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Anthropic shared on November 4 how its biology research team worked with Claude to map the first three-dimensional structure of a vault particle from bacterial life. Vaults are hollow, barrel-shaped protein assemblies — among the largest structures in human cells — first identified in 1986, whose biological purpose is still unknown.

The team searched roughly 15 billion predicted protein sequences for distant relatives, finding candidates across 29 major bacterial groups and four archaeal groups, and tested 44 in the laboratory. A phage-derived protein called L05 assembled into a complete vault of 96 copies of itself, about 54 nanometres long and enclosing roughly 25 percent more volume than mammalian vaults.

Claude contributed throughout, from protein searches and DNA design to purification and microscopy analysis: a chromatography approach cut isolation from about three days to roughly 90 minutes, and the first complete cryo-EM model emerged within 34 hours, against weeks conventionally. Anthropic also documents the failures — an additive that interfered with DNA delivery cost two weeks, and Claude produced an inaccurate map after skipping a standard processing step — both corrected under closer supervision.

Anthropic struck a content and data licensing deal with the Associated Press just before the US midterm elections — the first time it has ever paid a digital news publisher for content, Adweek reported, citing two people familiar with the matter. On Election Night, Claude users asking for polling updates saw up-to-the-minute information provided by and attributed to the AP.

Neither company commented on the record, and the financial terms, duration and scope beyond election data were not disclosed. Anthropic had announced earlier this fall that Claude would show up-to-date results on election night and in the days that follow; the AP deal is what supplied that live data.

The move is a notable strategy shift. Anthropic had argued that its use of publisher content was permitted under fair use and declined the licensing talks OpenAI and Google pursued — the AP was, in fact, the first publisher both of those companies signed. The deal also surfaced days after Anthropic's October 26 S-1 filing, as it prepares for an IPO while facing active copyright lawsuits.

Adobe announced on November 4 that its CX Enterprise Coworker — an agentic teammate for customer-experience work — is now available inside the AI platforms enterprises already use: ChatGPT as a plugin, Claude, Databricks Genie, Gemini for business and Microsoft Copilot. Availability inside Amazon Quick, IBM and Snowflake is expected to follow.

The Coworker brings agent-led customer-experience workflows into those tools, drawing on a brand's customer data and brand intelligence where the work already happens. Adobe also launched new connectors built as MCP server integrations with partners including Amazon Ads, Databricks Genie, Demandbase, an ads MCP server for Meta campaigns, Microsoft Work IQ, RainFocus and Snowflake Cortex AI, so the agent can take action in those systems rather than only answer questions.

It is another sign of where enterprise agents are heading: the major chat platforms are becoming the front door, and vendors like Adobe compete to be the specialist agent working behind whichever door the customer chose. Adobe did not announce pricing for the Coworker in the release.

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.

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.

Microsoft is replacing the standalone Word, Excel and PowerPoint agents in Microsoft Copilot with document-creation and editing capabilities built directly into the Copilot app, according to admin message centre notice MC1536062 published November 3. Users with a Microsoft 365 Copilot licence will ask Copilot Chat to create or refine a document, workbook or presentation directly, instead of Copilot invoking a separate agent for each app.

The change affects every user with a Microsoft 365 Copilot user subscription licence who currently has access to the standalone agents. Microsoft says the update introduces no changes to data processing.

The rollout is staged: worldwide general availability begins in mid-November 2026 and is expected to complete by late December 2026. It is the latest step in Microsoft's consolidation of Copilot into a single app and a single chat surface, following the August merger of the consumer Copilot and Microsoft 365 Copilot apps.

Meta said on November 3 that it is raising $15 billion through a five-part US dollar bond offering, turning to debt markets to help finance its accelerating AI infrastructure spending, Reuters reported. The sale includes $3.25 billion of notes due in 2031 at a 5.85% coupon and another $3.25 billion due in 2033 at 6.25%, according to a regulatory filing.

It is Meta's third big trip to the bond market in little over a year, after a $25 billion sale in April and a $30 billion offering last year. The new debt also lands days after Meta expanded plans for what could become a $97.5 billion equity raise.

Meta has said it expects capital expenditure of $135 billion to $145 billion this year, largely driven by AI. Moody's rated the new debt Aa3, and Meta's total debt stood at $83.67 billion as of September 30, per LSEG data — a striking shift for a company that historically funded growth from cash on hand.

Google said on Tuesday, November 3 that Google Search, Gemini, Gemini Notebook and Gemini in Classroom will be switched off by default for K-12 student accounts, staying off until a school administrator explicitly turns each one on. The company said it was acting because schools, teachers, researchers and policymakers had asked for control, and published a 29-page report on AI in education the same day. Guided Learning, already available in Google Classroom from November 3, will also reach Search for student accounts through a pilot in selected US schools later in November. Google gave no date beyond 'the coming months'; The New York Times reported early next year.

The catch is in the bundle. Each product can be enabled separately, but the Search a school switches on still includes AI Mode and AI Overviews, which Google describes as part of the product — there is no way to give students classic Search and leave the AI layer off. 'Search and A.I. are deeply integrated,' Chris Phillips, Google's vice president for education, told the Times. New York City Mayor Zohran Mamdani accused Google of using monopoly power to force AI into public schools, and a Community Note on Google's own response post made the same point: schools cannot enable basic Search without the AI features.

The stakes are the habits of the education market: Gemini Notebook — the renamed NotebookLM — counts more than 30 million users, and defaults set in school accounts shape what a generation reaches for first. Districts that keep AI off entirely will now lose student access to Google Search altogether, and students will see a message saying it is not available.

Update, November 4: Google spent Tuesday playing defence. In a blog post titled 'Designing responsible AI for learning' and a post on X, the company said the policy was meant to give schools more choice, repeating that Gemini, Gemini Notebook and Search are off by default and that 'schools are in control,' able to turn each on as they see fit. It also said Search for schools is being updated for learning: AI Mode and AI Overviews will offer step-by-step Guided Learning through problems so students do not simply get quick answers to schoolwork. The response did not address the central criticism — that a school cannot switch Search back on without the AI layer that comes bundled with it.

An adviser to Europe's highest court said on November 3 that Google's Gemini chatbot may breach publishers' copyright when it retrieves their articles and reuses them to generate answers, Reuters reported. Advocate General Maciej Szpunar's opinion in the case brought by Hungarian news operator Like Company draws a line: a publisher's reproduction right may be infringed when a chatbot gets around a paywall or other technical barrier, or reuses 'the form of expression of that publication in a recognisable manner.' The mere facts in a story are not protected — only their specific expression.

The same opinion cuts the other way on training: using copyrighted material to train large language models is 'freely permitted under the text and data mining exception,' Szpunar said, and there was no evidence Google had used Like Company's articles to train Gemini. The disputed activity covers June 2023 to May 2024. Google welcomed the training point and said Gemini 'learns linguistic patterns to create original outputs,' with publisher opt-out controls; the European Publishers Council argued publishers should not have to choose between search visibility and protecting their rights.

An advocate general's opinion is advisory, not a judgment — but the Court of Justice follows the majority of them, and it will rule in the coming months. A ruling against Google could force it to pay fees for content reused in AI answers, at a moment when publishers say AI summaries are replacing the search traffic they used to receive.

Google announced on November 3 that its AI Educator Series, a no-cost on-demand training programme giving teachers practical AI skills, will expand in the coming months to Brazil, Mexico, Spain, Australia and sub-Saharan Africa. The series first launched in the US earlier this year and has since reached India, Korea, Malaysia, the Philippines, and the UK and Ireland.

Teachers already in the programme are using Gemini and Gemini Notebook to turn topics into comic strips, podcasts and infographics, build lesson plans and assessments, and cut preparation time. Google says September sessions in India trained 80,000 educators, Malaysian teachers report saving three to five hours of prep per topic, and a partnership in the Philippines aims to bring AI training to over one million educators.

New November modules go live in the US on November 4, focused on saving teachers time: building interactive assessments with instant feedback, guiding students through game-based learning, and spotting assignment questions that invite shortcuts. Educators who complete the training earn a badge and join the programme's global community.

AI data centres have become a campaign issue in today's US midterm elections. The Information's analysis of candidate platforms and public statements, published November 1, found at least one major-party nominee backing a data centre moratorium in 21 of the 36 states electing a governor today — in Michigan, New Hampshire, Ohio, Oregon and Texas, both nominees back a pause — and concluded moratorium backers could win in up to 15 states, with pause supporters polling ahead in Maine, New Mexico and New York and seven more races close.

The underlying numbers are contested, and worth reading with care. SiliconNoon notes the dataset both The Information and WIRED draw on — MultiState's candidate tracker, published September 18 — flags a moratorium candidate in 16 states and roughly 20 candidates in total, with only five or six of those races genuinely competitive. Of the candidates not calling for a moratorium, most back at least one other restriction, most commonly ratepayer protection so campus power costs do not land on household bills; Hawaii is the only state where neither nominee campaigns on data centre limits.

Three sitting governors have already acted: New York's Kathy Hochul, Texas's Greg Abbott and Oregon's Tina Kotek have all paused approvals for new large-scale data centres, and Anthropic listed state-level moratoriums as a business risk in its IPO prospectus last week. Whatever today's results, the count that matters for builders is local as much as statewide — Ohio alone has at least 125 local moratoriums in effect and 14 local ballot measures today.

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.

xAI introduced Data Bot on November 2 as a Shared Bot inside Grok Bot, built by the SpaceXAI data science team to handle warehouse queries and analytical work for colleagues across the company. The team said its small size had become a bottleneck for straightforward questions that still needed specialist knowledge, so it encoded that knowledge into a bot anyone can message.

What Data Bot carries is a maintained, shared skill set: metric definitions and query logic, guidance on setting up A/B tests and checking results for bias, chart and dashboard conventions that can turn a chat answer into a Databricks or Hex dashboard, and dbt and data-engineering practices. A separate shared memory holds operational knowledge — who owns a pipeline, whether a past metric dip was a regional holiday — with team managers approving or rejecting proposed additions before they reach everyone.

xAI's examples are internal work, not a public product launch: a product manager investigating questions dashboards do not answer, a lifecycle marketer tracing what Braze campaign recipients did next during The X Subscription launch, and scheduled weekly metric reports posted into Slack channels. The company estimates Data Bot handled about 70 hours of work in the week before the announcement that would otherwise have gone to the data team, while complex analyses still stay with the humans.