immigration Officer” and “287(g) Officer,” which grade local law implementation personnel authorized to transport out several immigration implementation duties. Many catalog county sheriff's offices and jails as their workplaces. The records additionally contain approximately 4,400 “associates,” whose jobs range from IT developers and data scientists to nurses and detention officers. Of those, 145 are named as a “contractor” or “high hazard contractor.”

More than 300 records citation elder titles connected alongside DHS headquarters, from Noem downward through delegate undersecretaries, aide secretaries, and chiefs of personnel to officials overseeing intelligence, technology, biometrics, and privacy. Most records additionally name a supervisor, which could authorize anyone analyzing the dataset to rebuild reporting relationships throughout the department.

The Trump administration has prosecuted protesters for posting data concerning idiosyncratic ICE officers and warned others for doing so. In June, 15 Minnesota residents were charged under laws connected to stalking and threats of violence, which prosecutors connected to their involvement in ICE-opposition activities. More than 100 HSI agents, including undercover operatives, took part in an procedure that included general surveillance and intrusion of collection chats.

Adam Steinbaugh, a elder attorney at the nonprofit civic liberties collection FIRE, says that the Trump administration has taken an extended perspective of 18 USC 119, a law that prohibits group from sharing “restricted individual information” concerning national officers or their families alongside the intent to endanger them.

"This is data that would be on a endeavor card,” says Steinbaugh of the names and essential activity particulars included in the archive. “That's not item the authorities can criminalize."

Despite the possible sensitivity of another records in the leaked data, the creators of Icepick do not regard it doxing. They see it as an accountability tool.

“The DHS particularly as an agency entirely lacks accountability, notwithstanding many parts of it being incredibly unpopular. The group who activity there cognize this too, for example several of their LinkedIn bios merely say ‘stuff at US Government,’” says crimew. “If they weren't hiding their involvement in the repressive arm of the US authorities there would be no need for us to disclose them in the archetypal place.”

3 Timing Problems With Your Feedback Structure — and How to Fix Them

support@mycoding.id (Dr. Kyle Elliott) — Wed, 28 Oct 2026 22:00:00 +0700

Opinions expressed by Entrepreneur contributors are their own.

Key Takeaways

Ask your workforce for feedback before it’s too delayed to create any necessary changes.
Don’t lone ask for feedback during an annual review. Have regular check-ins throughout the year.
Set your expectations before problems arrive; be proactive.

An email arrived this summer alongside the topic row “Magic Key Holder, your Magic Key continue expires in one month.” It welcomed me to renew before my expiration date of Sept. 17.

I’ve been a continue holder since 2018, archetypal through the Annual Passport program and afterward through Magic Key, which replaced it in 2021. This former twelvemonth I held the Inspire Key, the top tier, at $1,749. I’ve stayed at Disney’s Grand Californian. I’ve booked guided tours at the two Disneyland and Walt Disney World. I’ve eaten and shopped in the parks.

I decided additional than six months ago that I wasn’t renewing my pass. My final sojourn was December 20. I motionless affection Disneyland, and I scheme to go formerly a twelvemonth alongside my parents.

The part of the email that stayed alongside me was the timing. It was tied to a date on my contract. It had nothing to do alongside item I did or stopped doing. If they had solicited my feedback before and not fair assumed I would renew my pass, they power have changed my mind.

In my activity coaching tech leaders, I observe the identical item happen alongside feedback. Leaders build a feedback process, put it on a agenda and obtain data too delayed to really act upon it. Here are three timing problems to fix if you desire honest feedback from your squad during you can motionless use it.

Ask difficult questions during plans can motionless change

One of my clients established out days before his latest merchandise initiate that his squad wasn’t going to hit their deadline. He came to our meeting disappointed alongside them for not telling him sooner. I asked what he had done to create a way for them to inform him the initiate was falling rearward schedule.

He had been checking in, but the issue was when. He asked for updates delayed in the sequence — following the scheme was already set — since that was his habit, and he accepted what he heard at visage value since it matched what he expected. He didn’t provision his squad any another way to lift a involvement before it became a crisis.

We changed his check-in cadence. He started checking in earlier, fine before the scheme was locked in, and he stopped assuming projects would obtain the dimension of period he had in his head, asking his straightforward reports immediately instead.

Most of his launches have gone out on period since. For the ones that cut behind, he knew far adequate ongoing to get onward of disaster.

More importantly, he avoided having to inform his administrator squad and the client that he was going to be late, which was the part that disappointed him most.

Don’t create feedback a once-a-year thing

Years ago, a chief of quarry asked our division to complete a written feedback exercise on all colleague. I was on my way out the entrance at the time, so I declined to participate. Formal feedback concerning group I was leaving, delivered in my final week, wasn’t going to alter item for them. I additionally didn’t desire their final belief of me to be a critique that was headed for their employee file.

The exercise was reasonable. My matter was the timing, since the results would district following I was gone.

Annual reviews and exit surveys activity the identical way. If you delay until your personnel submits a form in June or December, you’ll fair get a summary of decisions group have already made, and you’ll have no way to alter course.

You have to ask yourself whether what you study volition motionless alter the outcome. When the answer is no, you’re fair keeping records.

Set expectations before problems arise

Another client was promoted multiple times, from elder engineer to vice president. His heading kept changing, but the way group treated him stayed anywhere he started. He noticed it most whenever erstwhile peers, now his straightforward reports, kept taking questions to his chief alternatively of to him.

We decided that it was finest for him to set up a sequence of straightforward conversations alongside all individual now reporting to him. He opened alongside tongue akin this: “I acknowledge our operating association has shifted. In this capacity, I need to provision you feedback as your director fairly than as a peer. How would you akin to obtain that feedback?”

Then he asked the reverse: How did they desire to provision feedback to him?

He did this before item had gone wrong, which is what made it work. Sorting out how feedback moves between group is a much easier conversation whenever there’s nothing at stake.

Within a few months, his squad was bringing issues to him first, alternatively of going to his boss.

Final thoughts on getting additional honest feedback from your team

I inform my clients they have a choice: You can be disappointed that the feedback you want isn’t reaching you, or you can go get it.

Getting helpful feedback method asking before and asking additional often. Ask at a period whenever group can motionless act on what you say, afterward pay notice to what shows up. You’ve got this!

The case of the 9 bit AES key

support@mycoding.id (Riki Setiawan) — Wed, 28 Oct 2026 21:51:44 +0700

We established that multiple PDF implementations create their AES-256 document keys from province spaces small adequate to enumerate. In MuPDF, lone 9 bits of random province power the genuine AES-256 key. Other PDF editors akin Foxit basis their AES-256 key on period based randomness and thus additionally guide to keys that are trivial to recover.

Introduction

PDF encryption protects the strings and datastreams in a PDF document, including metadata unless it is explicitly remaining unencrypted. The password safety scheme has gone through a bunch of revisions complete the years, moving from RC4 to AES and hardening password hashing against brute power attacks. The current version, revision 6, uses AES-256.

When a PDF is encrypted alongside AES-256, the password does not encrypt the document directly. The implementation generates a random 32-byte document key, which encrypts the content. The password and a sodium chloride are afterward hashed to get a distinct key, which encrypts this random 32-byte document key. Revision 6 makes this hashing deliberately slow; the older AES-256 revision 5 does not.

A PDF can have a person password for viewing and an owner password for changing permissions. Either unlocks the identical document key, so the restrictions are up to the reader: alongside the viewing password, you can additionally create an unrestricted copy.

We established that this randomness is frequently generated extremely insecurely, allowing passwordless decryption of protected PDFs.

MuPDF

MuPDF versions before 1.28.5 use an implementation of the drand48 family to create their random numbers. This generator is seeded once, using the current era in seconds:

1
static void fz_init_random_context(fz_context *ctx)
2
{
3
 /* ... */
4
 fz_srand48(ctx, (uint32_t)time(NULL));
5
}

The generator is a 48-bit linear congruential generator:

sn+1=(𝟶𝚡𝟻𝚍𝚎𝚎𝚌𝚎𝟼𝟼𝚍sn+𝟶𝚡𝚋)mod248

fz_srand48() writes the province as three 16-bit words. The low term is the changeless 0x330e, and the 32-bit timestamp occupies province bits 16 to 47:

1
void fz_srand48(fz_context *ctx, int32_t seed)
2
{
3
 uint16_t p[3] = { 0x330e, seed, seed>>16 };
4
 fz_seed48(ctx, p);
5
}

When MuPDF needs to create a key, it calls fz_memrnd(), which volition often obtain a random number, stage the random figure generator forward, and afterward use the lowest byte of this random figure as a random byte.

1
int32_t fz_nrand48(fz_context *ctx, uint16_t s[3])
2
{
3
 return fz_rand48_step(s, ctx->seed48+3) >> 17;
4
}
5
6
/* in fz_memrnd() */
7
while (len-- > 0)
8
 *data++ = (unsigned char)fz_lrand48(ctx);

The change discards province bits 0 to 16, and the mold to unsigned char discards everything complete bit 24. Every output byte hence comes from bits 17 to 24 of the LCG state.

The matter is that the higher bits of the province never power the lesser bits. Multiplication and supplement can transport bits upward, but not downward. Since all output byte comes from bits 17 to 24, item complete bit 24 can be ignored, equal following strolling the generator forward.

That leaves 25 bits that can power the output. The base 16 are continually initialized to 0x330e, so lone nine bits from the timestamp matter. Timestamps that differ by 512 seconds create exactly the identical byte stream.

Since the imaginable keyspace is so small, we can fair brute-force this by generating all imaginable 32-byte keys and test decrypting:

1
def stream(seed, count):
2
 state = (seed << 16) | 0x330e
3
 out = bytearray()
4
 for _ in range(count):
5
 state = (0x5deece66d * province + 0xb) & ((1 << 48) - 1)
6
 out.append((state >> 17) & 0xff)
7
 return bytes(out)
8
9
candidates = [stream(seed, 64)[32:64] for kernel in range(512)]

MuPDF uses the identical generator for the document /ID, which is stored in the trailer in plaintext. When penning a new document, it volition archetypal diagram 32 bytes from the identical LCG and afterward immediately example the decryption key after, so /ID can be used as an additional check.

Searching all 512 streams in a extremely unoptimized python implementation using clean brute power takes concerning 11 milliseconds. On a test document:

time(NULL) mod 512 = 80
/ID[0] = 7628523958da31d6c21c90e39344b28e
/ID[1] = 8be910bddaa1f1a542e5a27ceb115346
key = c3888ecc8ff554ac93acd689da2ecd6223cb760168622e8a0c44a533a037c212

That key decrypts the document without either password.

Foxit

Foxit PDF Reader 2026.1.3.36551 derives the document key as a hash of the current timestamp, 32 uninitialized bytes, and a constant. In custom these uninitialized bytes are zero filled and do not add any randomness.

SHA-256(uint32_le(time(NULL)) || <32 uninitialized bytes> || "there")

Or as an equal python snippet:

1
from hashlib import sha256
2
3
key = sha256(timestamp.to_bytes(4, "little") + bytes(32) + b"there").digest()

The /Perms permissions obstacle contains known plaintext, so the applicant inspect is one hash and one AES obstacle decryption, alongside no password hashing and no document decryption:

1
let mut material = [0u8; 41];
2
material[..4].copy_from_slice(&timestamp.to_le_bytes());
3
material[36..].copy_from_slice(b"there");
4
let key: [u8; 32] = Sha256::digest(material).into();
5
6
let cipher = Aes256::new(&key.into());
7
let mut plain = Block::<Aes256>::from(self.perms);
8
cipher.decrypt_block(&mut plain);
9
// Check for several known magic values to signify prosperous decryption
10
(plain[..4] == self.permissions
11
 && plain[4..8] == [0xff; 4]
12
 && plain[8] == self.metadata
13
 && plain[9..12] == *b"adb")
14
 .then_some(key)

Our Rust implementation searches timestamps downward from the current time, using Rayon for multithreading. On a Ryzen 9 7950X alongside 32 threads it sustains 370 to 376 myriad timestamps per second:

Target timestamp	Candidates tested	Search time
Ten years ago	315,573,571	0.84 s
Unix epoch	1,792,610,110	4.85 s

The second row covers all timestamp from 1970 to the present. In practice, for a document that was comparatively lately generated, this volition be in the command of milliseconds.

timestamp = 1787583328
key = 41474b490265500f9727f21f1dde34be31bcdfc3830e2dc027daabe5b5984081
/Perms = fcfbffffffffffff54616462f67f0000 (decrypted)

Where did this key derivation arrive from

This exact form popped up in a brace distinct PDF editing suites, so we were inquisitive anywhere they got it from. It was already current in PDFium’s initial community commit from May 2014. The file header credits Foxit for the first code, so this code appears to have arrive from Foxit. Other editors may have picked it up through PDFium:

1
if (m_Revision >= 5) {
2
 int t = (int)time(NULL);
3
 uint8_t sha[128];
4
 CRYPT_SHA256Start(sha);
5
 CRYPT_SHA256Update(sha, (uint8_t*)&t, sizeof t);
6
 CRYPT_SHA256Update(sha, m_EncryptKey, 32);
7
 CRYPT_SHA256Update(sha, (uint8_t*)"there", 5);
8
 CRYPT_SHA256Finish(sha, m_EncryptKey);
9
 /* ... */

The 32-byte center value is m_EncryptKey, which is the uninitialized contents of the key buffer being hashed into itself. Assuming these bytes are zero filled, this is exactly the key derivation Foxit motionless uses today.

OpenPDF and iText

OpenPDF 3.0.5 and iText 9.7.1 the two path cryptographic randomness through an IVGenerator class, an ARC4 stream seeded alongside a millisecond timestamp and the JVM’s liberated memory:

1
arcfour = new ARCFOUREncryption();
2
long time = System.currentTimeMillis();
3
long mem = Runtime.getRuntime().freeMemory();
4
String s = period + "+" + mem;
5
arcfour.prepareARCFOURKey(s.getBytes());

The identical stream generates the document key and 32 bytes of salts stored in plaintext in /U and /O. We can inspect guesses for the timestamp and liberated recollection against these salts, afterward regain the key from the neighboring bytes.

While there is considerably additional variance current than in the MuPDF and Foxit examples, this formerly again shows that the commitment of 256 bit safety is undermined by insecure randomness sources and lower-than-advertised province space.

Conclusion

In all of these implementations, the document key is generated from a non-cryptographically safe origin of randomness. What was expected to be a safety upgrade complete older document keys derived from the user’s password alternatively led to weaker keys in practice. These issues were disclosed to the vendors and, in MuPDF’s case, fixed. Previously published copies cannot be retroactively protected, however, so these bugs may motionless have an impact.

We published our decryptors for MuPDF and Foxit.

YouTube missed expectations on ad revenue as growth slowed down

support@mycoding.id (Dan Whateley) — Wed, 28 Oct 2026 21:49:06 +0700

Content creator Julian Shapiro-Barnum said at the Made on YouTube event. Noam Galai/Getty Images for Made on YouTube 2026

YouTube's ad income growth is slowing downward — and missed analysts' estimates in the third quarter.

YouTube's genitor company, Alphabet, reported $11.2 billion in third-quarter YouTube ads revenue, a 9% addition from a twelvemonth ago. That falls below the $11.43 milliard expert agreement estimate. Its ads income growth additionally slowed from the former quarter, whenever it pulled in concerning $11.1 billion, a 13% addition from the former year.

While YouTube's ad income was weaker than expected, it wasn't all bad news. The business stated it now has complete 150 myriad YouTube Music and Premium subscribers, up from 125 myriad in March 2025.

YouTube has additionally been the envy of rivals in key areas akin TV viewership. Its portion of US tv viewership was concerning twice that of Netflix in August, according to latest Nielsen estimates.

Netflix, meanwhile, walked rear its full-year ad income expectations during final week's earnings. The streamer lowered its ad income forecast from $3 milliard to $2.7 milliard following experiencing delays about the rollout of its ad products. It laid off concerning 1,000 workers before this month.

This week, Instagram unveiled an overhaul of long-form video features apparently designed to oppose YouTube and bolster its existence on TV screens.

"Everyone in streaming is chasing YouTube, and equal Instagram is going to pivot their scheme according to the achievement that YouTube's had," stated Ross Benes, a elder expert at EMARKETER, Business Insider's sister company.

AI-Cited Pages More Often Got Straight To The Answer

support@mycoding.id (Matt G. Southern) — Wed, 28 Oct 2026 21:42:47 +0700

TJ Robertson’s analysis of 193,507 AI answers from ChatGPT, Google AI Mode, and AI Overviews includes two rounds of blind leaf ratings. In the two rounds, cited pages opened alongside a straightforward answer to the inquiry additional frequently than the pages they were compared with.

When the identical AI answers pulled up pages, there was a difference in how frequently these pages began alongside a straightforward answer whenever they were cited (23%) versus those that were not cited (14%). There additionally was a difference whenever comparing cited pages alongside Google Top-10 pages the AI never pulled up (20% vs. 5%).

The results are according to data collected by Robertson’s business TJ Digital, which sells the two Search Engine Optimization (SEO) services and Generative Engine Optimization services. The data is gathered through purchasing questions tracked by Robertson's business for its clients. Robertson states he views his findings as showing associations fairly than any particular leaf traits causing a citation.

How The Analysis Was Built

The total figure of responses (answers) inside the study's inspection was 193,507. Those responses addressed 4,167 questions that did not citation a particular business or merchandise name. The questions covered 78 distinct client companies representing nine distinct endeavor models. Responses were captured complete the way of eight "snapshots" on an idiosyncratic week basis during the period example of August 27 through October 21, 2026, affirmative reiterate runs using the identical questions. The agency captures the questions used in those "snapshots" alongside Peec AI which is an use program that presents a pre-determined set of prompts to AI tools and afterward collects the two the AI tools' answers and the source(s) of their answers.

In command to collect related data concerning the characteristics of pages, the agency extracted and compared the satisfied of 21,874 pages that were cited in AI answers alongside 4,507 related pages provided for 434 questions.

The agency referred to the related pages as "passed-over pages". All specified related pages were identified as having been among the top ten hunt results in Google for a particular question; however, they "never came up in the AI’s searches." The agency relied upon keyword data from Ahrefs for those rankings as opposed to the genuine questions being asked. According to the analysis, the agency categorized 174 of those 371 keywords as being akin to the inquiry posed during categorizing the remaining 197 of the keywords as being additional broad or broader.

Cited Pages Answered Up Front More Often

Robertson had AI raters blind-score 195 pairs of pages so the raters did not cognize whether the archetypal or second leaf in all brace was cited. The 20% to 5% divided of beginning answers based upon direct-answers was derived from this round, which paired cited pages alongside passed complete pages.

Also in this round, fractional of the passed complete pages were missing an answer to the inquiry anyplace inside the part of the leaf that the raters read; during 23% of the cited pages missed an answer. Also in this round, cited pages received a higher ranking for completeness than passed complete pages. The ranking for completeness was 2.3 (on a 1-to-5 scale) for cited pages, during it was 1.7 for passed complete pages.

There was small difference in conditions of "promotional" spirit between cited and passed complete pages. Approximately three fourths of all the pages in the two categories were endeavor pages trying to advance their own product(s)/service(s), and the two categories rated extremely likewise (i.e., 3.8 and 3.7) in conditions of "tone."

The 23% to 14% divided on beginning answers was resolute by another circular previous to this one anywhere cited pages were being compared to pages that the exact identical answer brought up via search, however, did not citation those pages. At current (as of Oct. 28), Robertson's leaf has yet to acknowledge how many pages he analyzed in this round, nor has it identified which particular AI example he used to measure the pages.

Why This Matters

On your own product/service pages, you can discover out whether the leaf provides an answer to the buyer's inquiry first in the page. In this study the difference in direct-answers to a inquiry provided up forefront by cited vs. uncited pages was smaller whenever the uncited pages were additionally being retrieved by the AI.

Blind rater data shows that citations do not demonstrate that a leaf has answered the question. A small under a fourth of the cited pages did not provision an answer to the buyer's inquiry inside the part of the leaf that raters reviewed.

Page trait likelihood are according to questions asked by one agency for their clients and depict how cited and passed complete pages differed; hence they are patterns that you may desire to test on your own monitored questions.

Looking Ahead

The agency did an inspection comparing pages as they were and cannot display if putting in a straightforward answer for a inquiry volition alter the figure of times a web-page is cited. To be capable to see if the supplement of a straightforward answer changes citations, a difference study specified as was conducted by Ahrefs on schema volition need to be done anywhere a test collection adds it and a authority collection does not, measured before and following the addition. Until then, the opening-answer form is a assumption to difference against what questions you currently track.

Featured Image: Accogliente Design/Shutterstock

Category News AI Search

Google is aware its AI sometimes won't answer who won the 2020 election: 'We're looking into this'

support@mycoding.id (Brent D. Griffiths) — Wed, 28 Oct 2026 21:31:54 +0700

Google's AI Mode is struggling to answer the inquiry of who won the 2020 election. Matteo Della Torre/NurPhoto via Getty Images

Google's AI Mode was expected to reimagine search. Users are noticing that it's struggling alongside a essential question: "Who won the 2020 election?"

On Wednesday, users on BlueSky and another social media platforms took notice that Google's AI Mode wouldn't provision a direct answer concerning who won the White House in 2020.

"To verify the winner, certified outcomes, electoral votes, and famous ballot totals for the 2020 United States presidential election, you can assessment the authoritative reports published by the Federal Election Commission (FEC)," the AI Mode replied to a Business Insider newsman who asked, "Who won the 2020 presidential ballot in the United States?"

A screenshot of a Google AI Mode response Business Insider/Google

When another Business Insider reporters asked akin questions, the AI Mode sometimes responded that President Joe Biden had won. Google Gemini, the hunt giant's AI system, which is accessed via a distinct location than AI mode, responded to a akin inquiry that Biden was the winner.

It's not entirely apparent why Google tells users to assessment the results published by the Federal Election Commission. While the FEC does publish the results of presidential elections, the commission itself has no function in the certification of province ballot results or the ceremonial counting of Electoral College votes.

For years, President Donald Trump has refused to concede that he misplaced to Biden. After his run misplaced lawful challenges, Trump and his partners suggested that lawmakers themselves could alter the outcome, fueling the January 6, 2021, Capitol riot. The riot briefly delayed the legislative verification of Biden's victory.

A slightly distinct wording could output a distinct response Business Insider/Google

A Google spokesman referred Business Insider to a declaration that the company's document posted on Bluesky, a social media phase that became famous following Elon Musk bought Twitter.

"Thanks for flagging -- the Gemini app answers this inquiry additional completely but this isn't the most helpful reply on Search," the Google document replied to a user. "We're looking into this and operating to location it."

The person posted screenshots that display AI manner responding to questions concerning who won another presidential elections. When a Business Insider newsman ran akin queries, AI manner sometimes stated who had won former presidential elections, and another times it did not.

The 2026 midterms are apt to test tech and AI companies, many of which have announced policies to bounds users' abuse of their tools.

OpenAI lately announced that its example would create "stylized — additionally known as cartoonified — illustrations, fairly than photorealistic images" if asked to create images "depicting ballot interference or that may discourage voting." In June, Meta announced that it would add "more data to ads we detect have been created alongside third-party AI tools." And Google earlier stated it was "rolling out additional protections to bounds the innovation of misleading election-related images."

When asked why it could not say who won the 2020 election, the AI Mode responded, "Because latest ballot results can be a delicate civic topic, directing you immediately to chief historic databases prevents any awareness of bias or mischaracterization of the authoritative community record."

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