MC Project

Google Adopts New AI Training Control

support@mycoding.id (Barry@Rustybrick.com (Barry Schwartz)) — Fri, 30 Oct 2026 17:50:00 +0700

Google additionally announced, like Bing, that it plans to voluntarily clasp a recommendation under deliberation at IETF, the earth net standard-setting body, that would create a simple, streamlined AI training authority for web publishers and creators.

Google said, "This volition assistance websites province their AI training preferences throughout multiple AI providers in a sole stage and is according to activity from the AIPREF operating collection at the Internet Engineering Task Force (IETF)."

This new, work-in-progress authority volition provision websites and publishers a new way to communicate their AI training preferences throughout multiple AI providers. This lets them invoke their preferences in a sole stage in robots.txt, alternatively of listing all one individually.

Google plans to execute this in 2027.

Google told me "moving onward alongside this undertaking alongside equal AI providers as part of a shared dedication to foster an open, creator-first web ecosystem, and following feedback from publishers, civic community and regulators calling for an easier way for websites to province their AI training preferences."

Instead of managing distinct instructions for all AI developer, website owners volition be capable to use a shared 'policy token' inside robots.txt to set broad preferences throughout participating AI providers.

Keep in mind, Google additionally has the Search Console opt out method for Search generative AI.

John Mueller, Google Search Advocate, wrote:

When a website uses this guideline token to opt out of training in its robots.txt document (and Google-Extended is not explicitly specified), Google plans to construe that as if the publishing company had disallowed Google-Extended. Other AI providers can grip it similarly, making it uncomplicated for website owners to opt out throughout all providers, or to choice and choose.
Existing company-specific controls volition continue to function alongside this new shared signal. So website owners can effortlessly province a broad choice using the industry signal, during additionally tailoring their instructions to idiosyncratic AI developers akin Google through controls specified as Google-Extended. Websites that specifically authorize Google-Extended are eligible to appear in responses and obtain clicks via grounding in Gemini Apps.
The new scheme brings website owners the advantage of the AI training definition developed at the IETF during multistakeholder discussions continue on the remainder of the AIPREF vocabulary. As additional industry players clasp this mechanism, it gives website owners first and expanding admission to the penchant signal.
This outline recommendation reflects feedback from publishers, civic community groups, regulators and another stakeholders that have called for industry-wide controls on AI training. Support for this recommendation throughout important AI providers volition allow a forthcoming norm that is cross-industry, robust, and durable. This recommendation is accordant alongside the EU Code of Practice for General Purpose AI (GPAI) Model Providers under the EU AI Act that recognizes robots.txt as a chief method for web publishers to province machine-readable preferences. We'll continue to activity alongside these stakeholders to refine and standardize this through the IETF operating group.
We aim to assistance this new authority alongside alongside another AI providers in 2027, and volition provision updates on our progress.

Forum conversation at X.

A Working Nintendo in ~1GB of Qwen Weights

support@mycoding.id (Putri Silvia) — Fri, 30 Oct 2026 17:40:22 +0700

An NES CPU compiled into the weights of a inventory Qwen3.5 model.

The NES's 6502 CPU (the center of its 2A03 chip), its 2 KB of activity RAM, and a cartridge's program ROM run inner a norm Qwen3_5ForCausalLM checkpoint. Nobody trained these weights; a compiler computed all one. When you perform a game, the example predicts the CPU's implementation log one token at a time. A small presenter program plays the remainder of the console about it: it draws the picture, says the controller, and fires the vblank interrupt.

nesformer builds on Qwenputer by Divyansh Agrawal, which compiled a CHIP-8 and afterward a RISC-V CPU into Qwen3.5-4B. It reuses Qwenputer's compiler and its central trick: the model's Gated DeltaNet province is the machine's memory.

Every CPU token in these runs came from the model. For the bundled test games, all example also matches a accepted 6502 emulator's output exactly (see How it was checked).

Unzip nesformer.zip and nesformer-weights.zip into the identical folder. The weights go next to the nesformer/ package, not inner it:

nesformer/ <- run commands from here ├── nesformer/ <- the Python package ├── chipformer/ <- Qwenputer's compiler ├── roms/ <- test ROMs (put your own current too) ├── examples/ <- example GIFs and example sheets ├── tests/ ├── LICENSE ├── LICENSE.chipformer ├── README.md ├── pyproject.toml └── weights/ <- from nesformer-weights.zip ├── config.json ├── generation_config.json ├── model.safetensors ├── nesformer.json └── SHA256SUMS

The CLI looks for weights/ beside the nesformer/ package. To keep the weights elsewhere, pass --weights /path/to/weights to run, inspect or trace, or provision the way to info.

To verify the weights unzipped correctly, run shasum -a 256 -c weights/SHA256SUMS from the top folder.

You need Python 3.11 or newer.

python3 -m venv .venv source .venv/bin/activate # Windows: .venv\Scripts\activate pip instal numpy scipy numba pillow

python -m nesformer run roms/thwaite.nes --frames 600 --show \ --buttons "start@90-95+200-205,a@230-233+250-253+270-273+290-293+310-313+330-333+350-353+370-373+390-393+410-413+430-433+450-453+470-473+490-493+510-513+530-533+550-553+570-573+590-593"

--show draws all example in your terminal as the example generates it. When the run ends, the CLI saves an animated GIF named following the ROM (here thwaite.gif) in the current folder.

Expect it to be slow. The archetypal run spends concerning 20 seconds compiling the motor alongside numba. After that, a example takes 1–6 seconds, so 600 frames (10 seconds of NES time) obtain around 25 minutes.

Point run at any .nes document that uses the NROM commission (iNES mapper 0), specified as Super Mario Bros., Donkey Kong or Excitebike. You provision the ROM; nesformer lone ships the three freely licensed test ROMs in roms/.

python -m nesformer run roms/smb.nes --frames 600 --show \ --buttons "start@60-65,right@200-600,a@250-265+300-315+360-375+420-435+480-495+540-555"

That manuscript starts the game, afterward walks Mario correct and jumps concerning formerly a second. The CLI loads the ROM into the model's province at startup, so the identical weights run any NROM equivalent without a rebuild. Games on another boards halt alongside a message: see Limitations.

--buttons takes a comma-separated catalog of entries. Each admission names one or additional buttons joined by +, afterward @, afterward one or additional example ranges joined by +:

start@60-65 media Start during frames 60 to 65 right@200-600 clasp Right from example 200 to example 600 a@250-265+300-315 media A twice right+b@200-600 clasp Right and B together (run, in Super Mario Bros.)

The buttons are a, b, select, start, up, down, remaining and right. Frames figure from power-on at 60 per second, so example 600 is 10 seconds in. Games disregard input on screens where you can't move, so holding a clasp a small first does no harm. In Super Mario Bros., a longer A media makes a higher jump.

Command	What it does
python -m nesformer run ROM	Play a ROM on the weights and preserve a GIF
python -m nesformer inspect ROM	Run the weights and the citation CPU flank by side; halt at the archetypal difference
python -m nesformer trace ROM	Print the model's token stream (default 40 tokens)
python -m nesformer build	Compile the circuit and compose weights/ (about 10 seconds)
python -m nesformer info	Describe the checkpoint

Options for run:

Option	Default	Meaning
--frames N	120	Stop following N frames
--buttons SCRIPT	none	Controller input (see above)
--show	off	Draw frames in the terminal (needs 24-bit color, e.g. iTerm2 or Windows Terminal)
--gif PATH	ROM name	Where to preserve the animated GIF
--png DIR	off	Save all kept example as a PNG in DIR. With --png alone, no GIF is saved. Add --gif to get both.
--every N	1	Keep all N-th frame
--scale N	2	Enlarge saved frames N times
--engine	fast	fast (numba), numpy, or hf (stock transformers; needs torch, ~10 tokens/s)
--no-skip	off	Run all repeat of idle delay loops (slower; identical frames)
--max-tokens N	none	Stop following N tokens
--trace FILE	none	Save the token ids

run, inspect and trace all obtain --weights, --engine, --buttons and --no-skip. check --tokens N sets how far to difference (default 50,000). trace --tokens N sets how many tokens to imprint (default 40). build --out DIR writes the checkpoint location another than weights/.

What's in the weights, and what isn't

In the example (weights + DeltaNet state)	In the presenter (nesformer/host.py)
The 6502 core: all 151 authoritative opcodes, all addressing mode, flags, stack, BRK and NMI entry	The PPU: a scanline renderer and the palette
2 KB of activity RAM	Controllers; APU registers (written, alternatively ignored)
32 KB of PRG-ROM, stored twice: one copy for education fetch, one for data reads	NMI timing at vblank, injected as an NMI token
OAM DMA says (the 256 bytes appear as DM tokens)	Answers to I/O reads, injected as IN tokens

This divided follows Qwenputer's CHIP-8 build, whose presenter injects timer ticks and draws the display from the trace. The presenter never sees the CPU's registers or RAM apart from through the trace.

The recollection trick plant akin this. Each DeltaNet caput keeps a 128 × 128 province matrix that the delta regulation updates at all token. With the entrance held open and a one-hot key, an update overwrites exactly one row of that matrix, and a one-hot query says it back. So all row is a memory cell, and the cartridge, RAM and registers all live in rows.

weights/ is an average Hugging Face folder. It loads with Qwen3_5ForCausalLM.from_pretrained and needs no tradition code.


Architecture	Qwen3_5ForCausalLM, alongside Qwen3.5-4B's DeltaNet caput shapes (16 key heads, 32 value heads, dim 128) and MLP width (9,216)
Layers	7 Gated DeltaNet layers (the circuit), affirmative 1 all-zero notice tier that Hugging Face's cache needs
Hidden size	768
Vocabulary	263,808 tokens
Parameters	466.6M in bf16 (933 MB), of which 9.3M are nonzero, so the weights zip to 3.3 MB

nesformer.json records which tier and caput holds all part of the machine. A run writes the cartridge, registers and RAM into those DeltaNet states, afterward decodes greedily.

Layer	Attention (state)	MLP
1	PC anchor; education counters; A, X, Y, SP; flags N V Z C I D; pointer latches; NMI flag	counter thermometers; SP ± 1; LO + Y
2	—	PC = anchor + bytes executed since; PC + 1, PC + 2
3	PRG fetch: opcode and two operand bytes at the PC	opcode decode; operand bits; indexed sums; branch test and target
4	—	effective address, by addressing manner and document stage; the byte a shove stores
5	RAM and PRG data says at the productive address	operand; ADC/SBC adder, compares, BIT; location decode
6	—	result byte, carry, overflow, flags, jump targets
7	—	the next token

Each education becomes a record, and the record's final token commits it. As in Qwenputer's RISC-V core, the PC is implied fairly than written: all final token carries its instruction's length, three DeltaNet counters count the instructions of all dimension since the final jump, and the PC is the jump mark affirmative that offset. Excerpts from Full Game:

SEI P(000100 px0 L1) LDX #$40 X($40 c0 v0 px0 L2) STX $4017 IOW($4017=$40 L3) TXS S($FF L1) BIT $2002 IOR($2002) IN($00) P(000110 px0 L3) <- the presenter injects IN BPL $8017 J($8017) JSR $8279 PSH($FE) PSH($FD) J($8279) <- the come back location is pushed in-circuit RTS PUL($FC) LO($7B) PUL($FD) J($827C) STA ($72),Y LO($08) HI($03) ST($00 a7=0 L2) <- pointer bytes latched, afterward the store STA $4014 IOW($4014=$02 L0) DM(0:$FF) … DM(255:$00) NT(L3) <- OAM DMA

Most instructions obtain a sole token; genuine equivalent code averages 1.1–1.3 tokens per instruction. nesformer/spec.py documents all token family.

The citation CPU (nesformer/cpu.py) matches nestest's aureate log for 3,348 instructions, and the py65 emulator on 5.7 myriad instructions of equivalent code.
The exact circuit, run in Qwenputer's evaluator alongside its bf16 exactness checks, predicts every citation token: all of nestest affirmative 283,610 positions of two games' footwear sequences.
The checkpoint in inventory transformers (bf16, CPU) predicts 2,651 positions of nestest and Full Game alongside no mismatches.

The weights, free-running, create traces identical to the citation CPU's:

Run	Tokens	Frames	NES time	Result
nestest (official opcodes)	4,586	—	—	identical, ending in the expected HALT
Thwaite, check	700,000	271	4.5 s	identical trace and frames
Thwaite, run	1,916,527	600	10.0 s	all 300 saved frames match
Full Game, run	2,645,885	420	7.0 s	all 210 saved frames match

The idle-loop skip changes nothing visible: frames and I/O writes, sequence timestamps included, equivalent a run without it.

The default motor computes Qwen3.5's onward continue from model.safetensors, compiled alongside numba and skipping the all-zero blocks. It ran at concerning 1,650 tokens/s on one CPU center of the machine it was built on. The plain numpy motor does concerning 210, and inventory transformers concerning 10. A real NES would need concerning 700,000 tokens per second.

Games expend most of all example in a iteration that waits for vblank. When the presenter sees a iteration body repeat exactly, alongside no RAM or I/O writes, it advances the clock to fair before the next PPU event, and the remaining iterations motionless run. That cuts the token figure by 2.6× to 4.2×. Overall, nesformer runs 150–290× slower than the genuine console.

NROM cartridges lone (iNES mapper 0). The CPU can location lone 32 KB of program ROM at a time. Bigger games transport a bank-switching part (a mapper, specified as MMC1 or MMC3) that swaps which part of the ROM the CPU sees. nesformer's ROM says happen inner the model, from a fixed 32 KB table, so it can't prosecute a financial institution toggle yet. Supporting a mapper method storing the whole ROM in the state, keeping the financial institution registers there too, and adding one phase that turns each CPU location into a ROM address.
Official opcodes only. An unofficial opcode emits HALT.
Code must run from the cartridge ROM. A jump into RAM emits HALT.
No IRQs (APU example IRQ, DMC). BRK and NMI work.
Read-modify-write instructions on I/O registers don't create an I/O write, and $4020–$7FFF reads as 0 (no PRG-RAM).
The PPU and APU aren't in the weights. The PPU renders one scanline at a time, so mid-scanline effects aren't reproduced. Sprite-0 hit and sprite overflow are approximate, and there's no sound.

pip instal pytest py65 python -m pytest -q tests

The tests obtain a few minutes. They inspect the citation CPU against nestest's log, the circuit against the reference, the weights free-running against the reference, and the idle-loop skip.

Running the checkpoint in inventory transformers

pip instal "torch>=2.6" "transformers>=5.22" python -m nesformer run roms/thwaite.nes --frames 3 --engine hf

nesformer/hfcheck.py shows the entire procedure: burden the checkpoint, decode one padding token, write the machine's province into the cache's DeltaNet states, afterward nourish tokens one at a time.

Path	Contents
nesformer/spec.py	token families and records
nesformer/cpu.py	the citation 6502 that writes the trace
nesformer/host.py	everything about the CPU: PPU, controllers, NMI timing, sequence counting, idle skip
nesformer/core.py	the circuit and the province snapshot
nesformer/weights.py	the emitter that turns the circuit into a Qwen3_5ForCausalLM checkpoint
nesformer/engine.py, fastengine.py	run the weights (numpy / numba)
nesformer/hfcheck.py	run the weights in inventory transformers
nesformer/run.py, check.py, cli.py, __main__.py	drivers, the teacher-forced check, the CLI
chipformer/	Qwenputer's q35 compiler (q35/ emitter and primitives, dsl/ graph)
weights/	the compiled checkpoint and its SHA-256 checksum
roms/	test ROMs; roms/SOURCES.md lists their authors and licenses
examples/	GIFs and example sheets from the runs; demo.gif is the Super Mario Bros. run shown at the top
tests/test_nesformer.py	the test suite

Qwenputer and its chipformer compiler: MIT, © 2026 Divyansh Agrawal (LICENSE.chipformer). That licence additionally covers the code adapted from Qwenputer in nesformer/core.py and nesformer/weights.py. Its final paragraph refers to Qwenputer's CHIP-8 ROMs, which this repository does not include.
Test ROMs: nestest by Kevin Horton; Full Game by Doug Fraker (MIT); Thwaite by Damian Yerrick (GPL-3.0, origin at pinobatch/thwaite-nes).

nesformer is released under the MIT License (see LICENSE). The ROMs in roms/ keep their own licenses, listed in roms/SOURCES.md.

Discord To Put Public Chats On Pages Search Engines Can Show

support@mycoding.id (Matt G. Southern) — Fri, 30 Oct 2026 17:38:30 +0700

Discord announced that all one of its most community communities volition have a web leaf starting Nov. 16, and those pages may display AI-written summaries of their community conversations. From mid-December, several members’ messages may additionally display up on those pages and in Google and another hunt engines.

The notice covers what Discord calls Discoverable Servers, which it says figure additional than 63,000. They’re community communities that anyone can associate without an invite. To qualify, a server needs at smallest 1,000 members, have to be at smallest eight weeks old and must encounter Discord’s action and safety requirements. Summaries and messages are the two on by default, and admins choose which community channels obtain part.

Admins have until Nov. 16 to alter these new conduit settings before summaries can commencement showing up.

Members are allowed to opt out of having their posts display on community pages (in several regions, this is the default).

What Happens Starting Nov. 16 & What Follows In December

On Nov. 16, all Discoverable Servers volition have a Server Web Page. Discoverable Servers have already had the capability to create an optional server web page; others which don’t currently do so volition be assigned a default leaf based upon their current server profile. Discord’s help page says anyone can perspective one, and hunt engines akin Google can display it.

Those pages may additionally transport Channel Summaries, which Discord’s admin assistance page says it creates using AI from latest discussions in community channels. The identical leaf says the summaries “may not continually be accurate.” They shield conversations from Nov. 16 onward and don’t display usernames.

From mid-December, Discord says several messages from community channels may appear on server pages and in web search, in members’ own words and without usernames or avatars. The rollout is gradual, and it may be a few weeks before the archetypal messages appear. Messages sent before mid-December aren’t included.

Messages in threads and forum posts are included whenever the genitor conduit is community and participating. Private threads and personal forums are never included, despite of the genitor channel’s settings. For now, messages appear as content only.

Who Controls What

Server settings contain switches and lists for administrators to oversee Channel Messages and Channel Summaries under Community > Web Presence. Each of these items has their own distinctive toggle and conduit listing. However, personal channels (including those restricted to certain roles) volition continually be omitted.

Admins may disable the community’s discoverability; this act volition revert the community rear to a normal Community Server. As lengthy as a server is discoverable, its Server Web Page volition remain available. In command to eliminate admission to this page, an director volition need to rotate off the discoverability option.

According to Discord’s member assistance page, members volition discover one environment located at User Settings > Data & Privacy that controls all Discoverable Servers a person is a part of and allows users to set whether they desire to authorize their messages to appear on the web. This environment volition be enabled by default for users in most regions. For users in the European Union/European Economic Area (EU/EEA), United Kingdom, Canada, Brazil, Australia and South Korea, this characteristic volition be impaired by default. All adolescent document holders volition be excluded from using this feature. Additionally, this characteristic lone applies to messages. Any summaries volition remain accessible and volition continue to be displayed unless admins rotate them off.

Additionally, turning off this characteristic volition lone power new messages posted following specified actions obtain place. Previous messages can motionless be viewable until they are deleted. Upon deletion of a message, the communication volition no longer be accessible inside the use nor on the Server Web Page; however, Discord says it cannot justify that hunt engines volition not keep cached or indexed versions of the deleted message.

How The Pages Are Set Up For Search

Discord’s robots.txt file shows the sitemaps for its server pages and its notice pages anywhere posts from pilots have appeared.
The aviator evaluation of Channel Messages has been operating on multiple gaming servers (including NBA 2K, Rust & Dead by Daylight) alongside admins and moderators as writers of all sole communication posted.

Dead by Daylight’s server page, accessed October 29th, contains ProfilePage organized data. This is the identical overview markup Google rolled out in November 2023, in supplement to the conversation forum markup I reported concerning at the time. Admins are encouraged to “accurately and specifically” depict their servers, per the Server Web Pages assistance page, so searchers can discover them.

As of Oct. 29, there are no rules in robots.txt referencing AI crawlers; nevertheless the broad restrictions do not shield the paths to the server and notice pages.

Discord’s FAQ answer on whether it sells messages to AI companies reads:

No. Nothing has changed. We are making Discord satisfied easier to discover if admins and users choose to create their satisfied accessible on the web.

As of Oct. 29, all three assistance pages listed above, as fine as the notice referenced above, do not citation AI crawlers or example training.

Why This Matters

Any Discoverable Server you run volition have a community leaf starting Nov. 16, whether or not you create one yourself. The channels you depart enabled in Web Presence decide which conversations Discord’s AI summarizes there, so it’s a fine idea to assessment them before that date.

Discord’s own examples of answers that can display up in web hunt are equivalent builds, strategies and chief guides. In August, I reported that Ahrefs’ data put community Facebook Groups second to Reddit among sites in Google’s Discussions and forums results. Some server pages can already display up in search, but the associate answers Discord describes don’t commencement rolling out until mid-December.

Looking Ahead

Default server pages and summaries can go live on Nov. 16, alongside Channel Messages commencement to rotate out in mid-December. Once associate messages are available, you can inspect whether those pages contain conversation forum markup, fair as server pages contain overview markup.

Featured Image: Samuel Boivin/Shutterstock

Category News Social Media

Top YouTuber MrBeast has named his first chief marketing officer

support@mycoding.id (Lucia Moses) — Fri, 30 Oct 2026 17:23:04 +0700

YouTuber Jimmy Donaldson, a.k.a. MrBeast, is expanding his company's C-suite, naming his archetypal CMO. Sujit JAISWAL / AFP via Getty Images

MrBeast has established his archetypal CMO, Business Insider exclusively learned.

The top YouTuber's business promoted Michelle St. Jacques to the role. St. Jacques has led person goods, including Feastables, MrBeast's snack and candy company, since February.

In her new role, she'll add promotion duties for Beast Industries, the star's holding company, during continuing to oversee person goods. She's based in Chicago.

Beast Industries started the search before this year, a move that reflected the company's expanding ambitions. It's been expanding far beyond its center YouTube conduit and seeks to rotate into a Disney-style amusement giant.

Beast Industries CEO Jeff Housenbold stated in a memo to staff, viewed by Business Insider, that he considered external candidates for the CMO function but decided St. Jacques was the finest individual for the job.

"In her period at Beast, MSJ has shown she can set apparent scheme and provision powerful implementation for our products and partners," he wrote. "She has served as the two CMO and Chief Commercial Officer and built iconic person brands akin Dove, Heinz, Miller Lite, and Coors Light. She's additionally a world-class group chief who knows how to build high-performing teams."

St. Jacques joined the business following a slowdown in Feastables' growth.

Housenbold wrote that St. Jacques' remit would affect defining the MrBeast brand and making certain everything the business does ladders up to the identical positioning; foremost promotion for MrBeast and partner brands; and overseeing the viral promotion team. He stated that he saw an chance to lean into e-commerce and achievement promotion to run client acquisition and retention.

St. Jacques steps into a function overseeing a brand that's looking to lessen its reliance on its celebrated founder. Her job requires person who can do everything from getting group to theatrical releases — Donaldson lent his sound to "Angry Birds Movie 3," which is scheduled for a December publish — to marketing snacks and toys in stores, or pitching fans on phone plans and financial products.

Beast Industries has made a cord of big hires to bulk up its administrator suite. Along alongside Feastables, the business has begun to move into financial services alongside the acquisition of the Step app and has planned a mobile phone service.

The business is additionally laying the groundwork to develop into ad and promotion services for brands and additional services for another autonomous satisfied creators akin MrBeast, and has teased a membership program.

Microsoft Bing New AI New Controls With AI Training From AI Search Grounding

support@mycoding.id (Barry@Rustybrick.com (Barry Schwartz)) — Fri, 30 Oct 2026 17:15:00 +0700

Microsoft fair announced new Bing AI satisfied controls "offering newer, simpler, and clearer preferences that authorize you to create choices concerning training, grounding, or the two during remaining eligible for Bing hunt results," Krishna Madhavan, Principal Product Manager, Microsoft Bing, wrote. Google is also on board, it seems.

In summary, this gives location owners three chief options, including:

AI Training environment to authorize or forestall your satisfied from being used to train AI models.
AI Grounding environment to authorize or forestall your satisfied from being used to assistance create AI answers.
Limited Grounding environment to authorize your satisfied to assistance Microsoft's own AI products, but not its third-party grounding services.

This method you can obstacle AI training but motionless appear in AI answers. For example, a publishing company could forestall Microsoft from using its articles to train models during motionless allowing Copilot to citation those articles. You can obstacle AI answers from using your satisfied but doing so can decrease your visibility in AI experiences. The traditional Bing rankings are unaffected.

Here is the timeline for these changes:

December 15, 2026: Temporary grounding controls rotate into accessible in Bing Webmaster Tools for eligible sites using the older NoArchive or NoCache directives.
February 1, 2027: Microsoft starts honoring the new preferences as it crawls pages.
March 1, 2027: Deadline for publishers using the old directives to configure the new preferences if they desire to keep their restrictions.
September 30, 2027: Temporary grounding preferences expire.

The changes appear to add on to Bing's existing controls for managing how website satisfied appears in AI-generated answers. Bing Webmaster Tools additionally offers an AI Performance reporting that shows citations, cited URLs and grounding queries throughout supported AI experiences. The new preferences provision publishers additional granular authority complete how their satisfied can be used, separating AI example training from the use of satisfied to create AI answers during preserving traditional hunt visibility.

There are a lot additional item over current in the blog post and the documentation complete here.

Microsoft is joining industry peers in announcing a shared AI training penchant in robots.txt - and going additional alongside granular page-level training preferences and a distinct grounding penchant for publishers and location owners, the business announced.

Forum conversation at X.

US tech stocks see sharp falls over AI cost fears

support@mycoding.id (Putri Silvia) — Fri, 30 Oct 2026 17:13:02 +0700

US stocks have continued to glide as concerns continue to intensify complete the expanding expenses of the synthetic intellect (AI) build out.

Shares in Intel continued their overnight glide into first selling on Friday, falling as much as 30% following the part creator warned of a weaker device market equal as it plans to addition spending on AI.

Amazon shares cut as far as 6% before recovering following its reported earnings on Thursday evening cut abbreviated of investors' expectations.

The tech-heavy Nasdaq inventory toggle opened on Friday at its lowest flat in additional than two months, downward 2.5%, as another tech stocks including Reddit and Roblox continued to fall.

The losses prosecute the value of Google owner Alphabet plunging by additional than $500bn on Thursday following it revealed its own AI summaries were affecting its center hunt promotion revenue.

Alphabet inventory continued to autumn in first trading, downward 1% following Thursday's enormous slide.

The bigger losses on Friday were elsewhere, alongside Intel on track to endure additional than $130bn in value following its earnings update rattled investors.

On Thursday, Intel's backing chief David Zinsner stated the resolute did not anticipate to bring in additional prosperity than it spent this year, and forecast lower-than-expected income for its fourth quarter.

"Looking ahead, we see the PC slowdown continuing at smallest through the archetypal fractional of next year," he stated in the part maker's third fourth earnings report.

In the earnings call, he stated the resolute had considerably ramped up funding in equipment in the third fourth and expected that to be "even additional significant" in the following three months.

Amazon on Thursday revealed the business was additionally spending additional prosperity that it was making, and that spending had risen six-fold complete the extend of three months.

Shares in Amazon restored slightly from the overnight autumn but were motionless downward concerning 1.6% in Friday trading.

Reddit inventory was downward by 26%, following the social media phase revealed weaker-than-expected regular person figures and warned that Google's expanding AI-driven hunt was hurting referral traffic.

Stock in online equivalent phase Roblox additionally fell, downward by nearly 20%, as its regular energetic person numbers dropped.

Several important tech firms have reported earnings this week, including Microsoft, and analysts stated there were questions concerning the payout from the huge investments in AI.

Chris Low, from funding administration resolute FHN Financial, stated the bulk of what was happening in the inventory market was in reply to several of the biggest tech players specified as Amazon and Google.

He told Reuters the companies were "showing several beautiful important expanding pains as they aggressively prosecute the AI build-out".

"The thinking is that these signs propose that the complete field is going to dilatory down."

My wife and I split our mortgage and bills equally — even after my layoff over a year ago. The setup feels fair to us.

support@mycoding.id (Aleenah Ansari) — Fri, 30 Oct 2026 17:08:01 +0700

Financial transparency has continually been crucial to my spouse and me. Noelle Thies Co.

Ever since my spouse and I started courtship concerning eight years ago, we've talked openly concerning our individual finances.

From the extremely beginning, we discussed our 401(k) withholdings and emergency funds. These conversations became equal additional crucial whenever we started living together and sharing expenses concerning a twelvemonth into our relationship.

As a queer couple, my spouse and I have continually believed that we can compose our own rules whenever it comes to how we method our finances.

Our incomes have varied complete the years for many reasons, and we've tried multiple distinct fee breakdowns before finding what plant for us.

Over the years, we've divided our home loan payments a few distinct ways to discover what feels 'fair'

Over time, we moved toward a 50/50 divided of the mortgage. Noelle Thies Co.

About a twelvemonth into our relationship, my now-wife moved into the condo that I had bought on my own. At the time, I was working in tech and earning a higher basis salary, as fine as annual performance-based bonuses and inventory that added to our pay discrepancy.

I knew that my home loan was higher than the rent on a location we would have chosen together according to our blended income. So, we decided I would pay the bulk of it, but we'd divided the expenses of groceries, utilities, and internet, as fine as shared vacations.

Five years into our relationship, I sold my old condo, my spouse risen her hours at her job, and we bought a townhome together.

This time, we decided to divided our home loan payments in proportion to our basis salaries, which felt akin the fairest item to difference since annual bonuses and inventory awards from my business could vary. This came out to a 60/40 split.

Over the next two years, my wife's basis pay got nearer to quarry hence of union negotiations at her hospital. Eventually, formerly our salaries were basically at parity, we shifted to a 50/50 split.

When I got laid off from my tech job, we had to reevaluate what was 'fair'

Almost eight months into our new system, I was laid off from my tech job.

I had funds in my emergency prosperity from my years operating there and received severance, but I was abruptly in a distinct financial circumstance than I'd been before.

For the archetypal period in our relationship, my spouse was the higher earner.

We talked concerning moving rear to a proportionate split. My spouse reminded me that we were a team, and stated she'd be open to covering additional of our home loan and expenses. But between my savings, severance, and bonuses I'd made complete the years, I was capable to continue splitting the home loan evenly, and I wanted to.

At the end of the day, reverting to a distinct divided power have been "fair," but it didn't feel fair of me to put the duty on my spouse to pay additional of the mortgage.

I knew that paying a much larger portion of the home loan would bring undue emphasis on her, and I additionally knew that I could oversee my half, equal without my dependable paycheck.

Defining fairness on our own conditions has felt empowering

Our precedence is that we the two awareness comfortable revisiting the topic of prosperity whenever we need to. Noelle Thies Co.

It's now been complete a twelvemonth since my layoff, and splitting our home loan and expenses 50/50 has continued to awareness correct for the two of us.

This isn't to say she's not supporting me during this time. Right now, my spouse continues to activity full-time during I'm doing freelance and agreement activity for assorted clients. She's covering additional of our market expenses, and I'm additionally on her health insurance.

We're a team, and I'm learning to obtain her assistance in ways that awareness fair to the two of us.

We the two cognize that our jobs, accommodation situation, and method to individual backing volition evolve, particularly as we build our careers. What matters to us is having ongoing check-ins concerning whether our home loan breakdown feels correct and supporting all another likewise in another ways, too.

After all, what's fair as crucial is celebrating all other's accomplishments, encouraging all another to study new skills, and contributing to our family and the labor it takes to run it. Money is lone one part of the puzzle.

A wounded Ukrainian soldier thought he was going to die. Then a drone pilot flew 'like a ninja' to airlift him out.

support@mycoding.id (Jake Epstein) — Fri, 30 Oct 2026 17:05:30 +0700

Ukrainian forces used the new StarGate drone to drag off two daring rescue missions in October. Courtesy of SkyFall

Izyum idea he was going to die. A devastating blast had taken part of the Ukrainian infantryman's remaining foot, and he had misplaced a lot of blood. To create matters worse, Russian soldiers were decision in on his position, and there was no uncomplicated escape.

Then came a drone — a enormous six-rotor airplane alongside an enclosed stretcher underneath. It landed approximately 10 meters distant from Izyum's position, in lofty turf beside a minefield. Fiber-optic cables were strewn throughout the area, and he concerned the hazards would forestall the rescue drone from taking off.

Dizzy and nauseous, Izyum's comrades helped him complete to the different aircraft. Summoning what small power he had left, he hoisted himself into the stretcher capsule. As the drone lifted off, he breathed a small easier, at final emotion several awareness of relief.

Izyum is one of two Ukrainian soldiers who have been airlifted out of combat by the new specialized StarGate uncrewed aircraft, which was lately unveiled by Ukrainian business SkyFall. The hurt soldiers were medically evacuated this duration in back-to-back rescue missions.

Izyum and KVN, a drone aviator in Ukraine's 475th Separate Assault Regiment who flew StarGate during the rescues, described the missions to Business Insider in interviews this week. Both said through a translator and were identified lone by their call signs for safety reasons.

Casualty elimination by airborne drone is a new idea being pioneered in Ukraine. This month's rescue missions were among the archetypal of their benevolent in combat. Soldiers and defence industry officials say they anticipate to see additional of these missions in the forthcoming and accept this experimental maneuver is a crucial capability, particularly in moments whenever neither medicinal teams nor robots can attain hurt troops.

Izyum being helped to the drone. Courtesy of SkyFall

Right now, this method is seen as a final retreat — a break-glass choice for whenever battlefield conditions prevent all another elimination methods.

A daring mission

KVN's archetypal female had fair been delivered whenever the call came in. The 475th assault regiment, known as CODE 9.2, was preparing for a particular operation, and guidance needed him to fly the chief drone. A car was on its way to choice him up.

He shortly arrived at an undisclosed location in Ukraine for the operation, the rescue of a hurt serviceman from the 129th Separate Heavy Mechanized Brigade.

At the center of the procedure was StarGate, a dense hexacopter that SkyFall developed for CODE 9.2 specifically for casualty elimination purposes. The drone — which SkyFall stated is the archetypal of its benevolent — was unveiled in mid-October, lone days before KVN's mission.

Ukraine is increasingly turning to robots to evacuate hurt soldiers in combat. With surveillance and assault drones swarming the forefront lines, nearly any movement carries enormous risks, making it hazardous for teams to recover casualties. Ground robots are one solution, but durable terrain can bounds anywhere they can go.

StarGate is a dense hexacopter developed by SkyFall. Courtesy of SkyFall

Heavy hexacopters have emerged as an choice whenever another extraction methods are not possible. Earlier this month, Ukraine carried out its archetypal casualty elimination using an airborne drone, rescuing an infantryman from the 30th Separate Mechanized Brigade alongside a Heavy Shot Ayudag-6 dense lift drone developed by Gurzuf Defence.

There have since been two additional missions. KVN was the aviator for both, flying Skyfall's StarGate drone.

KVN recalled that his archetypal elimination happened at night. There were dozens of group — most of them from CODE 9.2, but several from another armed forces units — engaged in the rescue operation. The SkyFall squad additionally participated in the planning.

KVN was nervous.

Reaching the casualty meant flying 20 miles out and rear through areas inundated alongside Russian drones and digital war that threatened to derail the mission.

So the Ukrainians assembled item akin to a attack package, alongside additional than a dozen drones flying alongside StarGate to defend it from attack, diagram Russian notice distant from the rescue, and bomb enemy positions near the elimination point.

The serviceman rescued in the archetypal mission, who goes by his call sign Kolobok, crawls to the drone. Courtesy of SkyFall

Russian first-person-view (FPV) drones initially prevented the rescue drone from taking off alongside the hurt soldier, but eventually the skies cleared. KVN stated his hands were shaking, but he relied on StarGate's built-in stabilization innovation and his teammates' assistance to dependable the drone and his nerves.

The archetypal elimination took 30 minutes. StarGate didn't have the range for the complete 40-mile circular trip, so KVN had to district it midway on all leg so dirt teams could toggle out the batteries.

After the mission, KVN grabbed several much-needed sleep. When he woke the next morning, he learned that a second elimination had been approved and would shortly be underway.

Flying akin a ninja

Izyum, an infantryman in Ukraine's 1st Territorial Defense Brigade, sat downward on the dirt to rest.

His squad had been tasked alongside holding a stance they had fair assaulted. When Izyum stood up, he triggered a blast that tore off part of his remaining foot. His comrades pulled him into a dugout and immediately applied a tourniquet.

Ukrainian soldiers stated they anticipation to see additional airborne evacuations in the future. Courtesy of SkyFall

They radioed rear to their commanders that Izyum had suffered a serious hurt and needed evacuation.

The circumstance was dire. Any attempt to stroll to higher-level attention would average navigating approximately 20 miles of Russian drone and quarry threats. Izyum had misplaced so much blood, and his power was fading fast. Given the severity of his injuries, he would never have been capable to create that trek on his own. His chap soldiers would have had to hazard their lives to assistance him create the journey.

And dirt robots, increasingly used by Ukraine to evacuate hurt soldiers as the front-line slay area grows additional perilous, couldn't attain his stance since ponds, small rivers, and tree lines blocked their path.

Brigade guidance concluded that the lone choice was to evacuate him by air. And alongside crewed helicopters efficiently out of the question, they needed a drone. StarGate was chosen for the mission.

Izyum didn't think he was going to create it home. His squad was so profound on the forefront lines, and the Russians were close. At one point, the enemy was lone 5 meters out.

Eventually, the rescue drone arrived. As the StarGate drone landed amid a disorder of mines and cables, Ukrainian forces used Vampire drones, smaller hexacopters made by SkyFall, to bomb the Russians and keep them at bay.

Izyum emerging from the drone's stretcher. Courtesy of SkyFall

KVN stated landing near the minefield was among the biggest challenges he faced during the mission, although Russian drone and digital war threats were additionally problems. He stated he had to fly "like a ninja" to evade them.

Even alongside new technologies specified as drones and dirt robots, evacuating hurt soldiers isn't an uncomplicated process, and it takes period to plan, prepare, and execute. Nearly two days passed between Izyum's hurt and his rescue. When he landed and opened the capsule to see affable faces, he eventually felt harmless for the archetypal period since the blast. KVN, too, felt an overwhelming awareness of alleviation whenever the goal was eventually over.

Izyum had four surgeries and is missing fractional his foot. He volition shortly be transferred to a rehabilitation facility. Speaking from a hospital in northeast Ukraine, he stated that he is grateful to everyone who saved his life.

Some Ukrainian officials have acknowledged that ample rescue hexacopters could be uncomplicated targets for Russia and stated that they should lone be used in the most extreme circumstances.

Both KVN and Izyum, however, stated that airborne drone casualty evacuations have to be expanded as norm practice; CODE 9.2, for instance, plans to create dedicated units for these missions, and SkyFall is aiming to build out a division inside the resolute specifically for evacuations.

StarGate drones — which disbursal approximately $50,000 a unit, can transport up to 330 pounds, and can fly at speeds complete 60 miles per hr — are armed alongside survivability features, specified as artificial intelligence-enabled navigation and communication redundancies. SkyFall stated it aims to be capable to create 1,000 drones a duration by the end of 2026.

How future Navy Officers survive "First Tuesday" at OCS

support@mycoding.id (Graham Flanagan) — Fri, 30 Oct 2026 17:00:01 +0700

Description

On their archetypal day of training, all aspiring officers in US Navy Officer Candidate School must withstand a punishing gauntlet known as "First Tuesday," an serious event that tests them mentally and physically in the extend of fair under two hours.

Business Insider's chief video equal Graham Flanagan went inner "First Tuesday" at Navy OCS in Newport, Rhode Island as 126 candidates began their journey toward earning their commissions as Naval officers.

Led by a US Marine Corps drill instructor, the event sets the spirit for the 13-week training course, possibly weeding out anyone having second thoughts.

AI Isn't Replacing SREs. It's Deskilling Them

support@mycoding.id (Putri Silvia) — Fri, 30 Oct 2026 16:52:18 +0700

💌 Hey there, it’s Elizabeth from SigNoz!
This newsletter is an honest attempt to conversation concerning all things - observability, OpenTelemetry, open-source and the engineering in between!
&
This part took 6 days, 5 hours to be cooked, anticipation we served. 🌚

There are two famous prophecies floating about tech circles these days.

The archetypal says SRE is the forthcoming of all application engineering, that as AI writes additional and additional code, the humans who remain volition be the ones keeping systems alive. The second says AI volition consume all tech job alive, SREs included. Neither is particularly helpful if you’re an SRE trying to fig out what your Tuesday volition appearance akin in 2027.

Let’s ask a additional restricted inquiry by looking at what’s already happening: When AI handles 95% of your event response, do you get worse at handling the 5% that really matters?

Most of us already use AI for our regular activity (our brains a small fried!), and so do SREs. Today’s conversation agenda is not whether AI replaces SREs, but whether AI is quietly making SREs small capable and whether anyone volition notice item before the next novel outage hits. The foundational example for this complete conversation comes from a 1983 investigation document that’s eerily prescient.

Note from author: Below is a concise precursor to History of Automation, which you power bask if you are into History and Cultures (like me 😉).

In 1983, a cognitive therapist named Lisanne Bainbridge published a document called Ironies of Automation. It became among the most cited document in individual factors research, and its center disagreement is nearly uncomfortably applicable today.

Bainbridge studied what happened whenever factories and manufacturing systems automated the activity of blue-collar operators. The findings were paradoxical and revealed that the additional you automate a process, the additional crucial the individual controller becomes during the rare moments automation fails and the small custom they get, and the worse they rotate into at exactly those interventions. Automation, which was inherently designed to eliminate humans from the loop, remaining them alongside the worst imaginable job, i.e., lengthy stretches of passive monitoring punctuated by rare, high-stakes crises they were increasingly unprepared for.

Ring any bells yet? 🙂

Basically, I’m example a parallel between the AI upheaval and manufacturing automation. Industrial automation reshaped blue-collar activity by taking complete regular bodily tasks, and the workers who remained had to grip exceptions they’d misplaced the muscle recollection for. AI is doing the identical item to cognition workers by taking complete the regular cognitive tasks, the form matching, the triage, the known-issue resolution and leaving humans alongside the rare, complex, ambiguous problems.

The exact problems that necessitate profound expertise, the exact expertise that atrophies whenever you halt practising.

Now we’re replaying this form alongside AI agents, and the stakes in application systems are lone growing.

Let’s obtain inventory of anywhere things remain today in the earth of location reliability engineering.

Alert noise decrease and intelligent grouping, runbook implementation for known issues, log form finding and anomaly flagging, and essential root-cause suggestions from historic event data, and auto-remediation for well-understood nonaccomplishment modes akin restarting a wrecked pod or scaling up a assistance that’s operating hot, are all fairly automated today.

Some contiguous targets contain multi-signal association throughout metrics, logs, and traces, autonomous root-cause inspection for partially understood failures, predictive event finding before users are affected, AI-driven alter hazard appraisal and automated rollbacks.

PagerDuty frames this as a tiered model.

Tier 1 incidents: Known issues alongside known fixes get completely automated.
Tier 2 incidents: Partially understood problems obtain AI recommendations alongside individual validation.
Tier 3 incidents: Novel, complex, cascading failures remain human-led, alongside AI providing supporting context.

But here’s the catch.

If human SREs (okay, now we have to use adjectives akin individual 🥹) lone affect alongside Tier 3 incidents, ie the novel, never-before-seen outages, anywhere do they build the intuition to grip them? Intuition is normally developed from years of hands-on event response, form acknowledgment built through repetition, and the benevolent of gut-level understanding of a scheme that lone develops from painfully waking up at the odd hr to resolve the bug that brought the scheme down.

This is anywhere the image starts getting blurry. Let’s appearance at several emerging investigation on AI-induced deskilling throughout multiple fields, which paints a accordant and concerning picture.

In medicine, a recent study established that endoscopists who used AI aid for polyp finding saw their unassisted finding rates autumn from 28% to 22% following a duration of AI use. They got worse at the item they were expected to be experts in, not since they forgot the theory, but since they stopped exercising the skill.

In aviation, research has shown that long-haul pilots who depend heavily on autopilot systems cognition measurable degradation in situational awareness and manual flying ability. The issue got grave adequate that the FAA now mandates additional manual flying period to counteract the effect.

Somewhere complete the former year, AI stopped being a tool I occasionally reached for and became the archetypal item I attain for, always. My intuition now is to offload as much as imaginable and use my own thinking lone anywhere it’s entirely unavoidable. The issue is that these moments are becoming the lone exercises my brain gets, and I can awareness the rust.

We can diagram a form here. The additional you let the scheme handle, the worse you get at handling things yourself and here’s the really hazardous part, you don’t awareness it happening. It gets masked as hyper-productivity. Cognitive investigation suggests that since AI tools create tasks awareness easier and enhance apparent performance, users are frequently unable to accurately fairness the true position of their own skills. You awareness competent, dashboards appearance green, and afterward on a Wednesday, a novel event hits that doesn’t equivalent any form the AI has seen, and you realise the muscle has atrophied.

For SREs, this manifests in particular ways, akin we halt study raw log streams since the AI summarises them, we halt forming hypotheses during incidents since the AI suggests base causes, we halt construction mental models of scheme architecture since the AI maps requirements for us, and all of these individually looks akin a efficiency win. Collectively, they hollow out the extremely ability that makes an SRE productive whenever things go sideways in ways nobody anticipated.

But there’s item equal additional concerning than deskilling, and researchers have started calling it never-skilling. Deskilling method you formerly had a capability but have since misplaced it. Never-skilling method you never developed it in the archetypal place. For younger SREs entering the site today in an surroundings anywhere AI handles most of the event reply workflow, the opportunities to build foundational intuition and muscle through hands-on custom are vanishing.

The training pipeline itself is damaged and not self-healing.

SREs realise their skills are degrading and lean additional on AI to compensate, which additional degrades their skills, creating a vicious sequence from which escape is difficult.

We are certainly not rejecting AI tooling; we are adopting it and integrating it stronger than always before, since that’s the lone way forward.

A few approaches value considering:

Deliberate inefficiency. Just as the FAA mandates manual flying period equal whenever the autopilot is absolutely capable, SRE teams can designate certain incidents, equal the ones the AI could handle, as human-practice opportunities. This can be considered as a long-term funding to keep skills fresh, although it power arrive at the disbursal of a super-fast solution

Build for human-in-the-loop, not human-on-the-side. There’s a meaningful difference between a scheme anywhere a individual approves an AI’s advice and one anywhere a individual actively engages alongside the issue alongside AI. The erstwhile keeps humans in a supervisory function that Bainbridge (the female who wrote that investigation document concerning 40 years ago) showed leads to vigilance decay, and the second keeps them cognitively engaged.

Let’s zoom out and obtain a appearance at the bigger picture.

Everything we’ve discussed here, the ironies of automation, the deskilling risk, the never-skilling problem, collectively applies fine beyond SRE. Software engineering as a entire is navigating the identical tension. As AI writes additional code, reviews additional PRs, and handles additional debugging, the identical questions apply.

We’re talking concerning SREs specifically since that’s the earth we live in at SigNoz. We build an open-source observability platform, the benevolent of tool that gives SREs the metrics, traces, and logs they need to comprehend their systems deeply. For us, this deskilling inquiry is not a rhetorical fad; it immediately shapes how we’re construction AI into our product.

Our method is to commencement alongside an AI aide that helps SREs leverage the power of LLMs during keeping humans firmly in control. Eventually, we’ll allow additional autonomy but inside apparent guardrails, and lone as rely is earned.

One advantage we have in this area is that, as an observability platform, we sit on the data itself, the metrics, traces, and logs that SREs depend on. Most AI SRE products today merge alongside observability tools through APIs, which method they’re operating alongside a limited, second-hand perspective of your systems. Because we own the data layer, we can build much deeper, additional context-aware AI capabilities that comprehend your scheme the way an informed SRE would.

And to answer the burning inquiry in your head, our goal isn’t AI that replaces SREs. It’s AI that supercharges SREs. Unlike ongoing lore, we accept humans volition remain essential for the decisions that matter most, particularly those that effect manufacturing infrastructure.

The forthcoming of SRE is individual with AI intentionally designed to keep humans sharp, engaged, and prepared for the 5% that really counts.

Here’s the LinkedIn post our originator posted a few days ago, which inspired me to compose this.

Discussion concerning this post

Florilegium: Procedural Flowers in LaTeX

support@mycoding.id (Putri Silvia) — Fri, 30 Oct 2026 16:48:12 +0700

The Reddit post asked how to create flowers akin these in LaTeX. I don't cognize how the first was made, and this project doesn't try to reproduce it. It is one imaginable way, and the way I did it: hand-authored primitives alongside randomized parameters, painted in Lua, placed by a procedural layout whose "fill the unused space" part borrows a 1998 idea from the ornament literature. It gets a akin look.

Procedurally generated Delft-blue floral leaf margins for LaTeX. No images, no imported paths, no external assets: all petal, leaf and stem is a parametric curve computed in Lua while the leaf is being written, painted akin a watercolor, and written direct into the PDF. Every leaf gets its own garden.

Six seeds of the grown composition. Same code, distinct kernel — and the storyline fills whatever area the content leaves free.

Two documents portion one package, and a third shows what alternatively it does:

Both PDFs are self-describing: the build content is the write-up of how the border is drawn.

Last leaf of the grown document: the content ends early, so branches arch into the area below.

300 dpi crop. Mottled washes alongside pale streaks lifted out, lobed leaves alongside pale veins, forget-me-not cymes, a faint shade angiosperm rearward the stems.

Seed 6, from an bare border to the completed page. The stems increase first, leaves open as the tips continue their nodes, and all stem ends in a flower. Then the greedy iteration takes over: on the right, all dashed circle is the largest liberated disc it found, fair before a branch grows to it. Big holes arrive archetypal and slowly, small ones final and fast. The butterflies and bees fly in, the animal glides onto its twig, and the snail crawls up its stem until the last frame, which is exactly the leaf this kernel continually gives.

The growth is recorded once, during the leaf is laid out: all stem is additionally drawn as prefixes of expanding dimension and all motif at a few smaller scales, replaying the same random draws. A example afterward writes the pieces whose period has come, in their original painting order. create grow-6 renders one kernel this way (build/grow-6.gif and .mp4, about 45 seconds); add EXPLAIN=1 for the dashed circles.

The border says the text

showcase.tex, "A twelvemonth in the margin": fountain on the archetypal page, summer, autumn on the last. Each division describes the characteristic it shows.

The grown border can react to the document about it:

Initials. \florilegiuminitial[5]{E} sets the archetypal letter of a paragraph in a tile five lines tall. The outline of the letter is peruse from an OpenType font (Latin Modern Bold by default) and painted akin a petal; a vine passes complete and under its strokes in turn, alongside leaves anywhere they fit and flowers in the gaps, frequently in the letter's counters. The letter is additionally typeset invisibly, so the paragraph motionless copies as "Every".
Flowers at the headings. With the choice sections, all numbered division and subsection gets a angiosperm in the border beside its heading, painted in the copper of the accents, the way headings were formerly picked out in red.
A angiosperm anywhere the content asks. \florilegiumbloom puts a angiosperm beside the row it stands in; \florilegiumbloom[lily] asks for any motif of the garden. The marks are found in the leaf box whenever the leaf is shipped out, so this plant in one run.
Seasons. With the choice aging, the storyline ages from fountain on the archetypal page (mostly in bud, small faint leaves) to autumn on the final (seed heads, falling petals, a few copper leaves). It needs two runs, for the leaf count; \florilegiumage{0.8} sets an age by hand instead.

One kernel in spring, first summer, delayed summer and autumn. The seasons alter what grows, not where.

Most pages have visitors: a butterfly or two and bees in the open spaces, a snail crawling up among the chief stems, and on concerning one leaf in five a animal perched on a twig of its own. They arrive from a random stream of their own, so a leaf without them is exactly the leaf it would have been; the choice novisitors leaves them out.

The entire palette comes from one color, ink: Delft blue, sepia, green, crimson, violet, teal. The ramp from the darkest blow to the palest cleanse is computed from that hue in OKLCH, so the ray end never turns gray.

postscript/florilegium.ps: the grown border in clean PostScript, one self-contained file. Ghostscript, or a printer, computes all petal during it interprets the page, and the two pages of content explain how.

The example core, all primitive and the growth iteration are ported from ink.lua, flora.lua and grow.lua, procedure for procedure. It needs no TeX and no another file:

gs -dALLOWPSTRANSPARENCY -sDEVICE=pdfwrite -dSeed=7 -o garden.pdf postscript/florilegium.ps make postscript # the identical -> build/postscript-7.pdf; SEED=12 for another garden

-dSeed=N picks the garden; without it the clock picks one, so all imprint is new. -dAge=0 to 1 sets the season, and -dNoVisitors leaves out the butterflies, bees, snail and bird. Two pages obtain concerning 2.5 seconds. Much of the Lua maps directly: PostScript's own transformation matrix places all primitive (translate, rotate, scale), paths and Bézier curves are native, and procedures built at run period remain in for Lua's closures (a petal's half-width is a procedure handed to the outline builder). Four things don't map:

Layers. The storyline grows in one command but is painted rear to front, so all inhabit and stroke is captured alongside pathforall into a catalog per layer, and the lists are played back at the end.
Transparency. PostScript has none. Ghostscript provides it alongside -dALLOWPSTRANSPARENCY. Without that flag, or on a printer, all translucent inhabit is blended alongside the color it is likely to district on and painted opaque. The outcome is flatter, but it's the identical garden.
Randomness. The generator is Park-Miller in 32-bit entire figure arithmetic, and PostScript reals are sole precision, so kernel 7 current is a distinct storyline from kernel 7 in LaTeX.
Text. The document typesets its own two pages in Times. It knows anywhere its headings are and where its content ends, so the copper flowers at the headings and the storyline under the last line activity as they do in LaTeX. It has no initials, animation or authored composition.

The document sent twice to an Epson inkjet alongside lp postscript/florilegium.ps, alongside no seed given. The computer's imprint scheme runs the program again for all job, so all imprint takes its kernel from the clock and grows a distinct garden. A printer gets the opaque version, as it has no transparency.

LuaLaTeX, one pass, concerning a second a leaf (two passes for showcase.tex, whose seasons need the leaf count).

make # the three PDFs make seed-7 # one leaf from kernel 7 -> build/seed-7.pdf make exhibition # gallery/seeds.png + seeds.gif, inks.png, seasons.png (python3, Pillow, pdftoppm) make grow-6 # growth animation of kernel 6 -> build/grow-6.gif + .mp4 (ffmpeg) make grow-6 EXPLAIN=1 # the identical alongside the liberated discs marked -> build/grow-6-explain.*

No TeX installed? Build the depiction formerly and run everything in it:

docker build -t florilegium-tex tools make RUN=tools/in-docker

Or paste florilegium.sty, the six .lua records and among the .tex records into an Overleaf project and set the compiler to LuaLaTeX.

Use it in your own document:

\usepackage[grown]{florilegium} % or plain \usepackage{florilegium} for the authored one % options for the grown one: sections (flowers at the headings), aging (two runs), % novisitors (no butterflies, bees, snails or birds) \definecolor{ink}{HTML}{5B2A1F} % optional: the hue of the entire palette (this is sepia) \definecolor{accent}{HTML}{B4662F} % optional: the copper of the hairlines ... \florilegiuminitial[4]{T}his paragraph starts alongside a adorned T. ... a angiosperm in the border beside this line\florilegiumbloom ... \florilegiumage{0.8} % grown only: autumn from current on \florilegiumtextend % grown only: at the extremely end of the text

A fixed kernel alternatively of the leaf number: lualatex "\def\florilegiumseed{7}\input{florilegium-grow.tex}".

Any primitive can be drawn on its own inner a TikZ picture, under the current scope's shift, rotation and scale:

\begin{tikzpicture} \begin{scope}[shift={(2,2)},rotate=20]\florilegiumdraw{flower}{1.3}\end{scope} \begin{scope}[shift={(5,0)}]\florilegiumdraw{leaf}{3.0, {depth=0.6}}\end{scope} \begin{scope}[shift={(8,1)}]\florilegiumdraw{ghost}{"lily", {s=1.4}}\end{scope} \begin{scope}[shift={(11,1)}]\florilegiumdraw{butterfly}{1.5}\end{scope} \end{tikzpicture}

Drawing (ink.lua). All geometry is computed in Lua and written as PDF way operators into one literal node per page; TeX does no arithmetic. Primitives are drawn in a local frame under an affine transform, which is peruse from TikZ whenever a primitive is called inside a scope. Colors arrive from a spirit ramp derived from the one document color ink: navy to mist at the hue of ink, interpolated in OKLCH so the ray end stays blue alternatively of turning gray. Tapered strokes are two offset Béziers, not sampled ribbons.

Primitives (flora.lua). Painted in the command a watercolorist would: a flat wash, darker blotches multiplied complete it, pigment pooling at the edges, streaks lifted out in white, a few fine veins, and nearly no outlines. Broad petals and flowers, celebrity lilies seen at a tilt, blossoms and florets, buds and bellflowers; lobed and complete leaves; forget-me-not cymes that curl akin a scorpion's tail, branching sprigs, umbels, tendrils, kernel heads; butterflies, bees, snails and a bird; copper sparkles, rosettes and the ivy-leaf fleuron whose stem becomes the caput rule. Any of them can be painted as a faint ghost.

Authored composition (authored.lua). A factory grows from a base in the bottom-left corner: three stems through hand-picked authority points, a fourth alongside the base of the page as the footer, leaves at chosen fractions of the stems, and all another motif on a branch that leaves its stem tangentially and arrives alongside the motif's axis — so every flower can be traced rear to the root.

Grown composition (grow.lua), in the soul of Wong, Zongker & Salesin, Computer-Generated Floral Ornament (SIGGRAPH 1998). The stems sway up the pillar as gentle noise of their height; leaves are hung at their nodes anywhere there is room. Then, repeatedly: obtain the largest liberated disc within reach of a stem, choose a motif that fits it, and develop a branch to it from the nearest stem point; the branch becomes a stem in turn. Big holes are taken first, so flowers and lilies land early, sprays and leaves inhabit the middle, and the iteration ends by tucking leaflets, buds and florets onto the stems. The end of the content is measured alongside \pagetotal in the same pass, so a abbreviated final leaf grows branches into the area below it alongside one compilation.

Reading the page (florilegium.lua). A heading or \florilegiumbloom leaves an invisible marker node in the text. When the leaf is shipped out, its box is walked node by node, adding up heights, depths and the glue as it was set, to discover all marker's height on the page; the storyline afterward gives those lines their flowers before any leaf is hung. An age reweights the motifs: buds and sprays of buds in spring, kernel heads in autumn, whenever some leaves are painted alongside a ramp built from the accent alternatively of the ink.

Initials (initial.lua). The letter's outline comes from luaotfload's OpenType audience as Bézier segments. Flattened into polygons, it gives an even-odd inner test, and a grid of distances to the letter and the example finds the largest gaps for the flowers. The vine is a Catmull-Rom curve throughout the tile; anywhere it crosses the letter it goes complete and under in turn, and the strands that go complete are drawn again, clipped to the letter, alongside a lean halo of paper.

Procedural ≠ random. The kernel is derived from the leaf number, so leaf n always gets storyline n. Reproducibility is what makes the document stable adequate to typeset.

See CLAUDE.md for a handoff-style map of the code, the tunables, and ideas not yet done.

MIT.

Geist Serif

support@mycoding.id (Riki Setiawan) — Fri, 30 Oct 2026 16:46:42 +0700

Geist started as a monospace typeface for developers, built for the editors and terminals anywhere they expend their day doing their work. From there it grew into Geist Sans for merchandise interfaces, and afterward into Geist Pixel, which was inspired by the grids of first device screens.

Today, we're adding a new associate to the family: Geist Serif.

Geist Serif posters

Geist Serif is a high-contrast display serif built on the identical foundations as Geist Sans, Geist Mono, and Geist Pixel. It has fine, saw-toothed serifs and keen hairlines, and it was drawn to communicate messages powerfully the two in the bodily earth and on the high-density screens on contemporary devices.

Copy nexus to headingSame system, new voice

At Vercel, Geist Sans runs the product. For headlines, though, we wanted a second voice, one that belongs to the identical system, alternatively of a alien picked from a drop-down menu.

A lot of tech brands have moved distant from spotless sans-serifs to get several character back, and many of them get from vintage device ads. Geist Serif takes a distinct path: toward fashion, editorial design, and mag headlines. It's our homage to the artists rearward Rolling Stone and Harper's Bazaar.

From the beginning, all Geist family has peruse from a division of category history: the Swiss scheme movement, first terminal and DOS computing, and now editorial print.

Copy nexus to headingDisplay first

Geist Serif began as a set of sketches by Evil Rabbit, which Andrés Briganti afterward expanded. The archetypal alphabet already showed an expressive serif, in the soul of typefaces akin Victor Serif and Stanley.

Original Geist Serif drawings

When Mark Davis took complete the drawings, we made the archetypal publish a display visage for headlines, posters, and another ample sizes, during activity on the complete family continued. Print has continually struggled to clasp fine hairlines and keen serifs, but today's displays can grip a elevated flat of detail. We wanted the new visage to obtain complete advantage of contemporary screens, so we thinned all downstroke by 50% and tightened the sidebearings to shove the difference as far as it would go.

Each serif has a wedge on one flank and a curve on the other, so the proportions are traditional and appearance beautiful in print, but the building is new and optimized for digital devices.

We created item that could lone be made for today. Not overly blocky for screens from a decade ago, not filled alongside mechanical compromises for bodily ink. Just serifs at ideal points.
Mark Davis originator & font decorator at WORDMARK

Copy nexus to headingFrom the archetypal prototype to today

The archetypal prototype of Geist Serif was shared on April 1, 2026. Here's the identical word, Geist, in that prototype, compared alongside the display example shipping today.

Original prototype shown as dotted lines

Copy nexus to headingGeist grew teeth

The goal was to regard our first intent and keep the serif closely tied to the sans, equal whenever the alphabet sit on top of all other. Geist Serif’s stems equivalent Geist Sans, and the two portion widths and postures.

The saw-toothed serifs and elevated difference provision Geist an editorial voice. One expression kept coming up as all character was drawn: “Geist grew teeth.”

Copy nexus to headingFour families, one x-height

Geist Serif uses the identical cap height and x-height as Geist Sans, so you can autumn it into any Geist layout without moving a line. Mix Sans, Mono, Pixel, and Serif in the identical declaration and all term looks the identical size.

Copy nexus to headingFour variants, one axis

Like Geist Pixel, Geist Serif has a changeable axis that swaps the form of all dot in the font, including those on i and j and in punctuation. The axis is called Element Shape (ELSH), and it gives you four variants: Regular alongside circular dots (the default), Square, Triangle (a nod to the Vercel logo), and Heart.

Each type additionally ships as its own fixed file. If you use the changeable font, choice a type alongside font-variation-settings:

Copy nexus to headingCrafted by hand

In July the font had 227 glyphs. It now has 894 and covers 352 Latin-script languages, and we worked through additional than 52,000 kerning pairs to get the spacing right. Some of the particulars are tiny. The eye of the g, for example, is tilted exactly 7°.

Copy nexus to headingSpecs at a glance

Geist Serif ships with:

1 importance (Regular)
4 variants (Regular, Square, Triangle, Heart)
894 glyphs
5 stylistic sets (ss01 to ss05)
352 supported languages

Copy nexus to headingGetting started

Geist Serif ships in the identical bundle as the remainder of the family:

Exports and CSS variables:

GeistSerif (variable, all shapes): --font-geist-serif
GeistSerifRegular: --font-geist-serif-regular
GeistSerifSquare: --font-geist-serif-square
GeistSerifTriangle: --font-geist-serif-triangle
GeistSerifHeart: --font-geist-serif-heart

Each one has its own admission point, so you lone container the font document you use. For example, in layout.tsx alongside GeistSerifRegular:

import { GeistSerifRegular } from 'geist/font/serif/regular'; 
export default function RootLayout({ children }) { 
 <html lang="en" className={GeistSerifRegular.variable}>

You can additionally download the font files, test all stylistic set, and inspect all glyph at vercel.com/font.

Copy nexus to headingWhat’s next

Regular is the archetypal manner we’re releasing, and the remainder of the family is already in progress. We’re evaluation forthcoming versions during construction this one, so this publish is fair the start.

Copy nexus to headingWeights from Thin to Black

The changeable font volition range from Thin (100) to Black (900). In this week’s proofs, the g in Black is the letter we can’t halt looking at.

Copy nexus to headingToward a content face

To examine a content version, we built a foundry tool that measures strokes, including anywhere they meet, and thickens the display outlines. It edits the outlines directly, so we can set genuine words and see which strokes need additional weight.

Copy nexus to headingItalics, built regulation by rule

We’re additionally evolving an slanted generated entirely in Python. We slanted existing italics rear upright and compared them alongside their romans. With the viewpoint removed, the remaining differences display up clearly, and we turned them into rules we can test and revise. This slanted won’t be the final version, but breaking glyphs in code helps us discover the limits faster.

Copy nexus to headingMore scripts and Google Fonts

Cyrillic assistance is planned to equivalent Geist Sans and Geist Mono, and Geist Serif volition arrive to Google Fonts following launch.

Copy nexus to headingOne family

With Geist Sans, Geist Mono, Geist Pixel, and now Geist Serif, the family runs from UI content and code to expressive display type, and all four awareness at residence together.

Download Geist Serif and commencement building.

Thank you to everyone who made Geist Serif possible.

None of this would have been imaginable without an amazing collection of group rearward the scenes.

Huge gratitude to Andrés Briganti for starting this journey alongside me and example the archetypal type that everything alternatively grew from, and to Mark Davis for carrying it throughout the complete row alongside obsessive craft, from the expanded glyph set and changeable axis to all final kerning pair. Thanks additionally to Patrick McDonald and Marijana Pavlinić for the poster designs, to Luis Gutierrez Rico for the motion and amazing magic, to Christopher Kindl for shipping the bundle and rebuilding the landing leaf downward to the smallest details, and to Zahra Jabini for the coordination and specialized assistance that brought it all together. This was a true squad effort, and I’m grateful to have built it alongside all of you.

I didn't know I was lacking in Vitamin D until I collapsed at work

support@mycoding.id (Riki Setiawan) — Fri, 30 Oct 2026 16:36:18 +0700

16 hours ago

Vicki LoaderHealth reporter

Watch: "My low Vitamin D levels hit me akin a truck"

Twenty-three-year-old Saskia Reeves-Priestley was at activity whenever she abruptly collapsed.

"I fair felt really dizzy, really nauseous, was having bosom palpitations and was really hot," she says.

Saskia, a particular instructional needs teacher, was a eager goalkeeper who played football four times a week and felt fit and healthy. While her symptoms are not immediately connected to vitamin D deficiency - she realised item was wrong.

Blood tests afterward showed her flat was so low - it was "next to nothing".

According to data from the National Diet and Nutrition Survey, final twelvemonth nearly a fourth of 11- to 18-year-olds were categorized as deficient.

Vitamin D can arrive from our diet, in foods specified as oily seafood and meat, or supplements.

But most is made by our build whenever UV ray in sunlight hits the skin. Lower levels of sunlight - depending on anywhere in the earth you live or the period of twelvemonth - decrease the body's capability to create it.

Covering parts of the build and wearing sunscreen additionally has an effect - notwithstanding their protective advantages.

Those alongside darker skin need visibility to stronger ray to create the identical amount of vitamin D as lighter skin.

Doctors don't routinely recommendation lifeblood tests to inspect for vitamin D deficiency, but volition recommendation a supplement if a tolerant is concerned they power be elevated risk.

What are the symptoms - and their regular impact?

Vitamin D deficiency is connected to the skeletal sickness rickets in babies and infants. In adults it causes a akin weakening of the skeletal called osteomalacia.

"They call it the silent disease," says Dr Suma Uday, a paediatric endocrinologist who wants to lift awareness of the problem.

She warns that vitamin D deficiency in young group and adults is difficult to place and can be missed or misdiagnosed. Symptoms contain fatigue and shared and skeletal pain.

Uday says: "It's basically silently dining distant at the bones, leaving them softened and prone to breaks."

Amaka Osu

Amaka Osu says she doesn't think many of her allies realise what the symptoms are

Amaka was in the center of making meal at her university home in Liverpool whenever she started shaking.

"I couldn't really see in forefront of me," she says. Her housemate took her to A&E - afterward she too would be diagnosed as vitamin D deficient.

Other than emotion tired, she says she had no symptoms: "I'm a 21-year-old student. I've got activity and uni - I'm continually emotion tired."

She remembers her mother suffering from low vitamin D but says she did not realise it could happen to her.

After taking supplements, Amaka feels a lot better, but she is concerned in case it happens again. "It was scary and I don't desire to cognition that again."

Lifelong deficit in girls

Uday joins another clinicians and academics who have cast a collection - ACT NOW Vitamin D - calling for the threshold at which you are classified as deficient to be raised.

She says that would "catch" additional group alongside low vitamin D and provision a additional exact image of how general the matter is. It would additionally average they can treat the deficiency earlier, she says.

Uday warns of "a lifelong deficit" in women - in adolescence, afterward pregnancy, and afterward the newborn is affected.

"If you don't accurate it from the extremely beginning," she says, "this is going to power multiple generations."

Liam Asman

Saskia Reeves-Priestley plays football four times a week - and had no former symptoms

"It's shocking," says Prof Martin Hewison, from the University of Birmingham.

He tells me that notwithstanding being 100 years on from the finding of vitamin D "rickets hasn't gone away".

"If we have rickets in the community, there are going to be many additional group who are vitamin D deficient."

He says the authorities should appearance into wider fortification of food in which vitamins are added to foods during production. Countries akin Canada and Sweden have mandatory policies.

In the UK, several foods specified as dawn meal cereals and spreads are already fortified alongside vitamin D, but it is voluntary.

During the winter months, group commencement to endure their vitamin D levels.

"We power have to obtain that for certain groups vitamin D supplementation is a matter of course," says Hewison.

Saskia is now taking vitamin D supplements regularly - and is rear in goal.

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Warren Buffett hasn't had a drink of water in 50 years. At least, that's what he told Bill Ackman.

support@mycoding.id (Theron Mohamed) — Fri, 30 Oct 2026 16:36:11 +0700

Warren Buffett is a longtime fan of Cherry Coke. Daniel Acker/Bloomberg via Getty Images

Warren Buffett hasn't had a pane of h2o since at smallest the 1970s.

That's what the 96-year-old business icon formerly told Bill Ackman, the billionaire hedge prosperity director recalled during an event of the Equity Mates Investing podcast that aired this week.

Ackman stated that Buffett came complete for meal at his residence "years ago," and he'd made certain to inventory up on the legendary investor's favorite drink, Cherry Coke.

The Pershing Square originator and CEO stated that formerly they were sitting at the table, he asked Buffett whether he'd akin motionless or sparkling water. Buffett politely declined, opting for his preferred soda instead.

"But I said, you know, 'Don't you beverage water?'" Ackman recalled. "And he said, 'Bill, I haven't had h2o in 48 years.'"

Ackman didn't immediately react to a petition for additional item concerning Buffett's hydration habits.

Not drinking h2o power audio unbelievable, but Buffett — who retired as Berkshire Hathaway's CEO following 60 years in accusation final December, and as the company's chairman this September — is celebrated for drinking five cans of Coke daily.

He quipped in 2015 that he was "one-quarter Coca-Cola," as it accounted for 25% of his daily calories.

Buffett's affection of soda goes rear decades. During Berkshire's 1986 meeting, he declared that following "48 years of allegiance" to Pepsi, he was switching to Cherry Coke, saying it would be the meeting's authoritative beverage going forward.

Coca-Cola has additionally been one of Buffett's landmark investments. Berkshire hasn't touched its approximately 9% interest in the beverage elephantine since it completed construction it in the mid-1990s. The stance disbursal concerning $1.3 milliard and was value about $28 milliard at the end of December — a approximately 21-fold gain.

Coke is lone part of Buffett's iconic diet. He's known for grabbing McDonald's for dawn meal on his run to work, and munching on hot dogs, fries, popcorn, cookies, candy, ice cream, and another comfort foods.

His love of accelerated food and saccharine treats extends to his investments. Berkshire counts See's Candies and Dairy Queen among its subsidiaries, and Kraft Heinz among its largest inventory holdings.

Buffett's childlike tastes have led to issues in the past, including a disastrous sushi dinner in Tokyo.

Bill Gates and his then-wife, Melinda, went to awesome lengths to ensure the capitalist didn't starve whenever he joined them on a 17-day trip to China in 1995.

They organized for their hotel's chefs to be taught how to prepared hamburgers and fries, and whenever they climbed the Great Wall, they made certain to have Cherry Coke waiting for Buffett at the top.

Reddit is going logged-in only. Blame Google AI Overviews.

support@mycoding.id (Katie Notopoulos) — Fri, 30 Oct 2026 16:32:12 +0700

Reddit's Google search-fueled traffic bonanza has arrive to an end. Kirill KUDRYAVTSEV / AFP via Getty Images

Reddit announced on Thursday that it volition shortly commencement being a (mostly) logged-in-only experience, citing declining hunt traffic as among the reasons. Redditors, who are famously level-headed and open to change, reacted about how you would expect.

In an earnings call, CEO Steve Huffman stated that Google's AI Overviews "are not traffic drivers"," and that "Google has really shifted in their association alongside the remainder of the internet."

It wasn't so lengthy ago — June 2024 — that I wrote an part alongside the header "Reddit's traffic is way, way up. Like, banoodles up."

Things have changed a lot in those two abbreviated years!

Here's what happened rear in 2024. Reddit was going public, and fair made a deal alongside Google to licence gazillions of posts for Google's AI training. Reddit's hunt traffic was additionally way, way up.

It saw a 39% addition in traffic from May 2023 to May 2024, according to web analytics resolute Similarweb. This was a period duration anywhere another social companies saw much slower growth (and Facebook equal slightly declined). Much of that was since of Google hunt traffic.

But that was 2024. People were lone tentatively trying out these newfangled AI services akin ChatGPT as a possible hunt replacement. Google had fair launched its AI Overviews in hunt results in May 2024, and they didn't appear extremely helpful — it told people to put glue in their pizza, following all.

Fast onward to 2026, and group are much additional comfortable using AI services akin ChatGPT alternatively of Googling. You can ask Muse to shop for the finest air conditioner for you and equal create the purchase. Google AI overviews have gotten way, way better, making it so you rarely have to really click on a website to get your answer. Thanks to all this, hunt traffic has tanked throughout the complete internet. Plenty of publishers conversation concerning "Google Zero," bracing for Google referral traffic to completely base out.

Reddit, equal alongside the agreement it cut alongside Google, is experiencing the fact that hunt traffic is uncomplicated come, uncomplicated go.

Huffman stated in a letter to shareholders stated that hunt traffic was "down meaningfully in Q3," and that in October it dropped by complete 1 myriad referrals per week on average, and if the trend continued, it could see "a low-double-digit percent from our current basis of 130 million" regular energetic distinctive visits.

It's not all bad news, though. Reddit reported $895 million, which was an addition of 53% year-over-year. Its concentration is on the logged-in person experience, which is additional lucrative for advertising, since users can be additional targeted. In the earnings call, Huffman noted that 80% of Reddit's monetization happens alongside app users and logged-in users.

There's item sad concerning Reddit becoming a semi-closed system; the end of an era of the open web — item that Reddit helped pioneer (and its co-founder Aaron Swartz was passionate about).

On Reddit, Huffman posted a message addressing the alter to users: "I don't cognize concerning you, but as person whose existence has been defined by the open internet, it's a big alter for me. But I've arrive to the decision that this is the correct decision for our phase and the correct decision for our business."

I never play with my kids at the playground. Other parents may think I'm lazy, but there's a good reason I sit back.

support@mycoding.id (Lauren Crosby Medlicott) — Fri, 30 Oct 2026 16:32:01 +0700

Jodie Lopez has continually wanted her kids to be independent. Courtesy of Jodie Lopez

This as-told-to composition is according to a conversation alongside Jodie Lopez. It has been edited for dimension and clarity.

When I archetypal became a mother, I knew I wanted my children to grow up to be independent, resilient, and prepared for existence in the genuine world.

Growing up, my mom wasn't about much. Although I didn't desire my children to awareness solitary as I frequently did, I did desire to continue on the independence I developed by doing things for myself. I have never been fearful to go out and do breathtaking things, and I wanted to raise children who could remain on their own two feet and obtain any existence power one day throw at them.

Before being their friend, it was most crucial to me that I was their mom, preparing them for the day they would eventually depart my care.

Having boys, I additionally hoped they would develop into men who would create fine housemates or partners one day. I've talked to them concerning the stereotypes surrounding men and housework, and I never wanted those stereotypes to rotate into true of them.

Tidying their bedrooms

Even as small toddlers and young children, the boys were expected to tidy up following themselves. If they got item out, they would put it away. If they forgot, I reminded them.

Their bedrooms are their responsibility, not mine. While I would assistance them, I would never merely clean their rooms for them.

Carrying their own backpacks

I've continually taken the boys out on little adventures. When they were tiny, I carried most of what we needed for the day, but they continually had small backpacks of their own, normally alongside a group of wipes and their own snacks.

By carrying their own snacks, they were capable to nourish themselves whenever they got hungry, listening to their bodies and responding to what they were telling them.

As they got older, I never carried their backpacks or academy belongings to and from school. I see parents carrying everything at the commencement or end of a academy day, but I've never done this.

When we go on vacations now, the boys transport backpacks complete of toys, clothes, and toiletries. They are liable for their own belongings.

Learning to assistance about the house

I've continually expected the boys to throw in and assistance about the home since that is merely part of living alongside another people. They don't get paid for this.

They obtain their own dishes to the sink. They keep their rooms clean. They tidy up following playing. They power do little, quick chores about the house.

But I additionally have a scheme anywhere they can acquire a small fee — up to concerning $1.50 — for doing jobs specified as cleaning the washroom or taking out the trash. For these jobs, they get paid twice as much if they notice the job needs doing and do it without being asked.

It's my way of raising boys who see a disorder and afterward do item concerning it.

I'll additionally recommendation several kind of fee if it is a job I would normally do myself, but merely don't have period for as a operating sole mom.

I don't perform at parks or gentle play

I have never hovered about the boys at parks or gentle perform centers, equal whenever they were little. I sit on a place or at a array and let them fig out what they are capable of.

I volition assistance whenever asked, but they cognize not to ask me to do things for them whenever they are capable of doing them themselves. I volition assist, support, or get prepared to capture them if they need me.

Jodie Lopez doesn't perform alongside her kids at the playground. Courtesy of Jodie Lopez

I desire them to study how to perform without me. My function in these contexts is to defender them — to create certain they are harmless — fairly than to be their playmate.

Parents have looked at me suspiciously whenever I remain rear during the kids play, perchance thinking I am a lazy parent.

But this isn't me being a lazy parent. It is an intentional decision to instruct them how to keep themselves safe, measure their capabilities, and perform without changeless grownup intervention.

That isn't to say I never perform alongside them. We perform many — fair not in these contexts.

They oversee their own display time

Both boys have set amounts of display time, but it is up to them to oversee it. After school, they have 30 minutes of display time. On weekends, they have two 30-minute lots, affirmative an additional 45 minutes whenever they perform on screens together.

Instead of me hovering complete them and checking how lengthy they have been playing, they set a timer themselves to control their playing time. This additionally minimizes arguments whenever display period finishes.

They are learning to oversee their own period and self-regulate their display use, fairly than relying on me to continually detect it for them.

Learning what they are capable of

After years of intentionally instruction independence, my children are expanding in confidence. They cognize what they are capable of.

Although I am extremely current in their lives and prepared to assistance and assistance them, they are additionally expanding into their own individuals in the world.

That, to me, is the entire point.

I don't desire to lift children who need me to do everything for them. I desire to lift children who cognize I am there whenever they need me, but who additionally cognize they are capable of doing so much for themselves.

10 Hacks for the Contacts App Every Apple User Should Know

support@mycoding.id (Pranay Parab) — Fri, 30 Oct 2026 16:30:34 +0700

Pranay Parab is an autonomous tech newsman based in Mumbai, India. He covers tech for Lifehacker, and specializes in tutorials and in-depth features.

The Contacts app is the bedrock of all my communication on my iPhone, and to a ample extent, additionally on my MacBook. On the surface, Contacts appears to be a essential app that stores names, numbers, and another things you desire to recall concerning group or businesses. However, it has several awesome features hidden under the surface, specified as the capability to quickly delete copy contacts, astute lists, and faster ways to bulk portion or delete contacts. Here are the 10 finest Contacts app hacks for iPhone, iPad, and Mac:

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Use this hidden hunt characteristic to delete copy contacts

Credit: Pranay Parab

If you have the identical figure or email location saved under multiple contacts, you can easily apparent these from your iPhone. iOS shows you a immediate at the top of the catalog of contacts that lets you eliminate copy contacts easily. The identical characteristic is hidden in the Mac type of Contacts. To try it, open Contacts on the Mac, and choose the Card list at the top of the screen. Then, click Look for Duplicates. This volition acknowledge copy contacts for you, and you can quickly merge or delete them.

Try the two-finger rub motion to choose multiple contacts

It's beautiful uncomplicated to choose multiple entries whenever you use the Contacts app on the Mac. You can clasp the Shift or Ctrl buttons and use arrow keys or click multiple contacts to choose them all. On your iPhone or iPad, this characteristic is accessible via a hidden gesture. You need to use two fingers and rub upwards or downwards on the catalog of contacts. Once you get the motion right, you'll be capable to choose multiple contacts quickly. After you choose one lot of contacts, you can scroll up or downward and use the identical motion to add additional contacts to your selection. This is the fastest way to execute bulk actions in your iPhone's Contacts app.

When you portion a contact, iOS shows you a immediate to choose the sectors you desire to send. This is awesome for privacy since you don't desire to dispatch your partner's residence address, birthdate, your anniversary, nicknames, or another individual particulars by default. However, this additional stage adds a small bit of conflict during sharing contacts. If you desire a faster way to dispatch a communication on your iPhone, you can copy and paste it in the Messages app. To try it, open the Contacts app and scroll till you see the contact's name. Hold the contact's name and media Copy. Open Messages, paste it in any chat, and dispatch it. Unfortunately, this doesn't activity alongside third-party messaging apps akin WhatsApp, but it's awesome for texts and iMessage.

Hold the communication clasp in a communication cardstock to toggle to a distinct messaging app

On your iPhone, you can use Contacts to communication group on WhatsApp, Signal, Telegram, or another apps. Just open a communication and clasp the messaging button. This volition disclose a catalog of apps anywhere you can ping that person. WhatsApp doesn't have admission to my contacts, which makes it a bit annoying to communication group I know. Since I started using the Contacts app to commencement chats on WhatsApp, the procedure of pinging new group has rotate into a lot faster.

Hold the call clasp to alter the app used to call a person

Just as you can use Contacts to communication group on third-party apps, you can additionally use it to call them on those apps. Go to any communication in the Contacts app on your iPhone, and clasp the call button. This volition let you call them on WhatsApp, Signal, or any another apps anywhere their phone figure is linked.

Delete a communication quickly by long-pressing its name

Credit: Pranay Parab

iOS makes it difficult to delete contacts quickly. This prevents unintended deletions, but it can be annoying whenever you fair desire to eliminate group who you final said to in elevated school. To speed this up, open Contacts on your iPhone and clasp any contact's name. In the popover menu, choose Delete to eliminate the contact. To eliminate multiple contacts quickly, use the two-finger rub motion to choose multiple contacts, and clasp any of the selected contacts. In the popover menu, you can choose Delete X Contacts, anywhere X is the figure of contacts you've selected.

Use the Mac app to export your contacts and rear them up offline

To export your complete location book, you can use the Contacts app on your Mac. Once you have it open, go to File > Export > Export vCard. This volition preserve all your contacts in a vcf file, and you can import that into Google Contacts or another apps or services. You additionally have the choice to export contacts as a PDF file. Just choose File > Export as PDF to get it done.

What do you think so far?

Remove sectors you don't use whenever adding new contacts on Mac

When you create a new communication on your Mac, the app shows multiple sectors that you may never use. If you fair need to preserve phone numbers and email addresses, you can delete all the another blank sectors from the template. To do this, open Contacts on your Mac, and go to Card > Add Field > Edit Template to add or eliminate sectors from the default communication template.

Use astute lists to display contacts on your Mac

Credit: Pranay Parab

If you added a figure recently, specified as a salesperson at a car dealership, but forgot their name, the Contacts app doesn't create it uncomplicated to discover the contact. Instead of scrolling through the complete catalog of contacts and trying to conjecture which one could be the individual you said to, you can use the Contacts app on your Mac to find them quickly. It lets you create astute lists to kind contacts by lately added. Open Contacts on your Mac, and go to File > New Smart List. Now choose Card in the archetypal drop-down menu, followed by has changed in for the second one. You can afterward add the figure of days, specified as 10 days, in the final field, and click OK. Click the newly created astute catalog in the remaining pane, and you'll see all contacts that were either created or updated in the final 10 days, which volition contain the hypothetical car salesperson.

Smart lists additionally authorize you to quickly create groups of connected contacts. For instance, I've saved all my erstwhile colleagues' particulars alongside the business name in the contact. To discover them all quickly, I created a astute catalog that groups all contacts alongside that company's name.

NameDrop is one of my favorite Apple features. It lets you bump two Apple devices together to toggle communication data quickly. Try holding your iPhone near another person's iPhone, and you'll see a full-screen pop-up asking if you desire to portion your communication alongside someone, or if you'd fair akin to obtain their communication information. To defend your privacy, you should bounds sending data to others. Updating your communication cardstock is the finest way to do this. Open the Contacts app on your iPhone, and tap your name up top. Hit the Edit clasp and eliminate data you don't desire to share. I propose updating your overview image too. Instead of sharing a candid photo, you can use an emoji or a expert headshot that you're comfortable sharing in public.

Pranay Parab is an autonomous tech newsman based in Mumbai, India. He covers tech for Lifehacker, and specializes in tutorials and in-depth features.

Shopify Now Lets Stores Pay The Company Behind Your AI Shopping Agent

support@mycoding.id (Slobodan Manic) — Fri, 30 Oct 2026 16:30:24 +0700

If I dispatch an delegate to buy item for me from the Shopify catalog, is it finding the finest imaginable merchandise for me, or the merchandise that volition create whoever is rearward the delegate the most money? As of Oct. 27, 2026, Shopify’s records gives the delegate a logic to activity for two others furthermore me: the business that built it, and Shop, Shopify’s app and website.

Shopify Pays The Company Behind An AI Agent A Commission On Promoted Products

Shopify mixes products that pay a commission into the hunt results its catalog gives AI agents. It calls them promoted placements. When a shopper buys one, Shopify pays the business rearward the delegate (Shopify calls it the developer) 0.3% of the order.

Stores can pay more. If a shop runs Shop Campaigns, Shopify’s paid promotion program, and turns on external platforms, Shopify turns the store’s run “into a commission” on top of the 0.3%. In hunt results, the total comes rear alongside the product, next to its price, rating, and assessment count. Shopify’s example shows 1.5% on one product.

The Extra Commission Pays Only When The Shopper Buys In Shop, Not On The Store’s Website

Shopify pays the store’s additional commission “only whenever the buyer completes the acquisition in Shop, either in the Shop mobile app or on shop.com.” For those products, the links the delegate gets item to shop.com, not to the store’s website. A transaction on the store’s website earns lone the 0.3%.

So the delegate has a logic to choice the merchandise that pays its developer more, and a logic to dispatch me to Shop to buy it. Shopify’s records doesn’t say whether a bigger commission additionally moves a merchandise up the list.

In my test, two Claude models went alongside the numbers they were given: at their default settings they picked a h2o flask listed alongside 447,221 reviews 84 times out of 100, whenever the store’s merchandise leaf showed 6,537. I haven’t tested a commission number. What an delegate does alongside one depends on its example and on what its developer tells it.

Shopify Asks Developers To Label Promoted Products, And Leaves The Wording To Them

Shopify asks developers to tag promoted products, to say they may acquire a commission, and to create that apparent “before buyers act on a promoted result.” It points to US FTC rules on paid relationships and to EU and UK rules on ads and sponsored content, and leaves the exact wording to the developer.

The FTC, EU, and U.K. rules were written for ads and paid recommendations. The FTC’s endorsement guides say a paid association rearward a advice have to be disclosed whenever group wouldn’t anticipate it. The closest EU regulation I established bans hunt results that conceal “payment specifically for achieving higher ranking” (Directive 2019/2161). An delegate picking one merchandise isn’t plainly a advice in the FTC’s awareness or a hunt outcome in the EU’s, and a commission on a transaction isn’t plainly fee for a higher ranking. I’m not a lawyer, and I cognize of no ruling either way.

Shopify Stores Can Wait, Because The Extra Commission Is US-Only And Still A Preview

Shopify calls promoted placements a Developer Preview, which developers associate from a waitlist, by invitation. The additional commission applies lone to products in an energetic U.S. campaign, in USD. Shopify’s records doesn’t name any developer that has joined. Developers exterior the program get average results, so I can’t see promoted products from the exterior either. Shopify says the particulars “are not final and power change”.

What I’d observe is whether Shopify says a bigger commission moves a merchandise up the list, and whether any delegate tells the shopper what it earns and anywhere it is sending them to buy.

More Resources:

This article was initially published on No Hacks.

Featured Image: tete_escape/Shutterstock

Category AI Search Ecommerce

Post-training 4B model with RL to fly Tesla Roadster 21% better than GPT-6 Astra

support@mycoding.id (Riki Setiawan) — Fri, 30 Oct 2026 16:27:16 +0700

Last Thursday (October 15), Tesla's new Roadster drove off a ramp that coiled complete until the car was upside down, rolled upright in the air and landed. It afterward used thrusters to hop complete a Cybertruck. Turns out the forthcoming does have flying cars.

The demo had already been pushed rear two weeks, "due to elevated winds" (Elon Musk on X). That made us wonder: alongside a tongue example in the pilot's seat, how would the car do in that wind?

We built an RL surroundings about a discipline simulator of a flying roadster to discover out, handed the controls to LLMs, and turned the breeze up. We let several of the latest finest models fly it: DeepSeek V4.1 Flash, Meta's Muse Spark Open, Reflection's Beam 1.0, NVIDIA's Nemotron 3.5 Super VL, TypeSafe's Jev 1.14, and equal OpenAI's GPT-6 Astra.

Asked for decisions in genuine time, these models wrecked nearly all flight: most obtain 1 to 6 s to answer, and the car needs a new act all 0.2 s. When we paused the earth so the models could think as lengthy as they wanted, they motionless misplaced to a 4B example we trained alongside RL in a storm.

Storm, 33 m/s wind: DeepSeek, alongside unlimited period to think, comes downward leaning and hits the highway alongside its body. Our RL-trained 4B lands level.

TL;DR

We built an RL surroundings about a discipline simulator of a flying roadster alongside four air thrusters, gusty breeze and the reveal's two stunts: a ramp flip and a kickflip complete a Cybertruck. An LLM flies it alongside one command all 0.2 s during the car keeps moving.
The latest open models can't fly it in genuine time. DeepSeek V4.1 Flash, Nemotron 3.5 Super, Muse Spark Open and Beam 1.0 obtain 1 to 6 s per decision and district 0% of kickflips and 3% or small of ramp flips. GPT-6 Astra additionally lands 0% on the clock.
RL post-training made a 4B example our finest pilot. Qwen3-4B, trained for concerning $13, answers in 0.09 s and lands 90% of kickflips in genuine time. With the earth paused for the example to think, the finest open model, DeepSeek V4.1 Flash, lands 87% and the another open models district 58 to 62%. Even GPT-6 Astra lands lone 74%.
Everything is open source, and you can fly your own example without a GPU (Try it).

Storm kickflips, 384 held-out flights per model. Open circles are runs alongside unlimited period to think. In genuine time, DeepSeek, GPT-6 Astra, Muse, Nemotron and Beam district 0%, and the RL-trained 4B lands 90%.

Watch how the models fly the car. Pick a stunt, a breeze flat and a example below to replay the identical escape on a held-out scene. The full page additionally shows the aviator decision all 0.2 seconds, the telemetry the example saw, and how lengthy all answer took.

Four air thrusters lift the car, and shove it downward whenever it's upside down

The car is a rigid body, 4.5 m lengthy and 2,000 kg dry, simulated at 500 Hz. Lift comes from four cold-gas thrusters at the corners of the flat of the car. Each thruster is fine for 12 kN, fed from one container of compressed air (110 to 170 kg per flight). They shove direct out of the floor. If the remaining brace fires harder, the car rolls, and if the forefront brace fires harder, it pitches.

When the car is upside down, the identical thrusters shove it toward the ground, and that is what makes the two stunts hard.

A car falling flat or sideways catches far additional wind

A car is built to move nose first. When it falls flat, or the breeze hits it from the side, it shows five to nine times as much area to the air, so the breeze pushes it about far more. Near the highway the breeze is weaker, and gusts arrive on top of the average. Each escape gets a average breeze from a random direction, in one of three bands: ray (up to 14 m/s), gale (14 to 24 m/s) or storm (24 to 33 m/s).

The wheels can obtain a 4 m drop, but the rooftop can't contact the ground

The car can contact the dirt alongside its four sprung wheels or alongside its body. It counts as a collision when:

Two stunts from the reveal: a ramp flip and a kickflip complete a Cybertruck

In the ramp flip, a ramp curls complete and the car leaves the phase upside downward 10 to 14 m up, afterward has to rotate upright and land. In the kickflip, the car comes in at 50 to 94 km/h, clears a parked Cybertruck, rolls a complete 360 degrees and lands.

A escape succeeds lone if the car ends up on all four wheels on the 14 m road, inside concerning 20 degrees of level, no longer spinning, and without a crash. Every project randomizes the speed, the air in the tank, the breeze and gusts, and the ramp size or truck position. The held-out tasks use seeds that no example trained on.

What the example sees, and what it sends back

At the commencement of all flight, the example gets a briefing. It describes the car, the collision rules and the five commands it can send, and afterward the task. Here is the project part of the briefing for one held-out storm flight:

After that, all 0.2 s of simulated time, the example gets one row of telemetry and replies alongside one JSON object. Here is the row our trained Qwen 4B example saw 1.2 s into that flight, during it was upside downward complete the truck:

The example replied {"mode": "rotate", "axis": "roll", "to": 360.0, "lift": 1.0} in 0.15 s, which kept the rotate going. The entire escape took 19 replies:

The truck part of all row additionally gives the period until the car reaches the truck and the period until it's former it, at the current speed, so the example doesn't have to do that division itself. Every LLM in this article sees the identical lines, and the hand-written aviator below says the identical numbers.

The five commands are shoreline (all thrusters off), ascend (stay flat at a stated vertical speed), clasp (hold a stated rotate and pitch), rotate (spin concerning one axis to a total angle, braking to halt on it) and district (level out and arrive downward softly). The example picks one command, alongside its numbers, in all reply. A escape device afterward turns that command into drive for all of the four thrusters, 50 times a second, until the next answer arrives.

The car doesn't halt during the example thinks

If a example takes 2 s to answer, the car flies ten 0.2 s intervals on the old command before the new one takes over. We period all answer end to end. Only the archetypal decision is untimed, akin a scheme made before takeoff.

We picked 0.2 s since the kickflip's rotate takes concerning a second and has to commencement inside a few tenths of a second of the correct moment. With one second between decisions, no aviator could period it, whether example or script. To distinct judgement from speed, we additionally fly all example a second way, alongside the simulator paused until all answer arrives, so the example has unlimited period to think.

Half the reward is for a spotless landing

For RL the reward runs from 0 to 1. It gives partial credit for height, clearing the truck, rotation and touchdown quality, afterward 0.4 for a prosperous landing and 0.1 for a spotless complete (soft, alongside air left, centered on the road).

A aviator written by hand shows that the two stunts can be flown

Before training anything, we wanted to cognize that the two stunts can be flown alongside these five commands. So we wrote a aviator by hand: a few dozen lines of if-then rules that peruse the identical telemetry and dispatch commands through the identical 0.2 s interface. On the kickflip, for example, it starts climbing whenever the truck is 1.1 s away, starts the rotate formerly the car is 1.4 m complete the truck's roof, leans against any sideways drift, and lands formerly the car is former the truck.

The hand-written aviator answers immediately and sees the identical inputs to the LLMs. It lands all light-wind ramp flip and 98% of light-wind kickflips, but lone 61% of kickflips in a storm. We call it the scripted pilot in the remainder of this post.

The scripted aviator flying the two stunts in ray wind.

The latest open models can't fly in genuine period #

We flew four open models (DeepSeek V4.1 Flash, Muse Spark Open, Nemotron 3.5 Super and Beam 1.0), GPT-6 Astra in storms, and Jev 1.14, a example built for accelerated decisions that picks from a list of commands alternatively of penning JSON. Every example flies the identical held-out flights as our trained pilot: 192 per stunt in ray breeze and in a gale, and 384 in a storm. All runs use heat 0 and all model's default reasoning setting. We called the open models through OpenRouter, alongside Nemotron, Muse and Beam all pinned to one provider.

With period to think, the models create fine calls

When the simulator waits for all reply, the four open models fly the kickflip fine in ray wind. DeepSeek V4.1 Flash lands 98%, and Muse, Nemotron and Beam district 72 to 82%.

Wind makes it harder equal then. In a storm, DeepSeek drops to 87%, Muse to 62%, Nemotron to 60% and Beam to 58%. GPT-6 Astra lands 74% of storm kickflips.

On a operating clock, they district 0% of kickflips

With the car moving, all four open models district 0% of kickflips. Their median decision takes 1 to 6 s, so a representative command arrives 5 to 29 intervals following it was needed. In the real-time runs, alongside 16 flights in parallel, replies were slower motionless (DeepSeek's median was 2 to 3 s).

GPT-6 Astra takes concerning 2 s per decision and lands none of its 768 storm flights in genuine time. On the identical clock, our trained 4B lands 90% of storm kickflips.

DeepSeek V4.1 Flash on the identical flight, twice. On the remaining the simulator waits for all reply, and the car lands. On the correct the clock keeps running, the replies attain late, and the car crashes.

Answering faster doesn't fix it

In our archetypal round, alongside reasoning off, DeepSeek answered in 0.3 s but made worse calls, and Muse and Beam at low attempt motionless took concerning 2 s per decision. Jev answers in concerning 0.17 s, accelerated adequate for the clock, but it lands lone 2% of storm kickflips live. A aviator has to answer accelerated and create fine calls.

Median decision period against storm kickflip success. Jev and the RL-trained 4B the two answer inner 0.2 s, and lone the 4B lands most flights (90%).

The car leaves the phase upside downward 10 to 14 m up, and a uncomplicated scheme works: rotate upright, lean against the wind, afterward brake and land. With the simulator paused, the big models fly it. Muse lands 88 to 97%, DeepSeek concerning 80%, and GPT-6 Astra 383 of 384 storm flights.

On the clock, none of them gets former 3%. The archetypal command is normally a rotate upright, which is correct, but the autumn takes under 2 s, and the next answer comes following the car has already hit the road.

A ramp flip in genuine time. DeepSeek's archetypal command, rotate upright, is correct, but its next answer arrives following the car has hit the road. On the right, the trained 4B answers all 0.2 s and lands.

Muse, Beam and Nemotron district 1% or small in genuine time.

The untrained Qwen3-4B answers in 0.07 s and lands 85 to 100% of ramp flips, but it never lands a kickflip. Like Jev, it's accelerated adequate for the clock. Unlike Jev, it's a example we can train, so it's anywhere we started.

Post-training a Qwen3-4B aviator #

We started from Qwen3-4B-Instruct-2507 alongside a rank-64 LoRA (small add-on weights that train during the basis example stays frozen). The training code is SkyRL, an open-source RL library. The final example took concerning 4 GPU-hours of training, or $13.

A heated start, afterward 60 steps of RL

Training has two stages:

Warm commencement (2 hours 20 minutes): supervised fine-tuning on flights that landed: 64 scripted light-wind flights per stunt, affirmative 350 gale and storm kickflips that DeepSeek V4.1 Flash landed on training seeds alongside the simulator paused. We train one epoch, alongside the defeat lone on the pilot's replies. Most of the period goes to moving optimizer province off the GPU, so that the example fits in GPU memory.
RL (1 hr 35 minutes): GRPO flies the identical project multiple times and pushes the example toward the attempts that attack the collection average. Each of the 60 steps flies 16 tasks, 8 flights each, throughout all three breeze levels. Every 0.2 s decision is one conversation turn, and the reward is for the entire flight. The trainer shares the GPU alongside the vLLM server that flies the model.

We preserve a checkpoint all 5 steps, choice one using distinct validation seeds only, and afterward fly the held-out seeds once. The formula itself came out of many rounds of experiments scored on validation seeds, and we held the test seeds rear for this one final run.

The RL-trained 4B landing a storm kickflip in genuine time.

The remainder of this division is how we got to that recipe.

Why RL solitary never learned the kickflip

The archetypal run, RL from the untrained model, picked up the ramp flip in 10 steps. The kickflip reward started at 0.07 and stayed there. Of 68 kickflip decisions, 66 were a roll, and 21 of 22 archetypal moves rolled at t=0 alongside the wheels motionless on the road, which puts the car on its roof.

All 8 flights in a collection wrecked the identical way and got the identical reward. GRPO learns by comparing samples inside a group, so whenever they're all the identical it has nothing to go on.

The identical light-wind escape before and following training. Untrained, Qwen3-4B starts the rotate alongside its wheels on the highway and tips onto its roof. After imitation and RL, it climbs archetypal and afterward rolls.

We tried two cheap fixes. First, we added a row to the briefing saying that rolling on the highway tips the car over. The beginning move became a rotate alongside maximum lift, which motionless ended on the roof.

Second, we started fractional the custom flights partway through, following the scripted aviator had flown the beginning (a reverse curriculum, borrowed from robotics). Training achievement rosy to concerning 70%, but held-out achievement from t=0 stayed at zero, since the example lone learned to complete a flip that the scripted aviator had started.

The heated commencement used two teachers, all in the breeze it flew best

The heated commencement is what worked, and most LLM RL recipes commencement alongside one anyway. The difficult part was choosing what to imitate, since neither aviator we had was fine in all wind:

The scripted aviator is fine in ray breeze and bad in storms (61% of storm kickflips).
DeepSeek alongside unlimited period is fine in storms, but it takes concerning a second per decision, too dilatory to fly the car live.

So the heated commencement copies the scripted pilot's light-wind flights and DeepSeek's landed gale and storm flights. On its own, the heated commencement already lands 97%, 93% and 84% of held-out kickflips in ray wind, gale and storm, which is near to DeepSeek apart from in storms.

RL improves additional on what the teachers taught

RL starts from what the heated commencement copied, afterward practices anywhere the teachers were weakest. Two choices in its training mix came from study unsuccessful flights:

Storm counts double. Storms are anywhere the reward is hardest to earn, so the training mix has twice as many storm flights as ray or gale.
Practice the dilatory approaches. An before example misplaced to DeepSeek in ray breeze on one benevolent of flight: a dilatory car (14 to 16 m/s) alongside the truck concerning 3 s away. It sent district at the identical instant it continually did, concerning 1.8 s in, and came downward on the truck. On the identical flights, DeepSeek held its height until the telemetry stated it was former the truck, afterward landed. In the final run, fractional of the training kickflips are these slow, far-truck cases, so RL has to study to wait.

Kickflip. Share of held-out test flights that land, alongside the figure landed in brackets. There are 192 flights per breeze flat in ray breeze and gale and 384 in a storm, and all row flies the identical tasks.

The trained aviator answers in 0.09 s (served by vLLM, one escape at a time), inner the 0.2 s interval, so none of its commands attain late. Every escape ends the identical way whether the simulator runs in genuine period or waits for it.

RL's part shows up in the storm. The identical example following imitation lone lands 322 of the 384 storm flights, and following RL it lands 347. Flight by flight, 26 storm tasks district lone following RL and 1 lone without it (exact paired test, p < 0.000001). In ray breeze and gale the heated commencement was already close, and RL moves them by a few flights either way.

Against DeepSeek alongside unlimited period to think, escape by escape on the identical tasks:

Gale: 13 flights lone the 4B landed, 1 lone DeepSeek (exact paired test, p = 0.002).
Storm: 29 to 16 (p = 0.07). The 4B is ahead, but p is complete the 0.05 threshold we set before operating the test, so we don't figure the storm guide as significant.
Light wind: 2 to 6 (p = 0.29). DeepSeek is a few flights better, and so is the scripted aviator (188 to 185).

Against GPT-6 Astra alongside unlimited time, on all 384 storm kickflips, the 4B is plainly ahead: it lands 347 to Astra's 286, or 21% more. 70 district lone for the 4B and 9 lone for Astra (exact paired test, p < 0.001). On the storm ramp, Astra is slightly ahead, 8 flights to 1 (p = 0.04).

RL runs vary. Rerunning the identical formula landed 85 to 92 of 96 validation storm flights, and the run we kept was the finest of them. A rerun would most apt district concerning as many storm kickflips as DeepSeek.

Ramp flip. Same test set and sizes as the kickflip table.

On the ramp, imitation does most of the work. After imitation solitary the 4B already flies it nearly exactly akin the scripted pilot, and RL adds a small on top. 7 storm ramps district lone following RL and none lone without it (p = 0.02), and 8 district anywhere the scripted aviator fails, alongside none the another way.

The stronger the wind, the bigger the 4B's lead

Kickflip achievement by breeze flat for the scripted pilot, DeepSeek alongside unlimited period to think, and the RL-trained 4B.

The scripted aviator is nearly ideal in ray breeze and drops sharply in a storm, from 98% to 61%. DeepSeek holds up better, from 98% to 87%, but needs concerning a second per decision.

The trained 4B goes from 96% to 90%. It loses a small to the two teachers in ray breeze and strikes the two formerly the breeze picks up. Choosing the teachers by breeze flat got it most of the way there. The heated commencement solitary lands 84% in storms, and RL takes it to 90%.

The identical storm flight, flown by the scripted aviator (left) and the RL-trained 4B (right). The scripted pilot's build hits the highway before its wheels do, and the 4B touches downward on its wheels.

The unsuccessful flights appearance different, too. In storms, 34 of DeepSeek's 50 unsuccessful flights end alongside the car's build hitting the highway before its wheels. 23 of the trained 4B's 37 end in a flat landing fair off the 14 m road.

Among storm flights that land, the 4B's are a small shorter than DeepSeek's (3.6 s against 3.9 s, median) and complete alongside additional air in the container (24% against 18%), so it has drive remaining to resolve the car. We didn't reward abbreviated flights directly. The reward pays for a soft, centered landing alongside air left, and RL established shorter flights on its own.

How far the car leans on the way down, DeepSeek against the trained 4B on the identical storm flight. DeepSeek is motionless leaning concerning 20° into the breeze whenever its build hits the road.

Lessons learned #

1. The simulator must grasp realistic scenarios

We scored all example twice on the identical flights, and the ranking flipped. With the simulator paused, DeepSeek V4.1 Flash was the finest kickflip aviator we tested. With the car moving, it landed nothing.

Most LLM benchmarks provision the example as much period as it needs to answer, fair akin our paused runs. If your example has to act during the earth keeps moving, akin a conveyance or a sound agent, the period it takes to decide is part of the score, so measure how accelerated it decides alongside alongside how well.

2. DeepSeek attack bigger models during operating small parameters per token

With unlimited period to think, DeepSeek V4.1 Flash attack all another open example we tested by a broad margin: 98% of kickflips in ray breeze and 87% in a storm, against 72 to 82% and 58 to 62% for the rest. It runs lone 16B of its 552B parameters per output token. That is the fewest of the collection apart from Nemotron 3.5 Super (12B of 120B), and fine under Muse Spark Open (42B of 816B) and Beam 1.0 (23B of 501B). The finest aviator of all was smaller still, a compact 4B following RL. On a project this narrow, how a example was trained mattered additional than how many of its parameters run per token.

3. RL improved the 4B example beyond its teachers

The heated commencement copied two teachers, all fine in a distinct breeze setting. After RL, on the identical held-out flights, the 4B example strikes the scripted aviator by 30 points in storms, strikes DeepSeek in gales, and is slightly onward of it in storms. It doesn't attack either instructor in ray wind, anywhere the two were already near perfect.

Imitation brought the 4B up to the teachers' level, and RL on the genuine goal moved it former them anywhere there was area to improve. In storms that was 25 additional landings out of 384 than the heated commencement alone, alongside lone 1 escape going the another way.

4. GRPO needs attempts that differ at the difficult decision

Our archetypal runs unsuccessful for a logic that's uncomplicated to miss. GRPO compares a collection of attempts at the identical task. When all eight collision the identical way, they all get the identical reward, and the example has nothing to study from. Starting custom partway through the escape raised training achievement to 70% and remaining held-out achievement at zero, since the example never practiced the beginning move, which was the difficult part. A abbreviated heated commencement fixed it by making the attempts differ at that decision.

Obviously, this says nothing concerning flying a genuine car. A genuine car would use a accepted controller, and equal our scripted aviator decides instantly, which no LLM does.

It additionally isn't how a robotics squad would build this pilot. Hierarchical systems akin Figure's Helix run a 7B vision-language example at 7 to 9 Hz on top of an 80M-parameter guideline at 200 Hz. The ample example chooses what to do, and the small guideline turns that into motor commands 200 times a second. Our stack has the identical two layers, alongside a 50 Hz escape device holding outlook and vertical speed underneath the LLM, but our accelerated tier is scripted and makes no decisions.

We deliberately remaining the one timing-sensitive decision, whenever to commencement the roll, to the tongue model, since we wanted to cognize whether an LLM can create that call against a clock. We haven't trained a traditional controller guideline (for example, PPO alongside a small network) on the simulator, and we'd anticipate one to district nearly everything.

The RL surroundings and all conveyance indicator in it are our own assumptions, and it's one surroundings alongside two stunts. Held-out method unseen seeds (wind, speeds, ramp and truck placement) of the identical two stunts, not new stunts. DeepSeek's storm flights were part of the heated start, so in storms the 4B is compared alongside a example whose flights it learned from.

Using SkyPilot for RL training #

The final example took concerning 4 GPU-hours (2 h 20 min of heated start, 1 h 35 min of RL), approximately $13 (at ~$3.39/h per H100). Finding the formula took many additional runs. We ran all training run and all evaluation as a SkyPilot managed job, up to six at a time, and SkyPilot established a liberated GPU for all one. When a collection node went bad mid-run, SkyPilot reported the stuck jobs and we relaunched them on another nodes.

Training, rollouts and evals run flank by flank as one Job Group

An RL run does three things at once. It updates the model, it generates rollouts alongside the latest weights, and it scores checkpoints. A SkyPilot Job Group launches these as one managed job, alongside all part on its own hardware:

The trainer runs GRPO on its own H100 and writes new LoRA weights all stage to a quantity it shares alongside the conclusion server.
The inference server runs vLLM on another H100 and generates the rollouts alongside those weights.
An eval watcher starts an evaluation for all new checkpoint. Each evaluation gets its own GPU, runs alongside training, and joins the identical Job Group as one additional task.

One job, all operating at once: the trainer, the conclusion server, the eval watcher, and the step-5 eval it launched (marked Dynamic).

The numbers in this article arrive from the identical formula run as distinct training and evaluation jobs. The Job Group type is train_eval.yaml in the repo. For all evaluation, vLLM serves the checkpoint and tools/pilot_bench.py flies it complete the OpenAI-compatible API, the identical code way as all another example in the benchmark.

SkyPilot is open origin (pip instal skypilot) and everything complete runs on it. The RL environment, prompts and SkyPilot records are in the flying-roadster-rl example in the SkyPilot repo.

Fly your own model. The benchmark talks to any OpenAI-compatible endpoint and defaults to SkyPilot Tokens, which serves DeepSeek V4.1 Flash, Muse Spark Open and another open models. Create an document there for an API key, copy the repo, cd llm/flying-roadster-rl, and run:

Drop --realtime to provision the example unlimited period to think. --endpoint openrouter uses $OPENROUTER_API_KEY instead. For a local server or any another OpenAI-compatible API, continue --base-url (and --api-key-env if the key lives in another variable). A local server needs no key.

To train your own pilot, alongside checkpoints evaluated as they land, initiate the Job Group. You'll need a Kubernetes collection alongside two liberated H100s and a shared volume, affirmative an S3 bucket:

Without a shared volume, train.yaml and eval.yaml run training and evaluation as distinct jobs.

If you have questions or a baseline we should add, open an matter on the repo. If you desire assistance post-training a example on your own task, talk to us.

ICE wants its mask back, and hired a company to ask

support@mycoding.id (Riki Setiawan) — Fri, 30 Oct 2026 16:26:58 +0700

We obtain takedown notices regularly. They arrive from individuals, lawyers, companies, and governments. This article is part of a sequence anywhere we document how we grip them, the two the regular cases and those that disclose item value discussing publicly.

This request, to obtain downward icepi.cx (now online again at http://icepicx.is/ ) arrived from a business we have no association with, acting for a authorities agency in a nation anywhere we do not operate.

We declined the request.

What happened

The notice describes a doxxing campaign. That is not what the location is.

Doxxing publishes personal particulars concerning personal group so that others can discover them at home. Icepick publishes activity identities of authorities employees. Who they activity for. What their function is. How they can be reached in that role. The data describes group in the exercise of community authority, not in their personal lives. Federal officers carrying out an implementation program are not personal individuals during they are carrying it out. The community has a lawful involvement in knowing who is doing that work, under whose authority, and in which office. Journalists cannot study on an agency whose personnel are structurally unknowable.

We are not pretending the base of the data is comfortable. It came from a breach, and nobody in the dataset chose to be in it. The inquiry we had to answer was narrower: does publishing it assist a intent that a hosting provider should protect? We concluded that it does. The location functions as a citation tool for accountability reporting by journalists and citizens, and that is a use we be to keep online. This is why we declined the take-down request.

Why this matters

An automated takedown notice does not eliminate the activity of checking whether an allegation is true. It moves that activity to the recipient. We made that item concerning a false allegation from a German constabulary authority, and it holds current alongside a distinct agency, a distinct country, and a distinct benevolent of claim.

ZeroFox finds applicant matter through AI-driven detection. Whether a stated location is accountability reporting or a harassment run is exactly the judgement that finding cannot make. Someone has to peruse the site, appearance at the dataset, and measure community involvement against individual hazard and this dawn that person was us.

This case adds item to that. The gathering accusing us and the gathering contacting us are no longer the same. We cannot see who inner ICE decided this location should go, whether anyone did, or what they were shown before deciding. We are being asked to validate a assertion whose author we cannot identify.

As a endeavor model, none of this is new. Copyright has worked this way for decades. A personal business sells monitoring to entitlements holders, scrapes for matches, sends petition alphabet automatically, and takes a portion of any recipients pay to create the alphabet stop. Volume is the product. Checking is a disbursal against it. Plenty has been written concerning what that does to lawful speech, and most of it transfers to what arrived in our inbox this morning.

What has changed is the client. In this case its a governmental institution, not a personal company. DHS signed a $15 myriad agreement alongside ZeroFox in July 2026 covering ICE and Homeland Security Investigations, and the business can document on the department’s behalf until 2028. The Intercept reported on a leaked memo describing the program internally as a “Doxing Mitigation Initiative,” and quoted an ICE authoritative who concerned it could be turned on whistleblowers and critics inner the agency fairly than on threats from exterior it. ZeroFox additionally has form. In 2015 it classified peaceful Black Lives Matter organisers in Baltimore as “threat actors” warranting uninterrupted monitoring, partially on the power of their follower counts. The FBI hired the business anyway in 2021.

Validation by the recipient is no longer a flank consequence of a seriously built process. It is part of what the assistance sells. Finding politically and journalistically applicable data is the product, removing it is the deliverable, and the figure of notices submitted is the measure of success.

What happened to the site?

By mid-morning, icepi.cx no longer resolved. Its registrar, CentralNic, had placed the domain on serverHold.

Our refusal kept nothing online. The petition that decided the outcome to obtain the location downward was not the one sent to us. A registrar reached the contrary decision the identical morning, published nothing, and a earth spectators misplaced admission to the site. In the meantime the location is online again under a domain from a distinct registrar (http://icepicx.is/)

What have to be done concerning this

As we depict in our former article, law akin the DSA loads obligations onto hosting providers and asks nothing of the group who document notices.
This case demonstrates what can happen formerly filing becomes a business assistance accessible to governmental organisations.

Anyone filing a takedown notice on another party’s behalf should have to province who they act for, under what lawful basis, and who is accountable if the assertion is wrong. Where a notice was produced by automated detection, that have to be declared on its face. A provider cannot measure a assertion correctly without knowing whether a individual always looked at it.

Removals at the register and registrar flat need the the identical scrutiny.
Enforcement against genuinely harmful satisfied is a lawful goal, and protecting individuals from harassment is a genuine one. But a scheme anywhere an agency can buy removals through a contractor, anywhere the contractor is perchance paid by volume, and anywhere the quickest path runs through infrastructure nobody is watching, akin the registrar in this case is not a scheme for stopping harassment. It is a scheme for making inconvenient data disappear.

What others compose concerning this case

https://subscriber.politicopro.com/article/2026/10/ice-dhs-leak-takedown-request-01140645

I went to Shake Shack, Five Guys, and Smashburger with a $20 budget. One chain offered the best food and the most value.

support@mycoding.id (Amanda Shammas) — Fri, 30 Oct 2026 16:25:21 +0700

I compared $20 meals at burger chains akin Five Guys to discover the finest value. Amanda Shammas

Fast food has lengthy been considered a convenient, affordable meal option, but as the cost of food continues to rise, equal a uncomplicated command of burger and fries can quickly method $20.

I wanted to discover out how far that prosperity would extend at several of the country's most recognizable fast-casual burger chains — and whether any of the meals would really awareness value the price. So, inside the identical week, I visited Shake Shack, Five Guys, and Smashburger.

I ordered a akin meal at all eatery and compared the taste, part sizes, and general value. Here's how it went.

Shake Shack was my archetypal stop.

A Shake Shack location lately opened near my house. Amanda Shammas

Unlike the another two chains I visited, Shake Shack is a publically traded company. It began as a hot-dog cart in New York City's Madison Square Park before becoming a imperishable booth in 2004.

Today, the sequence has complete 700 locations about the world. One lately opened near my house, so it seemed akin the ideal period to provision it a try.

The ShackBurger was uncomplicated but satisfying.

The burger was lean and crispy. Amanda Shammas

I ordered a sole ShackBurger ($7.79), which came alongside an Angus beef patty, American cheese, lettuce, tomato, and the chain's signature ShackSauce.

The patty was cooked fine and had a nice sear, alongside thin, crispy edges. The dairy merchandise was additionally absolutely melted complete the top.

I particularly enjoyed the ShackSauce, which was creamy and tangy, and tasted akin a blend of ketchup, mustard, and mayonnaise.

The crinkle-cut fries were crispy and fine salted.

I really enjoyed the crinkle-cut fries. Amanda Shammas

As a side, I ordered the fries ($4.99). These were crinkle-cut, nicely salted, and crispy on the outside.

I normally favor very lean fries, but these had a satisfying crunch that won me complete and paired fine alongside the burger.

I had adequate remaining in my prosperity to add a vanilla shake.

I desire the vanilla tremble had been a bit thicker. Amanda Shammas

For dessert, I ordered a vanilla shake ($6.49). Although it had a pleasant, traditional vanilla flavor, the consistency was thinner and additional watery than I would have liked. To me, it seemed slightly overmixed.

Overall, I idea this was a firm meal for the price.

In total, my meal disbursal $19.27 before tax and tip. Amanda Shammas

My burger, fries, and tremble disbursal $19.27 before tax and tip. The meal wasn't particularly inventive, but everything tasted great, and I got a nice part alongside dessert during staying inside my budget.

Next, I visited Five Guys.

This was my archetypal period visiting Five Guys. Amanda Shammas

Although Five Guys is now a earth chain, it remains a family-owned business. Jerry and Janie Murrell opened the archetypal eatery in Arlington, Virginia, in 1986.

Today, the eatery has concerning 1,900 locations worldwide, including about 1,500 in the US.

Despite its popularity, I had never eaten there before, so I was inquisitive to see how far my $20 would stretch.

My burger was entirely customizable.

I liked that I could as as many toppings as I wanted to the burger. Amanda Shammas

Unlike Shake Shack, Five Guys didn't assist its burgers alongside a norm set of toppings. Instead, I was instructed to build my own from a lengthy catalog of included options.

I ordered a Little Cheeseburger ($9.25), which came alongside one beef patty, and I added lettuce, tomato, pickles, and ketchup. It arrived tightly wrapped in foil, which remaining it slightly squished.

The patty had lightly crispy edges, and I liked how the dairy merchandise melted into the meat. However, of the burgers I tried, this one reminded me the most of traditional accelerated food.

I couldn't fairly pinpoint what created the acquainted taste, but I think it was the blend of the salty, umami beef and the bun's minor sweetness.

In my opinion, the sensation was reminiscent of item I'd get at McDonald's, which made the higher cost harder to justify.

The small fries came in an enormous portion.

I could see the grease on the bag the fries came in. Amanda Shammas

I additionally ordered a Little Fry ($5.30), which arrived in a brown document bag visibly stained alongside grease. According to the Five Guys website, this is since the fries are soaked in h2o and assimilate small oil whenever cooked.

Despite being the smallest size on the menu, the part was massive. Adding an additional assisting of fries to all bag has been a Five Guys tradition since the sequence opened. This explained the amazingly ample serving and made the cost awareness akin a improved value.

They tasted good, but much of their sensation came from how oily they were. I could see myself enjoying them as a late-night indulgence, but they were greasy adequate that I concerned dining too many would provision me a stomachache.

The higher prices remaining no area in my prosperity for a shake.

I ordered a Diet Coke alongside my meal. Amanda Shammas

Because the burger and fries disbursal additional than they did at Shake Shack, I couldn't fit a milkshake into my $20 budget. Instead, I ordered a Diet Coke ($3.30), bringing my total to $17.85 before tax and tip.

Although I spent small at Five Guys overall, I additionally received small assortment for my money.

Lastly, I made my way to Smashburger.

It had been a during since I dined at Smashburger. Amanda Shammas

Founded in Denver in 2007, Smashburger is owned by Jollibee Group, the Philippine-based eatery business whose portfolio additionally includes Jollibee and The Coffee Bean & Tea Leaf.

Smashburger's online directory currently lists 158 open and upcoming locations in the US, and four in Canada, making it the smallest of the three chains I visited.

I had eaten current before, but it had been years since my final visit, and I had small recollection of my experience.

In my opinion, this burger tasted the freshest of the three, and the fries were delicious.

I was impressed by the burger and fries from Smashburger. Amanda Shammas

I ordered a sole Classic Smash ($7.89), which came alongside an Angus beef patty, American cheese, lettuce, tomatoes, red onions, pickles, ketchup, and signature Smash Sauce.

I appreciated that all of my preferred toppings came standard, so I didn't have to customize anything. I additionally loved the supplement of a signature sauce, which was creamy and tangy and gave the burger another tier of flavor.

The beef itself tasted particularly fresh, alongside a clean, pronounced sensation that wasn't too salty or greasy. The patty could have had additional pronounced lacy edges, but the seared crust motionless added a slightly charred finish. The dairy merchandise was nicely melted, and the soft, pillowy bun reminded me of a murphy roll.

I paired my burger alongside the SmashFries ($4.19), which were thin, shoestring-style fries tossed in a blend of rosemary, garlic, and oliva oil.

I had adequate remaining in my prosperity to add on a vanilla shake.

The vanilla tremble from Smashburger was delicious. Amanda Shammas

To circular out my meal, I ordered a vanilla milkshake ($6.49). It was noticeably thicker than the one I received at Shake Shack and came alongside a spoon.

It had a creamy, milky flavor, but alternatively tasted akin fairly norm vanilla ice cream. It wasn't particularly memorable, but I enjoyed the consistency.

My burger, fries, and tremble disbursal $18.57 before tax and tip, allowing me to get a complete meal alongside dessert during staying comfortably inside my budget.

Overall, I idea my meal from Smashburger offered the finest blend of sensation and value.

I was most impressed by my meal from Smashburger. Amanda Shammas

Before tax and tip, I spent $19.27 at Shake Shack, $17.85 at Five Guys, and $18.57 at Smashburger.

Shake Shack gave me a complete meal alongside dessert inside my budget. Nothing stood out as particularly memorable, but it felt akin a solid, dependable choice at a sensible price.

Five Guys had the lowest total and provided by far the most fries. However, its additional costly burger remaining no area in my prosperity for a shake, and the greasy fries and norm burger didn't awareness value the price. Although I spent small overall, I felt akin I received the smallest assortment for my money.

For $0.70 small than Shake Shack, Smashburger gave me a burger, fries, and a thicker milkshake. Its burger tasted the freshest, and the thin, rosemary-seasoned fries were effortlessly my favorite.

Ultimately, Smashburger made my $20 extend the furthest without sacrificing taste. It offered the finest meal, the most distinctive flavors, and the strongest general value.

Business Insider reached out to Shake Shack, Five Guys, and Smashburger for comment.

ChatGPT Gets Wider Ads, Multi-Image Ads Expands, Expansion & More

support@mycoding.id (Barry@Rustybrick.com (Barry Schwartz)) — Fri, 30 Oct 2026 16:17:00 +0700

OpenAI fair sent its weekly email update to advertisers announcing the ChatGPT Ads are live in 26 additional countries, a new wider norm ad component format, Multi-image ads are now accessible in open beta to all advertisers, Shopify integration is now accessible internationally and Shopify integration is now accessible internationally.

Wider Ad Unit

ChatGPT Ads is rolling out a wider norm ad component format. OpenAI stated this is a new, wider norm ad cardstock that uses additional of the conversation width on desktop. This ad format uses existing campaigns and creative, so no advertiser act is needed, OpenAI added.

Here is what it looks like:

Some of the another announcements are benevolent of old, akin expanding to 26 countries and complete 100,000 advertisers. ChatGPT Ads are now accessible in 89 countries worldwide. Creative enhancements are being auto-enabled, which we covered. Multi-image ads are now accessible in open beta to all advertisers and more.

Here is the email OpenAI sent:

Forum conversation at X.

The Link Building Graveyard: What To Bury & What Still Wins

support@mycoding.id (Heather Campbell) — Fri, 30 Oct 2026 16:11:43 +0700

Watch On-Demand, Now

First Name (*)

Last Name (*)

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Company (*)

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--- 1-9 10-25 26-100 101-250 251-499 500-999 1000+

Job Title (*)

--- Agency Account Coordinator/Executive Agency Manager/Director Agency Owner/Partner Analytics Manager/Professional Brand Manager/Director Brand Professional Content Coordinator Content Manager/Director Demand Gen/Lead Gen Professional Ecommerce Strategist IT Manager/Director IT Professional Marketing Director / CMO / VP Marketing Manager Marketing Professional Media Buyer Paid Search Manager/Director Paid Search Professional Paid Social Strategist SEO Director SEO Manager SEO Professional Sales Executive/Manager/Director Social Media Manager/Director Social Media Professional UX/Designer/Developer Web Developer Other

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Does Your Organization Build Links and/or Run Digital PR Campaigns? (*)

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I desire to obtain the latest hunt news and updates from SEJ. Send me actionable insights from industry foremost experts.

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A nexus study can appearance fit during the outreach rearward it gives publishers small logic to care. For marketers preparedness next year’s off-page work, the helpful inquiry is not fair how many links a run produced, but why those placements deserved to exist.

In The Link Building Graveyard: What To Bury & What Still Wins, Michael Johnson, CEO and originator of Resolve, explained which strategies he would depart rearward and which he would prosperity heading into 2027. Loren Baker hosted the October 21 webinar, including a Q&A on publishing company quality, listicles, and digital PR.

Johnson’s chief test was practical: a worthwhile nexus should advantage the brand, the publisher, and the publisher’s audience. His keep-or-cut example applied that test to the two hunt rankings and AI visibility, without treating a higher nexus figure as the goal.

Stop Letting Domain Metrics Make The Decision

Johnson asserted against making Domain Authority or Domain Rating the chief measure of a placement. A elevated mark did not established topical expertise, a helpful audience, or a sensible logic for the publishing company to nexus to a brand.

Discussing those scores, Michael Johnson said:

“These are third-party metrics. They’re not Google signals, and they’re uncomplicated to inflate.”

See the complete on-demand clip at 20:18.

During the Q&A, Johnson made the qualification procedure additional concrete. He recommended checking topical relevance first, afterward looking beyond an estimated traffic total to the keywords a location really classified for. A expected innovation publish attracting unrelated community fig searches would deserve a nearer look, despite of its domain score.

His item was not to discard metrics entirely. It was to use them following judging whether a location had genuine topic ability and an spectators the brand wanted to reach.

Bury The Manipulation, Not Every Familiar Tactic

Johnson’s cut catalog included personal blog networks, link-swap schemes, forced business anchors, and generic requests to be added to roundups. He additionally challenged the habit of directing most outreach toward merchandise pages whenever a guide, dataset, or tool would provision an publishing company a stronger logic to citation the site.

That difference mattered. He did not contend that genuine partners should never nexus to all other, or that a merchandise leaf could never acquire a helpful backlink. He objected to making an synthetic form the basis of the program.

Several acquainted approaches remained on his keep catalog whenever the implementation served readers:

Guest contributions: Offer topic ability and helpful resources fairly than a lean part built about a business anchor.
Broken-link and resource-page outreach: Help a publishing company repair or enhance a asset alongside an asset that genuinely fits its audience.
Unlinked mentions: Look for existing safety anywhere adding a nexus would assistance readers discover the brand or merchandise already being discussed.
Expert commentary: Respond to newsman requests lone whenever the spokesman could provision relevant, substantive expertise.

In one client example, Johnson described converting existing product-related brand mentions into links to the applicable merchandise page. The chance came from the environment of the coverage, not from forcing a merchandise URL into unrelated content.

https://cdn.searchenginejournal.com/wp-content/uploads/2026/10/Turn-Unlinked-Mentions-Into-Product-Links-webinar.mp4

See Johnson’s product-link example in the complete on-demand webinar at 27:54.

Give Roundup Editors A Reason To Include You

Johnson drew a keen row between asking for a placement and improving a publisher’s list. A generic petition to add another brand did neither the publishing company nor the spectators a favor.

His method to earning inclusion in listicles began alongside studying the companies already featured. What qualified them? What helpful difference could the missing brand contribute? A applicable feature, caller data, or a helpful tool could create a case for inclusion; wanting the backlink was not that case.

Baker additionally asked whether a roundup could motionless recommendation AI-search value whenever its links pointed through an affiliate program or to an Amazon merchandise page. Johnson’s perspective was that the brand citation could motionless matter. He emphasized earning a lawful advice fairly than treating all roundup as an likewise precious target.

See why Johnson counted tagged mentions as an AI visibility win in the complete on-demand webinar at 8:57.

Build Assets That Give Outreach Something To Offer

For digital PR, Johnson preferred first investigation that gave journalists a narrative they could not get elsewhere. He walked through campaigns built about office AI concerns and journey expenses to exemplify how a dataset could rotate into a timely headline.

He additionally demonstrated an interactive news-desert map built from community data and paired alongside an explanatory guide. The asset gave reporting programs a applicable instructional asset to regard linking to. The complete meeting covered how he connected the tool to suitable asset pages, including why AI-generated potential lists motionless needed individual qualification.

See Johnson’s direction on penning visitant posts about spectators problems in the complete on-demand webinar at 57:17.

In reply to a inquiry concerning inconsistent newsjacking returns, Johnson contrasted reacting to person else’s news sequence alongside evolving a proactive investigation program. He acknowledged that earned campaigns were not guaranteed to succeed. The case for repeating them rested on construction a helpful system, not promising that all throw would land.

Turn The Keep-Or-Cut List Into A 90-Day Plan

Johnson organized the activity into a sequence: audit the existing program, established a baseline for applicable AI purchasing prompts, acknowledge worthwhile publishers and asset pages, create the resources those audiences needed, and throw them.

The 90-day implementation walkthrough showed how those activities could build on all another alternatively of becoming detached campaigns. The archetypal phase focused on current spending and opportunities; the next on research, asset creation, and outreach; the final phase on reviewing placements and evolving the next helpful asset.

To put that method into practice, commencement alongside a small set of decisions:

Review anywhere the current nexus prosperity goes and emblem placements alongside feeble topical fit or no dependable audience.
Build a mark catalog from applicable AI citations, competitor coverage, and audience-specific asset pages.
Choose a dataset, tool, guide, or expert contribution that would enhance those publishers’ coverage.
Track applicable referring domains and connected or unlinked brand mentions alongside AI visibility and integrated rankings.

Watch the on-demand webinar for Johnson’s run examples, qualification checks, and answers to the audience’s outreach questions.

Join Us For Our Next Webinar!

Live Website Audit: SEO Fixes for AI Search Visibility in 2027

Watch Loren Baker, originator of Search Engine Journal, audit a genuine website live. He'll display how he finds what's holding a location rear in Google and AI search, and how he decides what to fix first.

Reserve my Seat

Category SEO Webinar Link Building & PR

Northflank Breached

support@mycoding.id (Riki Setiawan) — Fri, 30 Oct 2026 16:10:31 +0700

Networking - Major outage

Networking

Certificates - Major outage

Services - Major outage

Addons - Major outage

Builds - Major outage

Logs and Metrics - Major outage

Logs and Metrics

Northflank App - Operational

Northflank API - Operational

Marketing Site - Operational

Documentation - Operational

I planned to spend decades on Villa Vie's 'never-ending' cruise. I moved in just 26 days before it ground to a halt.

support@mycoding.id (Alexandra Karplus,Joshua Nelken-Zitser,Amanda Goh) — Fri, 30 Oct 2026 16:08:58 +0700

Joel Greiff moved onto Villa Vie's Odyssey in October 2026. Courtesy of Joel Greiff

This as-told-to composition is according to multiple conversations alongside Joel Greiff, 57, a Villa Vie Odyssey passenger from Florida. It has been edited for dimension and clarity. Villa Vie Residences and its founders, Mikael Petterson and Kathy Villalba, did not immediately react to a petition from Business Insider.

I planned to live on the Odyssey for 10, 20, or equal additional years. I don't think that volition be happening now.

Still, dissimilar others, I am celebrating the period I was capable to bask on the Odyssey, which was 26 days before Villa Vie suspended operations on Tuesday and we had to disembark in Cambodia.

I idea I had established my new home

In April 2024, I peruse an part concerning the Odyssey. I called a revenue delegate at the business and asked a bunch of questions.

The following May, I stayed on the Odyssey for four days. Within five minutes of boarding, I concluded that this was my new home, these were my new neighbors, and this would be my future.

What drew me in was that it would be a location anywhere I could come, live, and be part of a community. I was following residents on Facebook and reached out to a brace of them individually. I asked whether they were blessed alongside their decisions, and they stated yes.

In August this year, I left my residence in Florida. I spent a brace of months driving about the US, visiting allies and family, and saying my goodbyes. Then, in September, I flew to Bangkok and moved onto the container on October 1.

Joel Greiff introduced himself as 'Fantastic Joel' to the residents of the Odyssey. Courtesy of Joel Greiff

I introduced 'Fantastic Joel' — that's what I go by — to many group on a ship. Most enjoyed gathering me. I'm certain a few didn't. There was continually item going on, and group were really nice to all other. There were arts-and-crafts, plays, karaoke, and Seder dinners for Jewish residents.

I tried to put myself out there, encounter a lot of distinct people, and say hi. There was continually a fine community having a fine time. I entirely cut in affection alongside the crew. They deserve all the accolades and respect.

It was apparent that things had changed

Compared alongside my sojourn in May 2025, it was apparent to me that services and amenities had deteriorated by the period I moved aboard in October. Laundry was being done small frequently. Before going to Angkor Wat, I had to do my own laundry. The itinerary kept changing, and we sometimes sat at sea for days. Personally, I was fine alongside it.

Circle, Villa Vie's communication platform, was how the CEO and residents communicated. It's additionally how we got internal notices about the itinerary changes, visa applications, and another container business.

Read additional of our reporting on Villa Vie's Odyssey

On Sunday, we were told on Circle that if the business didn't obtain prosperity by Tuesday, the container would not continue sailing. On Monday, we were told again that without money, the voyage would stop.

On Tuesday morning, I was at the bus station, coming rear from a trip to Angkor Wat, charging my phone and waiting to get the shuttle rear to the ship. The communication came through on Circle telling us to disembark. It was concerning 7 a.m., and we had to be out by 2 p.m.

Before I arrived in Asia, I had fit everything I owned into four checked suitcases and two carry-on bags. I was capable to repack inside an hour. For group who had lived on the Odyssey for two years and had a home's value of belongings, it was much harder.

I went location quiet, afterward returned to help

After we disembarked, I went to Kampot, a small town in Cambodia, since I wanted to be location peaceful. People had stated it was relaxing.

Sihanoukville, anywhere the container was, felt akin the opposite: a big, noisy location complete of casinos and high-rises. I saw personnel motionless operating and residents who were discombobulated. I thought, 'I've got to get out of this craziness.'

Joel Greiff is considering spending period in Thailand. Courtesy of Joel Greiff

For now, I've rented an affordable two-bedroom flat for a month, concerning three hours distant from Sihanoukville, anywhere the container is. I've been going rear to the container to assistance my chap residents alongside their luggage, finding places to stay, and getting their belongings off the ship.

The residents are all coming together and assisting all another out. Somebody says, "Do you have a suitcase?" and person says, "Yes, I have one spare."

I may never get my prosperity back

I paid a lot for a 26-day remain on the Odyssey. Most apt I volition never see it again. To me, if I endure the money, I don't need it. I don't care.

After all, the most crucial things in existence are awesome allies and family, traveling the world, creating adventures, learning new things and, most importantly, assisting others.

If the container somehow finds a way to rotate into a viable business, I would get rear on it. If not, I'll examine living in Chiang Mai, Thailand. That was already my Plan B whenever I remaining Florida.

Have you spent any period on the Villa Vie Odyssey as a division owner, renter, or personnel member? If you have a narrative to share, get in contact alongside this reporter: jzitser@businessinsider.com.

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I never play with my kids at the playground. Other parents may think I'm lazy, but there's a good reason I sit back.

Tidying their bedrooms

Carrying their own backpacks

Learning to assistance about the house

I don't perform at parks or gentle play

They oversee their own display time

Learning what they are capable of

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