The AI Wire ●

OpenAI published two documents on November 5: a National Community Compact covering every future compute campus it owns and operates, and a Compute Campus Policy Blueprint asking policymakers to impose comparable rules across the industry. The timing is direct: they land the day after midterm results in which governors promising data-centre pauses won in Texas and Georgia and 33 local limits passed or led.

The compact commits OpenAI to pay the full cost of the electricity it uses and the infrastructure needed to serve its sites, to provide financial assurances protecting other customers if a project is delayed or cancelled, and to publish site-level water and electricity use, construction plans and independent noise studies. It will not require public officials to sign nondisclosure agreements — with narrow exceptions for security and trade secrets — each campus gets a water plan favouring closed-loop or low-water cooling, a local point of contact, early resident engagement and a public progress report every year.

OpenAI points to money already committed as the model: an $80 million package for community priorities in Effingham County, Georgia, including a $4.8 million grant for free school meals for all 14,000 county students and $2 million for a local park, plus a joint $6 million childcare commitment with SB Energy in Pike County, Ohio. For its Project Camellia campus, OpenAI is contracting 3.2 gigawatts from Georgia Power in phases between 2028 and 2032, with the utility able to cut deliveries by up to 1,000 megawatts when the grid strains. The documents build on OpenAI's January Stargate community commitments and its November 2 Grid Protectors launch — and OpenAI itself says voluntary promises are only a starting point.

OpenAI published research on November 4, 'A thousand fewer paths to root,' describing a mid-October run in which an autonomous pipeline built on an upcoming cyber model hunted flaws in the Linux kernel. Scout agents picked 5,034 places to audit — about 2.8 million lines, roughly 7% of the kernel — and the pipeline turned 2,308 candidate findings into 1,724 dynamically reproduced vulnerabilities.

After variant analysis grouped exploits tracing back to the same flaw, OpenAI counts 948 distinct local privilege-escalation vulnerabilities, each backed by a working exploit — counted only when it produced a root shell on a stock desktop system with standard protections on — and a candidate patch. The whole run cost $1,213,430 in API credits, with exploitation the most expensive stage at $775,929; OpenAI values the haul at $18.9 million to $66.3 million at past bug-bounty contest rates, and puts the model's outright incorrect analysis at 3.1%.

The bounds matter: 948 is a count of distinct flaws with candidate patches, not fixes already on anyone's machine, and the post names no CVE identifiers, kernel versions or subsystems. Ten days after the scan, OpenAI says 61 flaws had already been patched upstream, 43 had patches in staging and 299 were being reported and discussed. The work sits under Patch the Planet, part of OpenAI's Daybreak programme, with human review before anything reaches a maintainer.

OpenAI launched ChatGPT Images 2.6 on November 4, adding native animated GIF creation to ChatGPT and Codex. Users can turn a written prompt or an uploaded photo into a looping GIF, then change its speed, revise individual frames and share the result — a one-step route ChatGPT did not have before.

The release is available globally across all subscription tiers on web, desktop and mobile, and OpenAI says image volume now exceeds 4 billion images a week across ChatGPT, Codex and the API, up from more than 3 billion at the Images 2.5 launch on September 8. Images 2.6 also adds reusable reference images, aimed at keeping a subject consistent across successive edits.

For developers, OpenAI added two API models: GPT-Image-2.6 Flare, positioned for faster generation — RuntimeWire reports output in as little as six seconds and generation about 50% faster — and GPT-Image-2.6 Sunburst, positioned for higher-quality output and consistency across edits. The split mirrors the 2.5 lineup, separating fast draft work from premium production work.

OpenAI announced on November 4 that it will acquire Pierre Computer Company, the small developer-tools startup behind Code Storage, a Git hosting service built for AI apps and coding agents. Code Storage will be integrated into Codex; Pierre's open-source projects will remain open source after the deal closes.

Codex users have already touched Pierre's work: its Trees library powers file browsing in the Codex app and its Diffs library powers change review. Code Storage is used by agent builders including Lovable, Bolt and Amp for code, memory files and documents. Pierre was founded by Jacob Thornton, a co-creator of Bootstrap, and Ian Ownbey, an early Twitter engineer, and raised a $22 million Series A in November 2025.

No price was disclosed, and the deal still needs regulatory approval; until it closes, the two companies remain independent. Axios, which broke the news, framed it as OpenAI going after Microsoft's GitHub — and it landed the same day Meta acquired Conductor, the parallel coding-agent startup, underlining that the coding race has moved from generating code to the infrastructure around it.

India has become ChatGPT's largest market globally by weekly active users, OpenAI India Managing Director Prabhjeet Singh said in an interview with The Economic Times published November 3 — his first media interview since taking the job. Singh said the Indian user base has doubled since January 2026, crediting users weaving the chatbot into everyday work, study and business.

The milestone moves India up from second place. In February 2026, CEO Sam Altman put India at more than 100 million weekly ChatGPT users, behind only the United States. OpenAI has not disclosed a fresh absolute count alongside the new claim, and Singh gave no revenue figures — largest by users is not the same as largest by revenue.

Singh pointed to what comes next: more Hindi and vernacular voice features, Android-first product work, and announcements on UPI-linked payments in the coming weeks. India is also among Codex's largest and fastest-growing markets, he said, and OpenAI has partnered with Tata Consultancy Services on data centre capacity in India through the TCS HyperVault platform, starting at 100 megawatts and scalable to 1 gigawatt.

OpenAI released 'Early science acceleration experiments with GPT-5' on November 3, a paper co-authored with collaborators at Vanderbilt, UC Berkeley, Columbia, Oxford, Cambridge, Lawrence Livermore National Laboratory and The Jackson Laboratory. It compiles early case studies across math, physics, biology, computer science, astronomy and materials science in which GPT-5 helped researchers synthesise known results in a novel way, run powerful literature reviews, accelerate tough computations and generate novel proofs — and it documents the limitations alongside the wins.

Three cases carry the paper. Immunologist Derya Unutmaz's team spent months on a puzzling change in human immune cells; GPT-5 identified the likely mechanism within minutes from an unpublished chart and suggested the experiment that proved it. Mehtaab Sawhney and Mark Sellke were stuck on the final step of a decades-old Erdős problem, and GPT-5 contributed the idea that completed the proof. Sébastien Bubeck and Christian Coester were testing a common decision-making method used in robotics and routing; GPT-5 produced a clear example showing it can fail and improved a classic optimisation result.

OpenAI's own framing keeps the human in charge: GPT-5 'does not run projects or solve scientific problems autonomously,' but shortens parts of the research workflow in expert hands. The paper is also a positioning document for OpenAI for Science — the company cites a survey in which 60% of US respondents said scientific and medical breakthroughs reach them too slowly — so the case studies are best read as selected examples with named external collaborators, not as a controlled measure of how much faster science now moves.

OpenAI formally showed ChatGPT Voice working inside Finances on November 3: after connecting accounts, users can talk through their money out loud — which subscriptions they are paying for, which to keep, and what cancelling the rest could save. OpenAI directs users to chatgpt.com/finances to try it, and its Help Center lists Finances for Free, Go, Plus and Pro users in the US on web, iOS and Android.

Finances itself is not new — it launched as a Pro preview in May, reached Plus and Pro through the autumn, and expanded to Free and Go users on October 2, which is also when voice support first became available to those tiers, according to CryptoBriefing's research. Accounts link through Plaid (12,000+ institutions) with credit data through Experian as a separate connection; the access is read-only, so ChatGPT can see balances and transactions but cannot move money, pay bills or trade.

The November 3 announcement is the showcase, not the first availability — but it moves voice from a quietly shipped capability to the way OpenAI is now pitching the feature. What OpenAI has not published is any date for Finances outside the US.

ChatGPT's volume of search-like queries is now roughly one-fifth the volume of Google's, consumer product lead Adam Fry said at an OpenAI-hosted dinner in New York on Monday night, in a fireside chat with Big Technology's Alex Kantrowitz published November 3. Fry's definition is narrow: a search is a user question that makes ChatGPT look something up on the web — current information about people, places or things, plus some finance and health questions. OpenAI did not disclose which Google baseline it divided into, and no independent firm has checked the comparison.

The same conversation put fresh numbers on ChatGPT's scale: 1.2 billion weekly active users, up from 1 billion over the last two months at roughly 100 million a month; 1.5 billion images created a week; and 250 million weekly users of voice input, counting dictation and voice conversations. Gizmodo noted the framing would make ChatGPT the world's second-largest search engine by volume — and that such numbers are exactly what a company says publicly ahead of a planned IPO.

Treat the growth timeline with some care: Fry described the jump from 1 billion to 1.2 billion as happening over the past two months, but The Verge was already reporting the 1.2 billion figure on September 29, so the timing of the increase is unclear. The one-fifth figure is OpenAI's own estimate using its own definition — a company claim about query volume, not a measured share of the search market.

OpenAI said on November 3 that ChatGPT and Codex are being used for mechanical design, electrical engineering and simulation work — creating and revising CAD models, designing printed circuit boards, preparing manufacturing drawings, configuring simulations and reviewing designs. The company announced the work in a thread on X and a same-day post on its site, with Chip Ganassi Racing and Mazda among the partners named.

OpenAI's own teams are the headline user: its hardware and infrastructure groups use the tools for robotics and compute-infrastructure design, and model usage by those teams has risen 23-fold since February, measured in tokens. In one internal example, two employees used GPT-6 Astra to design a test device in under a week as a side project, and a contract manufacturer produced a small prototype batch in under a month.

The bounds matter: the 23-fold figure is usage, not a measured productivity gain, and OpenAI's own prototype still required human correction on tolerances and assembly. This is a move from software production into work where errors carry manufacturing costs, with human review still required — not a claim that the models design hardware unsupervised.

Cat Wu, Anthropic's head of product for Claude Code and one of the tool's two public faces alongside its creator Boris Cherny, announced on X on November 3 that she has left the company after two years. 'Friday was my last day at Anthropic,' she wrote — Friday was October 30. Wu also oversaw Cowork, Anthropic's knowledge-work agent for non-engineers. Anthropic confirmed the departure to Business Insider; Wu gave no reason and named no next role, answering a question about taking time off with 'post agi!'

Wu joined in the summer of 2024, when Claude Code was still a small internal tool, and fronted its February 2025 research-preview launch video with Cherny. In her farewell post she charted how the product changed under her tenure: early users manually approved every permission prompt and mostly used Claude for questions and test-writing, while today auto-approve is the default and Claude handles large migrations and builds new products.

She is not leaving alone. Claude Code engineer Thariq Shihipar and desktop developer Anthony Morris both announced their own departures on October 24, so three members of the team have gone in under two weeks — weeks before Anthropic's planned IPO, with trading expected as early as the week of November 16. No successor has been named and no roadmap change has been announced alongside the exits.

Update, November 5: Wu has said where she went. At 00:25 UTC she posted that she is joining OpenAI to lead product management for Core Products, working with Thibault Sottiaux — Tibo — and OpenAI's product team to build agents that 'have your back and your team's, and keep you in control.' The post passed 2.5 million views within ten hours; OpenAI confirmed the hire to Business Insider, per later reporting, while Anthropic still has not named her successor. Austin Lau, who helped build Anthropic's growth function, also posted the same night that he had recently joined OpenAI.

SemiAnalysis released GDPx on November 2, a benchmark for general agentic capability spanning 11 domains the firm picked for where frontier models will earn their money: chip design, cybersecurity, biology, finance, legal, quant trading, recursive self-improvement, hardware design, materials science, alignment and software engineering. Version 1.0 has 206 tasks built with 14 specialist data partners, an eight-hour default time limit, and models running in their native harness — Claude Code for Claude, Codex for OpenAI's models, Antigravity for Gemini. New versions are planned every three to six months, with a public leaderboard at gdpx.semianalysis.com.

The headline number is how low the top score is: Claude Opus 5.5 leads at 12.0%, ahead of Gemini 4 Carbon at 10.9% and GPT-6 Astra at 9.6%. No model leads everywhere — Opus 5.5 wins quant trading, hardware and chip design, Carbon wins biology and edges software engineering, Astra wins recursive self-improvement and materials science — and under binary grading, finance and legal came back at essentially zero for every model. SemiAnalysis also notes Opus 5.5 and Astra are held back in cyber, biology and alignment by their own safety classifiers: strip those three domains out and Astra edges Opus 5.5, while Meta's Muse Wonder Full is rated the best available cyber model. Opus 5.5's lead is not cheap, at $51.41 per task against roughly $17 for Carbon.

Two caveats belong with the headline. GDPx is a paid SemiAnalysis product whose authors want it to become the benchmark of record, and its partner-built tasks are not independently audited. And a 12% top score reflects tasks deliberately chosen to be frontier-hard — it measures how far agents are from full automation of expert work, not whether they are useful today.

OpenAI published LifeVal on November 2, a benchmark that grades AI on everyday responsibilities instead of exams or code: finding childcare, enrolling a child in the right kindergarten, ordering groceries on a budget, managing household finances and getting through government paperwork. The task list was built from the American Time Use Survey, the Multinational Time Use Study and a new survey of 3,995 people on where they most want an assistant's help, across caregiving, health, education, household administration, personal finances, shopping and government services.

The headline score flatters its maker. GPT-6 Astra averaged 80.6% reward, up from 49.3% for GPT-5.2 in December 2025 and 80.0% for GPT-5.6, with example tasks such as organising flood volunteers at 98.0% and diabetes meal prep at 90.4%. OpenAI says it has used LifeVal internally for about a year to track and drive improvement on exactly these tasks.

The limits are structural: OpenAI built the test, chose the tasks, ran the scoring and publishes scores for its own models only, with no independent verification and no opening for third-party models to be graded. An average reward score is also not a share of real-world jobs finished correctly — LifeVal is best read as OpenAI showing which everyday jobs it is optimising ChatGPT for, not as a neutral league table.

OpenAI launched the Grid Protectors Program on November 2, committing the compute campuses it directly develops to reduce electricity use during grid emergencies and extreme weather. The company says it will work with utilities, regulators and policymakers on site-by-site arrangements setting how much demand can be cut, how quickly and for how long, and will publish further commitments as they are finalised.

The pilot is Project Camellia, OpenAI's planned 3,200-megawatt campus in Effingham County, Georgia. Under a 25-year agreement with Georgia Power, up to 1,000 megawatts — about 31% of the campus's peak load, and roughly the average electricity use of 700,000 homes — will be available for curtailment. OpenAI says it will pay the full infrastructure and electric-service costs of serving the site, with contracted power delivered in phases between 2028 and 2032.

The savings figures are the utility's projections, not results: Georgia Power projects about $950 million in annual customer savings from 2029 across its large-load portfolio including this deal, or at least $15 a month for a typical home using 1,000 kilowatt-hours. OpenAI itself concedes the limit of the idea — campus flexibility 'cannot replace investment in new energy supply and transmission' — and the campus, which drew local protests over the summer, is still in development.

OpenAI is expanding the models that power Dots, its always-on agents in ChatGPT. Tibo Sottiaux, who leads Codex, posted late on November 2 that the Dots model family is growing to include GPT-6 Astra and GPT-6.1 Terra, with 'some other models later,' and that Dots will automatically select the model best suited to each task — and can combine multiple models to complete a single request.

Terra is the practical half of the change: Sottiaux positioned it as faster, with a noticeably upgraded personality, and said it 'will help us bring dots to more people.' Dots launched at DevDay on September 29, each with its own cloud computer, and the expansion moves the product from a single-model setup to models split by scenario — which changes both its cost structure and its response speed.

What has not been announced is any change to who gets Dots: OpenAI has published no new plan arrangements alongside the model expansion, and Tibo's post does not mention ChatGPT Plus. Replies to the post ran far ahead of reposts, with many users asking about quotas and availability — questions the announcement itself does not answer.

Users opening the ChatGPT Classic app are now greeted with a retirement date: the app will officially be retired on January 30, 2027, 9to5Mac reported on November 2. The banner tells users to move to the new ChatGPT app and promises their full chat history comes with them. Classic is the old native app, renamed when OpenAI shipped a new Electron-based desktop app that put ChatGPT, Work and Codex under one interface — a change users criticised as confusing, which president Greg Brockman himself called 'kind of a mess.'

Separately, OpenAI is emailing users that it will begin testing a combined Chat and Work experience in the coming weeks, starting with a small group. The merged interface is meant to let users move from exploring an idea to having ChatGPT carry it through in one place — bringing in files and plugins, building a website or presentation, or acting on the web — while Codex remains a separate experience in the desktop app. Brockman had said the company hoped to eliminate the Work tab by the end of the year.

The merge is also where the money changes: as part of the transition, OpenAI plans the shared ChatGPT-and-Codex usage allowance the Wire covered on October 31, replacing separate limits. OpenAI says most users won't need to wait for usage to reset more often than today, that usage will depend on model and task, and that Unlimited Instant chat is included in plans and won't draw from the allowance.