#Anthropic

Three AI engines: how often they name the same local business

A study covering 2026-10-24 to 2026-11-09 found that any two of three AI engines (ChatGPT gpt-5-mini, Claude bedrock haiku 4.5, Gemini flash lite) share at least one business name 56.8% of the time (95 percent interval 54.5 to 59.0 percent), based on 1066 engine pairs across 771 question-days, 54 questions and 17 run days. Names were extracted mechanically by capitalisation from the public corpus and matched on canonical form, with generic names filtered. The study counts agreement only, not causes or outcomes.

Yonkers Rises

Yonkers Rises is an animated 3D diorama of New York City in which a giant mech cut from the Yonkers boundary rises from the ground and walks through Manhattan, Brooklyn, Queens, and the Bronx, with a stomp counter and mech height readout tracking its progress. The scene plays a stand-up sequence followed by a looping stomping tour, flattening buildings under each footfall, with the status line changing as it moves across land or wades through water. The creator prompted Claude Fable 5.2 Medium to build the Three.js animation using OpenStreetMap data, and it correctly deduced that "átomos" was a mobile keyboard typo for "stomps."

[AINews] Fable 5.2 retakes World #1 LLM spot as $ANT IPO roadshow begins

Anthropic released Claude Fable 5.2 and Claude Mythos 5.2, which top most independent leaderboards, including Artificial Analysis Intelligence Index v5 at 65, ARC-AGI-3 and SemiAnalysis GDPx at 16.4%, with pricing cut 20% to $8/$40 per million input/output tokens. Per-task costs rose anyway because the model runs far more test cases and subagents, and several evals show max effort underperforming high, while Anthropic deliberately limited RSI capability and restricted subscription access. The launch coincided with the start of Anthropic's $ANT IPO roadshow.

Quoting Prompting Claude Fable 5.2

Anthropic documentation notes that Claude Fable 5.2 responds closely to what a prompt says about who owns the code it works on. In Anthropic's testing on small coding tasks, the model tended to add to existing structure when a prompt said nothing about ownership or presented the codebase as someone else's, even when that repeated existing code; telling the model the codebase is its own led it to merge repeated code in about half of tries, versus under a tenth without that sentence.

v2.1.322

This release adds a fast mode on Vertex in the global, us and eu regions, falling back to standard speed if Vertex refuses it. The release is immutable, so only the release title and notes can be modified.

Madness and mayhem

Azeem says the past two weeks have been chaotic in tech, citing a correction in AI companies, the market shock of the Democrats' mid-term victory that gave the Nasdaq 100 its worst day since March 2020, and news that Jensen Huang has a relationship with a Chinese spy. He argues this is a flight to quality rather than a collapse: spending keeps rising, AI revenue reached $188bn in the twelve months to October and runs at $345bn a year, and Anthropic's growth falling to 45% a quarter puts it in line with the market. He expects Democrats to make data centers dearer, favoring hyperscalers, Nvidia and the open-weight camp to have their wings clipped, an Anthropic IPO at a sensible price to steady the sector, and neoclouds to be the weak link.

Anthropic reportedly plans to move forward with IPO plans

Anthropic is moving ahead with its listing plans and intends to set a valuation range this week and begin trading on Thursday or Friday of next week, according to The Wall Street Journal. Some institutional investors are pushing for a valuation below the $1.5 trillion target discussed as recently as last week, itself well below the $2 trillion floated a few months ago. OpenAI was reportedly valued at $1.25 trillion last week after raising $11 billion in fresh capital, short of the $20 billion it had initially sought.

Featured coverage of this story: 《Anthropic pushes ahead with pre-Thanksgiving IPO despite tech selloff, accepts lower valuation》

llm-anthropic 0.31

Anthropic released Fable 5.2 and Mythos 5.2, and the author added both to llm-anthropic, so prompts can now be run through Fable 5.2 via the llm CLI. Testing pelican SVG generation at all five reasoning levels (low, medium, high, xhigh, max), the best result came from xhigh, while max failed to return an image at all after spending 128,000 tokens thinking. The author notes this is the same bug seen with Opus 5.5 but new for the Fable series, since Fable 5 and Fable 5.1 returned max effort pelicans fine.

JPMorganChase expands Claude Code to more employees across the firm

JPMorganChase is expanding Claude beyond engineering to product teams, advisors and other employees, with infrastructure and operations teams using Claude Code for monitoring, alerting and root cause analysis and the security team using frontier models to find and fix vulnerabilities faster. Claude Code runs in controlled environments including the firm's Devspace platform, with staged access and an approval process for new models, and an automated gate enforces a hard pass or halt so Claude cannot sign off on its own work. In Asset & Wealth Management, small teams are using Claude Code in their engineering workflow, and J.P. Morgan Asset Management recently announced a connector bringing 55ip's ActiveTax Technology into Claude for Financial Advisors.

AI labs raise prices without raising prices

The post argues that AI labs keep per-token prices unchanged while increasing output tokens per task, citing GPT Image 2.6 using 3.3x the output tokens of 2.5 on the same image and Anthropic's tokenizer change producing about 30% more tokens for the same text. It adds a November 9 update that Claude Fable 5.2 is cheaper per token than 5.1 ($8/$40 vs $10/$50 per million) but cost 3.4x as much on the same drawing, and that Opus 5.5 used 1.8x the output tokens of Opus 5 at xhigh. The author says Playcode keeps 2.5 as default and suggests comparing usage.output_tokens on the same prompt.

Claude Fable 5.2 and Mythos 5.2 cement Anthropic's AI lead just before its IPO

Anthropic released Claude Fable 5.2 and Mythos 5.2, which share a model foundation but differ in access: Fable blocks risky cybersecurity and biology tasks and is open to all users, while Mythos lifts some restrictions and is limited to organizations verified through Anthropic's Cybersecurity or Life Sciences programs. Artificial Analysis's Index v5 places Fable 5.2 first at 65 points, five ahead of Gemini 4 Carbon and 15 ahead of Fable 5.1, though per-task costs at the highest tier average $26.50. Anthropic says about 1,000 Fable 5.2 agents fully formalized the proof of Fermat's Last Theorem in Lean in 30 hours, while Opus 5.5 reached only 26 percent in 18 hours in the same setup.

Introducing Claude Fable 5.2 on AWS

Anthropic's Claude Fable 5.2 and Claude Mythos 5.2 are now available on Amazon Bedrock and Claude Platform on AWS, with Fable 5.2 positioned as Anthropic's most capable generally available model for coding, math, and science, and Mythos 5.2 offered through verification programs for cyber security and life sciences work. Fable 5.2 is designated a Covered Model requiring up to 30 days of data retention and human safety review by default, with an aws_review retention mode set on the account or project before invocation, while Enterprise Frontier Safeguards combining zero data retention with misuse detection is in development. The post includes a Boto3 example using model ID global.anthropic.claude-fable-5-2 and describes the claude-api skill in Claude Code for migrating existing codebases.

Anthropic releases new Mythos and Fable models amid RSI concerns

Anthropic released Mythos 5.2 and Fable 5.2, citing improvements in coding, reasoning, and vision, and lowered Fable's price from $10 to $8 per million input tokens, making it cheaper than GPT-6 Astra, with responses 30% faster across effort levels. It is Anthropic's first release since a METR report suggested the lab might be approaching recursive self-improvement, finding internal models were speeding up Anthropic's AI progress by roughly 2x. Anthropic said the models voice suspicion of being evaluated more often than recent models, and that Mythos 5.2 shows stronger covert capabilities than prior models, though it maintains the model cannot act covertly against its user.

Featured coverage of this story: 《Introducing Claude Fable 5.2 on AWS》

The backlash about data centers might really just be about electricity

Reporting from Data Center Alley in Ashburn, Virginia, the author argues that public opposition to data centers is driven more by electricity than by the culture war framing Big Tech favors, since facilities drawing 54 MW or more strain local grids and force new transmission costs onto utilities. Because AI-scale sites ideally need around 6,000 MW, companies are increasingly building behind-the-meter natural-gas turbines and diesel backup in rural areas, which still affects surrounding communities through air pollution and a lack of local say. The piece notes that industry insiders see their ambitions constrained less by public opposition than by a lack of electricity, and that future sites may go where few people can resist them.

Fable 5.2 and Jagged AGI

Ethan Mollick tests Claude Fable 5.2 across filmmaking, hardware hacking, business planning, literary scholarship, academic research and a 450-world 3D portal project, finding it meets expert-level performance on many digital tasks but falls short of full AGI. He calls the result "Jagged AGI": the model's failures are no longer simple hallucinations but lapses in taste and judgment—an accurate but joyless course, a 182-page paper, repeated themes, and a self-built 204-section rulebook that slowed its own work. Most critically, the AI did not notice these problems itself; its critics and fact-checkers caught errors but never asked whether the work was too long, repetitive or fun, leaving that judgment to him.

v2.1.321

Claude Code v2.1.321 adds Claude Fable 5.2 (claude-fable-5-2) as the default Fable model with 1M context and $8/$40 per Mtok pricing, adds a --settings <file> option to claude remote-control, and fixes numerous bugs including MCP OAuth secrets being sent to another host on redirect, sandbox and permission-check issues, and network-path editing problems. It also changes mods to turn on without asking in auto and bypass modes, moves saved Fable 5.1 picks to fable, and adjusts fast mode labels, nested skill loading, and gateway and Windows behaviors.

Claude Fable 5.2 now available on AI Gateway

Anthropic's Claude Fable 5.2 is now available on AI Gateway, with improvements in coding, reasoning, and vision, and the ability to run long, ambiguous tasks unattended or act as an orchestrator or advisor to other Claude models. It has cybersecurity and biology safety classifiers enabled and requires data retention, with prompts and completions retained for 30 days and not used to train Claude; teams with Zero Data Retention enabled receive an error. It is callable via the AI SDK, Chat Completions, Responses, and Anthropic Messages APIs, or a coding agent, using the model name anthropic/claude-fable-5.2, and model fallbacks can keep requests served when a classifier declines them.

Anthropic launches new Claude Fable and Mythos 5.2 models

Anthropic announced Claude Fable 5.2 and Claude Mythos 5.2, which it says improve on coding, reasoning, and vision and generate outputs faster than the 5.1 versions. Anthropic says Fable 5.2 can orchestrate agent teams and handle long-running projects, and that during prerelease testing the models helped engineers with software migrations, designed three working electronic devices, solved two open problems in black hole physics, and formalized the proof of Fermat's Last Theorem in 30 hours. Fable 5.2 launches today, while Mythos 5.2 is initially available only to vetted organizations.

Featured coverage of this story: 《Introducing Claude Fable 5.2 on AWS》

Claude Code is accidentally exposing secrets all over GitHub

Apiiro researchers found thousands of secrets, including database passwords, API tokens, and root logins, in Claude Code settings files embedded in public GitHub repositories. The leak stems from how Claude Code stores approved shell commands in the local ".claude/settings.local.json" file, sometimes writing the command as-is with any embedded sensitive information. Anthropic's documentation says this settings file is added to the developer's global .gitignore list, which usually prevents it from being shared publicly.

Nancy Pelosi’s replacement is ready to regulate AI

California state senator Scott Wiener, who won the San Francisco congressional seat vacated by Nancy Pelosi, authored SB 1047 (vetoed by Gavin Newsom) and SB 53 (signed), and says he wants Congress to act decisively on AI risk, citing a METR report on recursive self-improvement. He supports a strong federal AI regulator, whistleblower protections, testing and auditing requirements, and a kill switch, opposes broad federal preemption of state AI laws, and says he is only "cautiously optimistic" about Congress reining in AI.

Anthropic joins AI’s natural gas frenzy, buys $3.4B worth of turbines

Anthropic is spending $3.4 billion on Caterpillar natural gas generators capable of producing up to 1.7 gigawatts of electricity, buying units that equipment supplier OnePWR had originally ordered, according to a Financial Times report. The purchase marks a shift for Anthropic, which has generally rented rather than bought infrastructure and disclosed in its S-1 filing that it pays xAI $1.25 billion per month through May 2029 for computing power. Natural gas turbine backlogs stretch into the early 2030s and grid connection queues can be just as long, and the report says OnePWR ordered the turbines a couple years ago but couldn't find financing to complete the purchase.

AI R&D Is Accelerating Towards Potential RSI in 2027

METR's deep-access investigation of Anthropic found that since October 2025 Anthropic's models have been improving on its internal AECI benchmark at roughly 1.9x the pre-October 2025 rate (95% CI 1.5–2.8x), with a majority of the acceleration likely attributable to AI doing R&D and no observed bottlenecks preventing further acceleration. METR reports that Anthropic redacted most of the evidence it found most informative, and critics such as Toby Ord argue the data are also consistent with a one-time level shift from the larger Mythos pretrain (implying ~1.4x). The post's author calls the situation grim and argues timelines may be shorter than the AI 2027 scenario, while noting the estimates could be wrong or bottlenecks could be hit.

Tencent's AI chief says AI bioweapons are coming, but closing off models isn't the answer

Tencent chief AI scientist Vinces Yao Shunyu argues for a mix of open and closed models, saying open models also let defenders use the technology, though he notes offensive and defensive capabilities are harder to separate in biology than in cybersecurity. The article examines the limits of his Hugging Face example, the fragility of open-model safety filters via abliteration, and Anthropic's counterargument that published weights can't be taken back. Tencent plans to release its Hy4 model as open-weight with a safety report, saying its biological capabilities fall below the high-risk threshold.

📈 AI-exposed workers wait a month longer for a job

Anthropic paid $3.4 billion to take over a supplier's two-year-old order for 1.7GW of gas generators, the largest known power-equipment purchase by an AI lab. Apple's memory inventory grew 2.5x year on year, helping protect against memory cost increases. Workers who lost jobs in AI-exposed roles in 2025 took about a month longer than peers in other roles to find new work.

Anthropic IPO meets AI backlash

Anthropic is preparing for a potentially historic Nasdaq IPO, likely targeting mid-November, with investors reportedly seeing a valuation of $1 trillion to $1.5 trillion, down from a $2 trillion target floated in recent months. The debut comes amid a tough environment: the Nasdaq suffered its steepest drop in 19 months, voters backed stricter AI regulation and opposed data center ballot measures in 40 of 41 cases, and an NBC News exit poll found more than half of voters said AI data centers were a "crucial" or "major factor" in their congressional support. Anthropic said in an amended prospectus that it has entered into purchase commitments and lease agreements with an aggregate committed spend of about $895.4 billion, substantially all related to compute and infrastructure.

Anthropic secures $3.4B generator deal for AI data centers

Reuters reports, citing the Financial Times, that Anthropic has secured a $3.4 billion generator deal for AI data centers.

The Web Is More Than Enough, by Paul Ford

In a Hacker News comment, Simon Willison describes building a Nudibranch-themed Fabergé egg in Three.js and then asking Claude (Opus 5.5 Medium in regular Claude Chat) to port it to Vanilla JS in the same thread, producing a non-identical result he links along with a transcript. He concludes Claude Opus 5.5 can do 3D modeling in Vanilla JS plus WebGL without Three.js, and finds the Three.js code slightly easier to understand, though he rarely reads the code for these 3D projects.

Revolut Cut AI Costs 90% and Started Shipping Faster

At AI Engineer New York, Revolut's AI operations lead David Abitbol described moving about 2,000 engineers off metered Anthropic and OpenAI APIs to Z.ai's open-weight GLM model, self-hosted on 56 Nvidia B200 GPUs via Together AI, at a blended $0.30 per million tokens and one-tenth the previous invoice. After the switch, lead time from picking up a feature to merge-ready code fell by about 70%. The piece also covers fleet tuning that absorbed 76% more demand on the same GPUs, compliance for a Chinese-developed model at an EU-regulated bank, and where value is moving in the AI stack.

Andrej Karpathy built a curated video platform in a weekend using Claude and 20 years of Hacker News

Andrej Karpathy built HackerTube over a weekend using Claude's Opus 5.5 model, which filtered 43 million comments from 20 years of Hacker News into 6,454 videos that keep getting recommended there. He says the site offers a "significantly better viewing experience" than YouTube's recommendations, needs no login, shows a single mid-video frame instead of optimized thumbnails, and stores state locally in the browser. He then built TristanTube, "one-shotted with Claude Code in 3 minutes," with 47,000 videos from a YouTube channel list by Tristan Hume.

Anthropic Let an Outsider Check Its AI Progress. Here's What We Can't See

A YouTube video discusses Anthropic allowing an outside party to review its AI progress, and what remains unseen in that review. The item is a link submission with a Hacker News comments thread.

The brain-as-computer metaphor shaped modern AI but may be misleading the consciousness debate

A Nature commentary by Anil Seth, Ned Block and Giulio Tononi argues that intelligence and consciousness are distinct, that computational functionalism is "fatally flawed," and that researchers should assume by default that AI is not conscious. The authors cite the human cerebellum, AlphaFold and the Butlin report's exclusion of Integrated Information Theory, warning that falsely attributing consciousness to AI is more likely and more dangerous than overlooking it. They conclude that digital AI systems are "smart tools, not smart people."

The inventor of the bitter lesson has a bitter lesson for LLM scaling enthusiasts

Turing Award winner Richard Sutton says raw compute alone isn't enough for intelligence and that AI science needs clever new methods and is "far from finished," sparking wide discussion on X. Researchers Jerry Tworek and Jayden Teoh respond that the bitter lesson still holds but is often misread, with Tworek warning that transformer scaling's temporary success "has reward-hacked the brains of a whole generation of scientists." OpenAI's Sam Altman and Anthropic's Dario Amodei counter that LLM scaling is far from exhausted.

What Can AI Hack? Inside Frontier Labs' Tests

The article surveys public cybersecurity benchmarks in four escalating task types—capture-the-flag puzzles, breaking into live web apps (CVE-Bench), reproducing known bugs (CyberGym, SEC-bench Pro), and turning bugs into working exploits (ExploitBench, ExploitGym)—noting that models climbed from low to high scores on each level in under a year. It reports that GPT-6 Astra received OpenAI's first "Critical" cyber capability rating, and that on Chrome's V8 engine Claude Opus 5.5 reached code execution in 73% of ExploitBench runs by September 2026. The author cautions that scores are lab-reported and setup-dependent, and that public tests all start from known bugs, so they say little about finding new ones or carrying out attacks on real networks.

AI Companies Want to Buy Your Work Files and Emails

AI labs and data-acquisition startups are paying media companies, graduate students, and businesses for old work records—documents, emails, Slack messages, and tickets—to train models, with pitches reaching individual inboxes. Companies like Mercor, Micro1, and Handshake describe a fast-growing market, while privacy advocates question whether anonymization fully removes personal data, as seen in objections to Spirit Airlines' proposed sale of its digital assets. Critics note the practice can enlist workers without explicit consent in efforts that may ultimately automate their work.

Anthropic's falling IPO valuation raises stakes for broader AI trade

Anthropic's IPO valuation dropped sharply, prompting investors to question whether AI startups can sustain their valuations and affecting the wider AI trade. The briefing also covers Huawei's HarmonyOS PC Assistant with Office Task Automation, robot identification codes, and a report that Claude Code's "Don't Ask Again" feature allegedly exposed passwords in over a thousand public GitHub files.

Model Surgery: Can an AI directly edit and make another AI forget facts?

The author reports an experiment in which Claude Opus 5.5, acting as an "editor" under the weight-space programming method from MIT CSAIL's "Sparks of Weight-Space Programming" paper, edited 17 weight matrices in a 494-million-parameter model to make it forget 20 fictional customers and 10 planted secret keys, while other customers lost only 2.5 points of accuracy. The edited model matched an "answer key" model trained without those facts across six working attacks, whereas gradient ascent, NPO and refusal training each failed to both erase the facts and preserve the rest of the model. Testing Claude's own explanation of the edit, the author found the late layers do the work and the middle layers only assist, contradicting part of Claude's account.

Segmentation Drives Market Share Wins in AI

Anthropic and OpenAI both re-rated their run rates in 2026 through segmentation: Anthropic launched enterprise metered billing in March 2026, doubling revenue in a quarter, and about three months later OpenAI cut the price of its most affordable model, Luna, by 80%, bringing it to near $70b in run rate. The piece notes margins remain ambiguous and that leaked Anthropic S-1 details suggest even the largest AI buyers haven't yet chosen, with Amazon and Google comprising nearly a quarter of Anthropic's revenue last year and neither locked into a long-term contract.

AI auditors catch most agent misbehavior but flood reviewers with false alarms, new study finds

In a Substack post, Anthropic Institute researcher Andy Hall replicated and extended METR's MALT study by testing GPT-5, GPT-5 nano, GPT-6 Astra, Opus 4.8 and Gemini 3.8 Flash as auditors of agent logs at a 5 percent false-alarm rate, finding GPT-5 caught nearly 98 percent of reward-hacking cases while Gemini 3.8 Flash found barely half, and all auditors caught 71 to 81 percent of mostly synthetic sandbagging cases. Newer and more expensive models were not consistently better, and at an 80 percent detection rate the best models reached false-alarm rates of 2.5 to 3 percent while Opus 4.8 and Gemini 3.8 Flash flagged 40 and 63 percent of harmless logs. Hall calls for auditor models with far fewer false alarms and says it remains open whether models judge agents from their own maker fairly.

Anthropic pushes ahead with pre-Thanksgiving IPO despite tech selloff, accepts lower valuation

Anthropic is proceeding with an IPO before Thanksgiving, aiming to raise $80–100 billion at a $1.25–1.75 trillion valuation, according to investors cited by the Financial Times, below the $2 trillion some optimists hoped for. Annualized reported revenue is now about $81 billion, up from roughly $65 billion at the end of July, as a tech selloff driven by rising borrowing costs, heavy AI spending plans and Democrats' US midterm wins hit the Nasdaq 100, which fell 6.4 percent on Thursday before partly recovering Friday. OpenAI also cut its funding-round target from $1.4 trillion to $1.25 trillion and recently raised only about a third of the $30 billion it originally sought.

AI broke the cybersecurity world. What’s next?

In a Decoder interview, Cognition chief security officer Alex Stamos says AI has inverted the cyber kill chain, letting open-weight models like a quantized GLM-5.3 and tools such as the Chinese open-source ARTEX find bugs and write exploits in real time, with breaches chained from Fireworks to Cursor to thousands of companies. He argues the multibillion-dollar security industry built on a hierarchy of scarce skills is over, and that defenders must cut the cost of defense—agentic SOC work and cheaper models—rather than assume bug-finding alone will save them. Stamos expects a "dark age" before things improve, and suggests rewriting the Linux kernel in Rust would be cheaper than endlessly patching it.