The AI Wire ●

Anthropic has made Claude Models on Google Cloud (Anthropic managed) generally available, giving Google Cloud customers a second way to buy Claude alongside the existing Google-managed offering. Both routes use Google Cloud credentials, IAM and Marketplace billing, and spending on the Anthropic-managed service counts toward existing Google Cloud commitments — but Anthropic operates this service itself, sets its usage limits and acts as the data processor under its own commercial terms.

The practical difference is features. The Anthropic-managed route carries the full Claude Platform from day one, including document uploads, web search and code execution, with new models and platform features arriving the same day Anthropic releases them; Claude Managed Agents remains in beta. The launch line-up is Claude Fable 5.1, Opus 5.5, Sonnet 5.5 and Haiku 5.5, and Opus 5.5 fast mode is generally available through the service at $8 per million input tokens and $40 per million output tokens.

Google's own comparison keeps the Google-managed option as the better fit for customers who need Google as data processor, strict regional residency, or native integrations such as Model Armor and Agent Engine, and it does not claim the same VPC Service Controls and customer-managed encryption keys for the Anthropic-managed route. Anthropic also warns customers with existing discounts to talk to their account executives before starting, because discounts cannot be applied retroactively to usage on the new service.

Anthropic and formal-verification startup Theorem say Claude has done something that used to take experts years: it wrote mathematical proofs that real software will not crash. In research published on October 22, Claude proved that 239 test entry points across 123 open-source libraries from Google's OSS-Fuzz programme never crash on any input under 64 MB, working at the level of compiled RISC-V machine code.

The proofs run to roughly 180 million lines of Rocq, a proof language checked mechanically by computer, with a typical proof around 600,000 lines for a binary with a median of 18,000 instructions. Along the way Claude found bugs that trillions of fuzzing runs had missed, patched them, and then proved the patched code crash-free. Anthropic is publishing a subset of the proofs and the trusted components underneath them, so the checking does not depend on trusting the lab.

The bounds matter: the proofs cover single-threaded, static RISC-V binaries, not the x86 or ARM builds most software actually ships as, and 'formally verified' here means crash-freedom for the stated property, not bug-free in general. Even so, Anthropic frames it as the first large-scale use of AI for formal verification of production software at assembly level — arriving in the same week AI models helped surface the PHP2Shell flaws and Claude stripped unneeded code out of OpenSSH.

Federal lobbying disclosures for July through September 2026 show a step change in Washington: Nvidia spent $2.2 million, Anthropic $2.1 million and OpenAI $1.5 million on federal lobbying in the third quarter — a quarterly record for each company, The Verge reported on October 22. Anthropic's figure is roughly double its highest quarterly total from 2025, and OpenAI did not clear $1 million in a quarter until this year.

A broader count by the Project On Government Oversight, which adds outside lobbying firms' filings, puts the three companies' combined third-quarter spending at about $7.5 million, up 22% from the previous quarter and roughly 60% from a year earlier. The three have spent about $37 million on federal lobbying since the start of 2024, with roughly half of it coming in 2026 alone.

The filings cover the fights now shaping the industry: child safety legislation including the Kids Online Safety Act, chip export controls, cybersecurity evaluations, copyright, and who pays for data-center power — Anthropic's disclosure lists the Ratepayer Protection Act, which would push data-center energy costs onto developers. Lawmakers have introduced at least 99 AI-related bills in the current Congress. The sums are still modest next to the incumbents — Microsoft has spent at least $2 million a quarter since 2021 and Google regularly exceeds $3 million — but the trajectory is the story.

The Agentic AI Foundation (AAIF), the Linux Foundation group for open agent standards, announced four new hosted projects on Thursday at AGNTCon + MCPCon North America in San Jose: Agent Skills, contributed by Anthropic; Open Responses, contributed by OpenAI; OpenEnv, contributed by Hugging Face; and OpenSandbox, contributed by Alibaba. The additions take the foundation to 10 hosted projects in its first year, up from three at its December 2025 launch, joining MCP, AGENTS.md, goose, the Agent2Agent protocol, Agent Router and agentgateway.

Agent Skills is the headline transfer. Anthropic built the format while developing Claude Code, launched it in October 2025 and opened it as a cross-platform standard in December; a skill is a folder built around a SKILL.md file, with scripts and reference material an agent loads only when needed. Anthropic says more than 70 agent platforms, including ChatGPT, Cursor and GitHub Copilot, have adopted it, and the donation covers the standard's name and branding, its GitHub organization and the agentskills.io domain. Engineers from Anthropic, OpenAI and Google will maintain it in their personal capacities, ending Anthropic's sole leadership.

The four projects cover four layers of the agent stack: how agents gain skills, how applications talk to models across providers (Open Responses is OpenAI's open inference specification), how agents are trained and evaluated, and where agent code runs safely. 'A year ago, AAIF launched with three projects and a bet that agentic AI needed a neutral home to thrive. Today we host 10,' said Manik Surtani, the foundation's CTO and co-founder. The scale cuts both ways: the skills directory lists roughly 1 million published skills with nearly 280 million installs, and Snyk has already identified 76 malicious skills in one sample, which is why Anthropic has proposed version management, a formal proposal process and security guidelines for the standard.

Walmart announced on Wednesday that it is embracing agentic commerce, launching an Agent Gateway and related controls for customers who shop through AI agents. The move is the opposite of its biggest rival's: Amazon has recently begun blocking outside AI agents from making purchases on shoppers' behalf.

The Agent Gateway is Walmart's own MCP server — the Model Context Protocol was originally created by Anthropic — letting approved agents search Walmart and Sam's Club inventory and buy on a customer's behalf, without the customer having to hand the agent their personal information or purchase history. Walmart already offers integrations with Meta's Muse, ChatGPT, Gemini and other popular AI apps.

Agent Profiles, rolling out next month, give each agent a dedicated profile inside a customer's Walmart account, likened to adding an authorized user to a credit card. Customers can require approval for every purchase or set a spending limit, can delete a profile at any time, and do not need a Walmart+ membership. Walmart is also publishing terms for agents: they cannot exceed what the shopper intends, cannot access payment information, and non-compliant agents will be blocked — while Walmart's returns process still applies when an agent buys the wrong thing.

xAI's Grok Bot can now build reports, memos and dashboards, the official @bot account on X said on Wednesday. Users ask Bot for a page, then edit it together with Bot or have Bot keep the page up to date on its own, the post said, showing the feature in a 27-second video.

That is most of what is known. The announcement gave no availability, plan or pricing details, did not say which data sources dashboards can draw on or how often a self-updating page refreshes, and Grok Bot's public changelog had no matching entry when Tesla News Wire checked — the latest listed release was v0.71.2 from October 14. An October 11 release had already labeled canvases and documents as Page, with PDF download and sharing.

The feature follows SpaceX's third-quarter call on October 20, where president Gwynne Shotwell said Grok Bot had 800,000 paid weekly users and that business customers are its fastest-growing group — the audience living documents and dashboards are aimed at.

Recursive Superintelligence released its first model on Wednesday: Flint, an open-weight coding model designed to run on a laptop rather than a data center. Flint is a mixture-of-experts model with 39.8 billion total parameters but only about 2.5 billion active per token, fits on a 48 GB Apple Silicon Mac or a single 48 GB Nvidia GPU (4-bit weights take about 23 GB), and is free on Hugging Face under Apache 2.0. The model card lists a 262,144-token context window; Recursive's blog cites up to 512k.

Recursive says Flint generates more than 125 tokens per second on an M4 Pro MacBook Pro and more than 150 on Nvidia RTX Spark — up to twice comparable models. On its own charts it tops other MoE models under 50B on agentic coding, scoring 74.2% on SWE-bench Verified and 95.1% on IFEval, though it trails badly on Terminal-Bench 2.1 at 54.9% against 73.0% for a dense Qwen model. The company concedes Flint may need more guidance than large closed coding assistants.

The bigger claim is how Flint was made: a small team built it from scratch in under four months, leaning on Eureka Machine, Recursive's automated research system, for nearly every part of the stack. Recursive, led by former Salesforce chief scientist Richard Socher, emerged from stealth in May with $650 million in funding from backers including GV, Nvidia and AMD Ventures, and pitches Flint as a first public test of recursive self-improvement.

Two critical vulnerabilities in PHP — the language behind roughly 70% of websites, including WordPress sites — were publicly disclosed on Wednesday, with emergency patches issued by the PHP Foundation. The flaws, tracked as CVE-2026-109618 and CVE-2026-109619 and collectively nicknamed PHP2Shell, are rated 9.2 in severity, allow unauthenticated remote code execution, and have sat in PHP versions since version 5 in 2004.

AI found them first. Security firm Calif, working in OpenAI's new Patch the Planet initiative, used GPT-5.6 Sol to find one flaw in August, while Wiz independently found both using its Wiz Atlas agent together with Google's Gemini 4 Argon and GPT-5.6 Sol. OpenAI says it led a two-month coalition of maintainers, researchers and providers to prepare fixes, and is putting $1 billion in subsidized model access behind defender work of this kind.

The US National Security Agency warned that sites that cannot patch immediately should be pulled offline until they can. Patched releases are PHP 8.5.12, 8.4.27, 8.3.36 and 8.2.35; versions 8.1 and older are unsupported. Wiz notes the same AI capability that found the bugs also lowers the barrier to exploiting them, which is why the patch race is urgent.

Day 17 of Tibo Sottiaux's 28-day ship-or-reset run, which lasts until November 1, landed on Wednesday as a reset day. The post reads: bet you thought we forgot, but no, it is reset day today — a full Codex limit reset for users tracking the series.

The same post used the moment to remind developers to get Daybreak Blue access, OpenAI's vetted tier for security work with its frontier models, saying it only takes about 15 minutes to apply. Daybreak Blue is the access route behind the recent run of AI-assisted vulnerability work, including the PHP flaws disclosed this week.

At Thursday morning's sweep, Day 18 had not yet landed: the trackers still showed waiting for Tibo, with the challenge at 18 of 28 days.

OpenAI, PerturbAI and Scripps Research announced on Wednesday that they split a whole-brain CRISPR atlas — 8 million mouse brain cells and nearly 2,000 disease-linked genes — across roughly 2,000 GPT-Rosalind agents, each investigating one gene disruption, analyzing how cells responded and searching the scientific literature for explanations. The full analysis took 32 minutes; the team estimates the same one-perturbation-at-a-time work would take human experts several months to a year.

The combined output is a public reasoning atlas linking genes, cellular effects, publications and candidate mechanisms. The distributed agents cited more than 700 references, against 11 from a single agent given the full dataset, and blinded specialists preferred the multi-agent reports 75% of the time. Their novelty and scientific-value judgments also lined up with the human experts'.

Two leads stood out: unexpected differences between disrupting Tsc1 and Tsc2, genes relevant to tuberous sclerosis, in movement-related brain regions including the cerebellum; and a new hypothesis linking disruption of DCTN1 to altered cholesterol regulation in neurons, relevant to Perry syndrome, a Parkinson's-like neurodegenerative condition. Both are research leads needing lab testing, and the companion paper is a bioRxiv preprint that has not been peer reviewed.

OpenAI and Google Cloud said on Wednesday that OpenAI's frontier models and its Codex coding agent will be offered through Google Cloud's Model Garden, billed through Google Cloud Marketplace. GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna are rolling out in private preview to select enterprise customers, with general availability planned in the coming weeks.

Customers will be able to draw down existing Google Cloud spend commitments and use Google Cloud's access controls and data governance tools, which the companies pitch at regulated industries building agentic workflows. OpenAI said Microsoft remains its primary cloud partner.

The deal puts OpenAI's models on all three big US clouds. OpenAI's exclusive distribution arrangement with Microsoft expired in April, and it has since expanded to Amazon Web Services and now Google Cloud — even though Google competes with OpenAI in core AI products and search.

OpenAI published a technical post on Wednesday explaining how ChatGPT's advertising system actually works — and how big it has already become. The company says ChatGPT Ads passed $1 billion in annualized revenue run rate in under 200 days and has drawn more than 100,000 advertisers, the same week it expanded ads to 26 more countries for a total of 89.

Ad selection is run by a custom, post-trained frontier model OpenAI calls the orchestrator. It handles the whole flow through tool calls — choosing when to run retrieval, ranking, relevance scoring and auction steps — in a separate service, so it cannot slow down or shape ChatGPT's answers. Because conversational intent does not arrive as a single search-style request, the system keeps a stateful session across turns and even across conversations, rewrites that context into retrieval queries and semantic embeddings, fetches candidates with approximate-nearest-neighbor search, then filters for budget, pacing, policy, targeting and advertiser deduplication.

A day earlier, OpenAI had emailed advertisers that creative enhancements — automatic rewrites of ad headlines, text and landing pages — will be switched on by default for new and existing campaigns unless advertisers opt out. Ads appear only on the Free and Go plans; Plus, Pro and Enterprise users see none.

OpenAI said on Wednesday it is expanding advertising on ChatGPT to 26 more countries, bringing the total to 89, as it builds the ads business ahead of a potential IPO. The company said in August that ads had reached an annualized revenue run rate of $1 billion, and that more than 100,000 advertisers have run campaigns since testing began in the US earlier this year.

The expansion adds 14 more Latin American countries, including Argentina, Chile, Colombia and Peru, following launches in Mexico and Brazil. Ads are also launching across Europe, the Middle East, Africa and Asia, including Nigeria, South Africa, Serbia, Ukraine, Cambodia, Bangladesh and Pakistan.

Ads appear only on ChatGPT's Free and Go plans; Plus, Pro and Enterprise subscriptions remain ad-free. Advertisers in the new markets can buy through technology partners or self-service via Ads Manager, and in September OpenAI added AI-powered advertiser tools and began testing business-sponsored agents with select US advertisers.

Sam Altman sat down with Matthew Berman for a 45-minute interview published on Wednesday, ranging across AI-driven math and science discoveries, personal AI assistants, compute and OpenAI's new hardware. Asked whether today's models are conscious, Altman said he does not believe they are — 'or if they are, it's a very strange form of it' — before adding the line that anchors the conversation: 'I want to be clear, no one really knows.'

On hardware, Altman argued that phones and computers were designed for people, so AI agents are stuck interpreting visual interfaces instead of reaching information directly. He sees AI becoming an ambient assistant that helps beyond a chat window, which may require a different physical form factor — the bet behind OpenAI's device work.

The interview also covers recursive self-improvement, why AI has not killed coding jobs, ChatGPT being too agreeable, and OpenAI's bet on chips and cheaper compute. Altman closed on ambition with a caveat: 'AI will cure cancer' is not enough — the point, in his telling, is aiming at a new renaissance.

At GTC Berlin on Wednesday, Nvidia expanded its open Agent Toolkit with the Agent Knowledge Foundation, a layer meant to ground enterprise agents in company data without moving the data, rebuilding workflows or changing governance controls. CEO Jensen Huang made data access the center of his keynote pitch: what turns agents into 'super agents,' he said, is access to a company's knowledge.

The foundation bundles CUDA-X libraries such as cuDF, cuGraph, cuML, cuOpt and cuVS with a new Auto-Ontology library that translates raw company data into business concepts — customers, products, orders — and maps how they relate. It also includes Nemotron Retriever and the new Kumo Structured open models (Kumo Tabular, Relational, Time Series and Forecast) for finding company information and making predictions from structured data.

Nvidia also unveiled the OpenShell Reference Architecture, a hardware-and-software design for containing and monitoring agents: models run on Vera Rubin systems, agent harnesses on Vera CPUs, and BlueField-4 chips run Nvidia's Sentry software to watch agent behavior and enforce policy in hardware. Anthropic, AWS, Google Cloud, Meta, Microsoft, OpenAI, Perplexity, SAP and SpaceX's AI unit are among those working with the architecture, and Nvidia also showed DSX POD, prebuilt AI factories it says can be installed in 14 days instead of six months.