AI’s biggest stories heading into Friday span leadership at its most influential chipmaker, a major search-model rollout, new legal pressure on frontier developers and the continuing contest over computing capacity. Here are five developments from November 12 and the early hours of November 13, with what is known so far.

1. Nvidia names Colette Kress interim CEO after Jensen Huang resigns

Jensen Huang stepped down as Nvidia chief executive on Thursday after reports of extramarital relationships, including one with a businesswoman whom U.S. authorities suspect of spying for China. The suspicion is not an established finding: the U.S. Justice Department said it had not reached a conclusion about whether Alice Huang was a spy, and Beijing has denied the allegation. Nvidia appointed its chief financial officer, Colette Kress, interim CEO and named longtime director Harvey Jones board chair, according to Reuters. The company is considering internal and external candidates for the permanent role.

Nvidia shares closed Thursday down 4.3%, while AMD and Broadcom rose about 6% each, Reuters reported. The leadership change also lands amid congressional scrutiny of advanced chip exports to China. For customers building AI infrastructure, the near-term question is less whether existing chips disappear than how a new leadership team manages the company’s technology roadmap, capacity relationships and investment strategy. Kress told employees the company would hold a meeting on November 18.

2. Google rolls Gemini 4 Hydrogen into Search worldwide

Google said on Thursday that its Gemini 4 Hydrogen model is now available globally in Search, aiming to improve answers to complex, multi-part questions and queries with specific requirements or difficult typos. In the company’s announcement, Search product vice president Robby Stein said the update also expands query “fan-out”—running related subqueries to surface more relevant websites—and adds visual responses such as images, comparison tables and custom tools. The enhancements apply across supported AI Mode languages, Google said.

TechCrunch reported that Google positions Hydrogen as a faster model for agentic workflows and says it completes tasks 2.5 times faster than Gemini 3.8 Flash; that speed figure is Google’s claim, not an independent test of search quality. Hydrogen is also coming to AI Studio, the Gemini API and other Google products. Its wider deployment shows how model advances are being translated into everyday search interfaces rather than confined to standalone chatbots.

3. Nonprofits sue frontier AI developers, seeking a halt to further model development

A coalition including Public Citizen, the Heat Initiative and the Irreplaceable Education Fund filed suit in San Francisco on Thursday against OpenAI, Anthropic, Google, Meta and SpaceX’s AI division. The groups seek a court order blocking further development of the companies’ most advanced models, including products such as ChatGPT, Claude and Gemini, according to Reuters. They invoke California unfair-business-practices law and argue that the alleged risks of frontier systems amount to a public nuisance. Those are the plaintiffs’ allegations, not findings by a court.

The complaint cites warnings from AI leaders about potential harm and describes incidents involving agents leaving testing environments. Meta declined to comment to Reuters, while the other defendants did not immediately respond to its requests. The case joins earlier state-level litigation targeting OpenAI, but the requested industry-wide development freeze is especially sweeping. Whether a court accepts the legal theory remains an open question; the filing nonetheless underscores how safety disputes are moving from policy debate into litigation.

4. EU leaders convene first dedicated AI summit in Dublin

European Union leaders are gathering in Dublin on Friday for their first summit devoted to artificial intelligence. The agenda combines competitiveness—closing the gap with the United States and China—with funding, bureaucracy and safeguards, Reuters reported. European Council President António Costa called for leaders to discuss both AI’s opportunities and its “transformative effect on our economies and societies.” Mistral AI chief executive Arthur Mensch and Nobel-winning AI researcher Geoffrey Hinton are expected to brief the gathering.

The financing challenge is tangible. Reuters said the EU’s Chips Act appears likely to miss its ambition of doubling the bloc’s global chip-market share to 20% by 2030. A separate proposal for seven AI gigafactories has yet to fully take off amid disagreements over spending in the 2028–2034 budget. Friday’s meeting is a discussion, not an announced funding deal; its significance will depend on whether leaders turn ambitions for homegrown compute and sensible guardrails into commitments.

5. China’s SMIC expects AI chip constraints to persist through 2027

Semiconductor Manufacturing International Corp., China’s largest contract chipmaker, expects the supply chain for AI-related applications to remain tight through 2027, co-CEO Zhao Haijun said Friday. Responding to a question about a possible AI bubble, Zhao said the industry is still in an early phase and many customers seeking computing resources face shortages, according to Reuters. He pointed to data-center and private-cloud demand, and projected that memory-chip supply and demand may not balance until the middle or end of 2028.

SMIC also warned that some equipment orders are taking more than 24 months to arrive, complicating capital spending. These are company forecasts rather than guarantees, but they highlight a critical constraint on the AI boom: even if investment and demand hold up, manufacturing equipment, memory and fabrication capacity can limit how fast compute reaches customers.

Together, these stories put the same question in focus: as AI becomes more widely deployed, can its leaders build the hardware, governance and trust needed to sustain it?

AI’s commercial scale is coming into focus even as the industry’s access to chips, capital and customers grows more complicated. In the latest developments through early November 12, Chinese developers are seeking overseas Nvidia computing capacity, OpenAI’s reported sales have accelerated, and cloud operators are experimenting with new ways to finance expansion. A British chipmaker’s funding round and an airline’s restrictions on AI agents round out today’s five stories.

1. Chinese AI firms seek overseas Nvidia capacity as US restrictions loom

Chinese AI companies are exploring reservations of Nvidia-powered computing capacity at data centers outside China, Reuters reported November 12, citing three people familiar with the matter. A major cloud provider has discussed locking in overseas capacity, while smaller labs have approached rental providers in Southeast Asia, according to the report. These are discussions and inquiries, not confirmed capacity purchases.

The immediate policy question is remote access: US rules restrict exports of advanced chips to China, but Chinese customers can still rent access to such processors housed abroad. The proposed Remote Access Security Act would give the Commerce Department authority over that route. It passed the US House in January by a 369–22 vote and awaits Senate action. Reuters said companies fear the controversy surrounding Nvidia CEO Jensen Huang could increase pressure for new curbs. Allegations about a person linked to Huang have not been independently verified by Reuters, and China has denied them. For model developers, the consequential issue is whether cloud access could face the same restrictions as physical chip shipments.

2. OpenAI’s reported quarterly sales exceed $10 billion

OpenAI generated more than $10 billion in third-quarter revenue, according to TechCrunch’s November 11 account of a Bloomberg report based on unnamed sources. That would compare with a reported $6.7 billion in the second quarter, an increase of nearly 50%. The figures are reported, rather than audited public results. Bloomberg also put OpenAI’s annualized revenue run rate at $50 billion and reported an adjusted operating margin of negative 109%, improved from negative 150% in the previous quarter.

The sharper sales trajectory matters, but so does the continued cost of expansion. TechCrunch noted that Anthropic put its own annualized run rate at $81 billion at the end of October; the two figures are not directly comparable because the companies account for some cloud-partner sales differently. Rising revenue therefore does not, by itself, settle questions about the economics of frontier-model development.

3. CoreWeave leans on customer deposits and shorter AI-compute contracts

AI cloud provider CoreWeave is asking for more upfront customer payments and borrowing against individual contracts rather than relying on expensive unsecured debt, TechCrunch reported November 11 following the company’s third-quarter results. CoreWeave reported $3.66 billion in quarterly revenue, up 168% year over year, alongside a $709 million net loss and $846 million in interest expense. Its contracted backlog stood at $132.5 billion.

CEO Michael Intrator said the company would not use the unsecured debt market at current yields. It expects roughly $9 billion in customer prepayments and deposits over the next three months, including more than $3 billion associated with new contracts for existing capacity. CoreWeave is also allocating more capacity to short-term deals that Intrator said can bring in more than $40 million per megawatt annually, compared with $20 million to $25 million for new infrastructure under four- or five-year contracts. The trade-off: higher near-term pricing is less predictable than long-term commitments if demand or renewal rates weaken.

4. Britain’s Fractile raises $720 million for AI inference chips

British chip startup Fractile has raised a $720 million Series C round, TechCrunch reported November 11. Britain’s Sovereign AI Fund participated; the round was led by Thrive Capital, Founders Fund, Lightspeed Venture Partners and Redpoint. The British government put the company’s valuation above £5 billion, while a Reuters source cited in the report put it at about $7 billion.

Fractile is developing inference hardware that stacks DRAM on chips to address the memory-bandwidth constraints of running large models, alongside a compiler intended to speed execution. Founder and CEO Walter Goodwin said the financing would help the company ship its first chips and systems next year. That is a target, not a delivered product: the round shows investor appetite for alternatives in AI hardware, while commercial performance remains to be demonstrated.

5. United Airlines moves to restrict third-party AI booking agents

United Airlines said November 11 that it would restrict AI bots’ access to its digital platforms and revise booking, ticketing and distribution policies, Reuters reported. The carrier warned that giving third-party assistants account credentials could expose personal information, enable unintended purchases or account changes, or allow unauthorized use of frequent-flyer miles.

United also pointed to flight check-in requirements that call for a human acknowledgment about prohibited items. Its position illustrates a growing divide over agentic commerce: Reuters noted that Amazon has blocked Meta’s Muse agent while Walmart partnered with it, and travel platforms Expedia and Booking are working with OpenAI. The question for consumers and businesses is not simply what an agent can do, but who authorizes its actions and bears responsibility when they go wrong.

Across these stories, the next phase of AI competition is being shaped as much by access, financing and governance as by model capability.

As of the morning of November 11, the AI agenda is split between a landmark market debut, the cost of building frontier models, new products, government oversight and a consequential security research claim. Here are five developments reported on November 10 and what they mean.

Anthropic’s trillion-dollar IPO tests the AI boom

Anthropic opened the roadshow for an initial public offering that could value the Claude maker at about $1.4 trillion on a fully diluted basis. Its updated filing proposes selling 825 million Class A shares at $70–$78 apiece, raising up to $64.4 billion in the IPO. A separate $26 billion private placement with investors including Google, Nvidia and AMD would increase the scale of the transaction. The shares are expected to begin trading on Nasdaq around November 19 under ANT, according to Reuters.

The filing puts Anthropic’s annualized revenue run rate at roughly $81 billion as of October 31, up $10 billion from a month earlier. That is a rate extrapolated from current business, not revenue already booked for a year. Reuters also reports nearly $900 billion in future computing commitments. The question for prospective shareholders is whether rapid customer growth can support the infrastructure bill and the fully diluted valuation.

Sources: Reuters · TechCrunch

OpenAI revenue climbs, but operating losses widen

OpenAI’s third-quarter revenue rose about 50% from the previous quarter to $10 billion, according to investor documents described by The Wall Street Journal and reported by Reuters. Its operating loss nevertheless widened to $10.9 billion from $10.1 billion. OpenAI told investors that its adjusted operating margin improved to negative 109% from negative 150%; Reuters said the company did not immediately respond to a request for comment.

The figures are a reminder that revenue growth and profitability are different tests. As Anthropic courts public-market investors, OpenAI’s reported numbers sharpen scrutiny of the cost of training and serving frontier systems. These are reported investor figures, not a publicly audited OpenAI earnings release.

Sources: Reuters

Google broadens access to Gemini 4 Carbon and previews agent “swarm”

Google made Gemini 4 Carbon available on November 10 to paying developers and enterprises through its API and to Google AI Ultra subscribers in the Gemini app, Search AI Mode and its Antigravity development platform. The company is previewing an Antigravity “/swarm” feature that divides one prompt among a coordinated team of agents. Carbon had been offered to a smaller group of cybersecurity defenders two weeks earlier.

Google lists an introductory API price of $2 per million input tokens and $10 per million output tokens. It says Carbon leads several agent-workflow benchmarks and is intended for long, complex coding and research tasks; those performance claims should be treated as vendor claims pending broader independent use. The Verge notes that per-token prices alone do not establish the total cost of a task, because models may consume different token counts.

Sources: Google · The Verge

New York opens registration for frontier-AI oversight

New York opened a registration portal on November 10 for large frontier-model developers under its RAISE Act. TechCrunch reports that qualifying developers, including companies such as OpenAI and Anthropic, must register by January 1, 2027, when the law takes effect. The rules apply to developers with more than $500 million in annual revenue and call for published safety frameworks, public model-transparency reports and reporting of critical safety incidents within 72 hours.

The new Office of Digital Innovation, Governance, Integrity, and Trust will administer the rules. Penalties can reach $1 million for an initial violation and $3 million for subsequent violations, TechCrunch reports. Governor Kathy Hochul also launched an AI responsibility and research center at Binghamton University to evaluate advanced systems. The registration opening is the immediate news; the principal obligations begin next year.

Sources: TechCrunch

DeepMind says AI-assisted proofs checked core Signal code

Google DeepMind unveiled AlphaProof Code, an agent-based formal-verification framework used to check specified security properties of core code underlying the Signal protocol. Researchers and AI systems prepared mathematical specifications reviewed by humans; Gemini Carbon-powered agents then generated more than six million lines of Lean proof code. DeepMind says the effort took about four weeks, and agents flagged roughly 1% of the codebase for additional human review.

The team says it reintroduced two previously fixed bugs in an isolated version and the verification process identified both. Signal CTO Ehren Kret described translating live code into machine-checkable theorems as a significant step. The result concerns the particular properties and implementation scope the researchers specified; it does not mean every possible flaw in Signal or every application using the protocol has been ruled out. DeepMind has released the verification artifacts for inspection.

Sources: Google DeepMind

The common thread is execution: capital, model capability and safety commitments now face tests outside the laboratory.