US export controls bar sales of Nvidia's most advanced AI chips, including the H100, H200 and H800, to China, and Nvidia has said the rules have effectively shut it out of China's AI data center market. Lawmakers are weighing bills to tighten those controls further, with OpenAI and Anthropic backing them. Reuters published its review on November 13, a day after Jensen Huang resigned as Nvidia's CEO.

Reuters reported on November 13 that although Nvidia has said US export controls have effectively shut it out of China's AI data center market, a Reuters review identified more than $3 billion in Chinese computing projects built around the company's restricted processors.

According to Reuters, the review examined more than 150 Chinese procurement notices, investment plans, construction contracts and corporate disclosures, and found projects and equipment agreements with a combined reported value above 23 billion yuan, or about $3.2 billion. Reuters said the estimate includes planned investments, signed contracts and completed installations, and covers buildings, power systems and other infrastructure, not spending on Nvidia chips alone.

The projects named in Reuters' factbox include a proposed 6.2 billion yuan computing center in Fujian province specifying H100 chips, a 3 billion yuan center in Shaanxi specifying H100 and H200 processors, and a 1.5 billion yuan project in Inner Mongolia that proposes installing 625 H200 servers. Reuters also reported that a Gansu province center plans to install about 3,072 Nvidia processors, though documents did not show whether they were delivered, and that clusters using H800 chips are already running in Wuxi and Fujian.

Reuters said the projects stretch from coastal tech hubs to remote western provinces and reach local government ventures and universities, and that tighter controls could force delays, cost increases or redesigns around Chinese chips.

Watch for responses from Nvidia, the Commerce Department and lawmakers pushing the chip export bills, which this report may strengthen. Investigations into how restricted chips reached these projects could follow. Nvidia's November 17 earnings call, its first under interim CEO Colette Kress, may bring questions about China exposure and compliance with the existing rules. Chinese chipmakers may also gain if projects switch to domestic hardware.

Unusual Whales, citing Bloomberg, reported on November 13 that banned Nvidia chips ended up in a Shanghai AI data center linked to Alice Huang. The post says a company she founded, now majority owned by her sister, listed 52 Super Micro units with H100 or H200 chips, and that a Singapore Nvidia cloud partner bought 22 Dell servers with H800 chips that went to a Shanghai facility run by her husband, Kang Wei. This is a separate report from the Reuters review of more than $3B in Chinese projects built around restricted Nvidia chips, which is also in this deck.

Unusual Whales posted on November 13, citing Bloomberg, that banned Nvidia chips ended up in a Shanghai AI data center linked to Alice Huang. According to that post, a company Huang founded, now majority owned by her sister, listed 52 Super Micro units with Nvidia H100 or H200 chips, which cannot be sold to China without US approval. The post also says a Singapore Nvidia cloud partner bought 22 Dell servers with Nvidia H800 chips, and that the chips went to a Shanghai facility run by Huang's husband, Kang Wei.

Those details are secondhand: they come from Unusual Whales' summary of Bloomberg, not from a post by Bloomberg itself or from a document published in the scanned posts. The post does not name the Singapore partner or the Chinese company, and it does not say whether Alice Huang personally arranged the purchases.

Unusual Whales also wrote that US officials suspect Alice Huang was recruited by Chinese intelligence to target Jensen Huang, who resigned as Nvidia CEO this week. That allegation is unconfirmed in the posts scanned and should be treated as a claim reported by Unusual Whales, citing Bloomberg, not as a proven fact. This report is a separate event from the Reuters review, also in this deck, of more than $3 billion in Chinese computing projects built around restricted Nvidia processors.

Watch for Bloomberg's full article, for named responses from Super Micro, Dell, Nvidia and the Singapore partner, and for any US or Chinese official comment. Documents that identify the companies, the facility and how the servers moved would make the account easier to check. Congressional testimony by Jensen Huang, already expected in other coverage this week, may also take up the export control questions raised here.

Nvidia's official account posted on November 13 introducing GR00T 2, which it called its most advanced, open System One model for robotics research. The post says the model learns skills from human demonstrations, predicts how its actions will change the physical world, and can carry those skills across different robot bodies. Nvidia published a research page with its own test results for the model.

Nvidia's official account posted on November 13 introducing GR00T 2 as its most advanced, open System One model for robotics research. The post says the model learns skills from human demonstrations and predicts how its actions will change the physical world, and that those skills can carry across different robot bodies, reducing the need to teach each robot every task from scratch.

Nvidia's research page describes GR00T 2 as a foundation world action model that predicts future video and robot actions together, and says the models run on parallel grippers, dexterous hands and humanoids. According to that page, on 50 tasks never seen on the target robot, GR00T 2 succeeds 40% of the time with no demonstrations on that robot. Five demonstrations per task, which Nvidia says is under 3 minutes of robot data, raise that figure to 95% after a 30 minute fine tune on a single RTX 5090.

Nvidia also describes a faster variant, GR00T 2 Turbo, that it says can run on a Unitree G1 humanoid, with each prediction taking 124 ms on the robot's own Jetson Thor. Those figures come from Nvidia and have not been independently checked in the posts scanned.

Watch for Nvidia to publish weights, code or training recipes, and for other labs to try the model on their own robots. Independent tests of the official zero shot and few shot figures, and of skill transfer across robot bodies, would show whether the results hold outside Nvidia's setup. Follow up posts in the official thread may add demos or documentation links.

The official ChatGPT account posted on November 13 that a user's dot can complete purchases on their behalf once the user approves, and that ChatGPT Wallet lets agents pay without access to actual card details. OpenAI's accompanying announcement says the wallet was built with American Express, Mastercard and Visa, and that it is rolling out first to ChatGPT Pro subscribers in the US. Every purchase, OpenAI says, requires a security check such as Face ID or a fingerprint scan.

The official ChatGPT account said on November 13 that a user's dot can complete purchases on their behalf with the user's approval. The post says ChatGPT Wallet lets agents pay without access to actual card details, that every purchase requires a security check, and that the wallet is rolling out starting that day to dots, for Pro subscribers in the US.

OpenAI's announcement adds that the wallet was built in partnership with American Express, Mastercard and Visa. According to OpenAI, a user adds a card once, then reviews the items, the total and the selected card before each purchase and approves it with a security check such as Face ID or a fingerprint scan. After approval, the payment network provides a payment token, a substitute for the user's actual card details, and the charge goes to the selected card without the wallet sharing those details with the business or the agent. OpenAI says users keep existing card rewards and protections for eligible disputes, and that users transact directly with businesses.

OpenAI says the wallet will initially be available to ChatGPT Pro subscribers aged 18 and older in the US with eligible US issued cards, and that it is starting with limited availability so it can learn from real world use. The company also published a Commerce Partner Playbook for businesses and says it is working with fraud prevention and payment partners so risk systems recognize legitimate purchases made by agents.

Watch whether OpenAI expands ChatGPT Wallet beyond Pro subscribers in the US, and whether major retailers and payment systems accept the tokens without declining the charges. Official comments from American Express, Mastercard and Visa already appear in the announcement; later reports from banks or merchants will show how often purchases go through. If OpenAI later lets users set spending limits or categories in advance, that would be a further change to report here.

DeepSeek already offered a consumer App and an API for its models. On November 13, the official DeepSeek account said the capabilities behind the App, including search, files, links, safety and voice, are now available through the DeepSeek API. The company also posted an open source frontend demo and a guide to building a chatbot with those features.

DeepSeek posted on November 13 that the full DeepSeek App experience is now available through its API. The lead post lists search, files, links, safety and voice, and says developers can enable built in features with a few parameters or call standalone APIs such as OCR, ASR and TTS, including to recreate the full App in their own application. The post also links to an open source frontend demo that can import DeepSeek conversation history, to the demo's GitHub repo, and to DeepSeek's Build a Chatbot guide.

In a follow up post, DeepSeek said V4.1 Flash, the model listed as deepseek-flash, now supports these capabilities across the Messages, Responses and Chat Completions APIs, with tool calls and context assembly handled on the server. The post lists web search (web or images, with citations, when thinking is off), deep thinking search (search and read pages through multi step reasoning), file input (PDFs, Office files, images and more), URL reading (fetching links in user messages) and safety checks that screen inputs and outputs and return refusal indicators when risks are found. DeepSeek said public facing apps must enable safety checks, and that developers remain responsible for content moderation, applicable model registration and AI generated content labeling. Search, Fetch, OCR, ASR and TTS are also offered as standalone APIs.

A third post in the thread said extended capabilities incur tool usage fees on top of standard token charges. The pricing image DeepSeek shared lists Search and Fetch at $0.75 per 1,000 requests, OCR at $0.225 per 1,000 pages, ASR at $0.058 per hour (marked 50% off for a limited time, down from $0.116 per hour) and TTS at $0.225 per 10,000 characters (also marked 50% off for a limited time, down from $0.45 per 10,000 characters).

DeepSeek's API docs describe the same feature set and say the service runs the searches and URL reading, while the client shows the returned blocks and passes them back unchanged. The docs also say the open source demo stores the API key, conversations and uploaded images only in the browser.

Watch for developers to ship apps that reuse the DeepSeek App's search, file and voice features, and for whether the standalone OCR, ASR and TTS APIs get used outside chat products. The limited time ASR and TTS discounts may end, which would change the cost of voice features. It is also worth watching whether DeepSeek extends the same built in tools to models beyond V4.1 Flash, and how safety check requirements are enforced for public apps.

Reuters reported on November 13, citing an internal Amazon document and people familiar with the matter, that Amazon is planning an initiative called World Product Graph. Watcher Guru shared the news on X. AI shopping agents from rivals such as Google and OpenAI are starting to compete for where people research and buy products.

Watcher Guru posted on November 13 that Amazon plans to collect data on nearly every product sold on earth to compete with Google and AI shopping tools. The post is based on a Reuters exclusive published the same day.

Reuters reported that the initiative, called World Product Graph, seeks to gather data on virtually every item for sale, whether Amazon stocks it or not, according to an internal document and people familiar with the matter. The document, written like a press release, carries an aspirational release date of October 1, 2027, and Reuters said it could not determine if or when the plan will be carried out.

According to Reuters, the plan relies on brands and retailers contributing product data and on Amazon crawling other retailers' websites. The document says Coca Cola and Bayer have signed up to contribute data. It also says many answers from Amazon's AI shopping assistant Rufus are factually wrong or incomplete, and that running its roughly 83 million weekly searches is expensive. Amazon told Reuters the usage figures are significantly outdated and that its data shows Alexa for Shopping is about 97% accurate globally.

Reuters cited a 2025 Morgan Stanley report showing 16% of online shoppers start product research on Amazon compared with 57% on Google.

Watch for Amazon to confirm the plan or launch parts of it, and for how brands and retailers react to Amazon crawling their sites. Legal questions over scraping and data access may follow. The plan also signals tougher competition with Google, OpenAI and Meta over AI shopping agents, an area where Amazon has already moved to limit outside agents on its store.

Natasha Bertrand of CNN reported on November 13 that US intelligence intercepts in the spring indicated an affair between Jensen Huang, then Nvidia's CEO, and an executive at Megaspeed, a firm under investigation for possibly diverting sensitive technology to China. According to sources familiar with the matter who spoke to CNN, officials asked for the American in the intercepts to be unmasked, the person was identified as Huang, and Secretary of State and National Security Adviser Marco Rubio drafted a classified memo that went to a small group of senior officials, including at the White House. CNN names the Megaspeed executive as Alice Huang.

Natasha Bertrand, a CNN national security correspondent, posted on November 13 and linked to a CNN report that US intelligence intercepts in the spring indicated an executive of Megaspeed was having an affair with a US person. Sources familiar with the matter told CNN that the American was first masked in the reporting, a standard privacy step, and that officials then asked for the name to be unmasked, revealing former Nvidia CEO Jensen Huang.

According to those sources, Secretary of State and National Security Adviser Marco Rubio drafted a memo summarizing the intelligence and sent it to a very small group of senior US officials, including at the White House. CNN says it is unusual for a US person's identity to be unmasked, and that such a request typically has to come from a very senior official.

CNN names the Megaspeed executive as Alice Huang and says Rubio wanted officials to be aware of the relationship when they dealt with Jensen Huang. Sources told CNN the memo was not written specifically for President Donald Trump, but that he was briefed more than once, including verbally by Rubio aboard Air Force One in May, when Huang joined the president's travel group to China.

A person familiar with Trump's response told CNN he appeared at least partly focused on the affair as an embarrassing personal matter and also voiced concern for the US economy. After Huang resigned, CNN reports, Trump said the former CEO was "going through hell," was concerned for his wife and children, and said the question of whether Alice Huang was a Chinese spy was unsettled.

CNN says Alice Huang had been an important National Security Agency target by the spring, and that Justice and Commerce began an investigation into her firm in 2024 as part of a broader probe into shell companies suspected of diverting restricted Nvidia chips to China. Officials still disagree on her relationship with the Chinese government, CNN has reported, and Attorney General Todd Blanche said on Thursday that Justice and the FBI have reached no conclusions about who she is or is not.

Watch for any official confirmation of the memo, and for what investigators say about Megaspeed and Alice Huang as Commerce and Justice continue their work. Nvidia reports third quarter results on November 17, and further official comment from the White House or from Huang could change how this report is read. Any public statement from Rubio, or a denial from Huang, would also test the sources who spoke to CNN.

Maggie Haberman of The New York Times posted on November 13 a passage from a Times story she wrote with Julian E. Barnes and Jonathan Swan. The passage says US intelligence concerns that Alice Huang was spying for Beijing were taken so seriously that President Donald Trump was briefed twice, late last year and again this spring. This is a separate story from David Sacks's later dispute with the Times. No official New York Times account post of this article cleared 100,000 views in this scan, so Haberman leads.

Maggie Haberman posted at 8:37 PM ET on November 13 and quoted a New York Times story published the same day, written with Julian E. Barnes and Jonathan Swan. The quoted passage says, "The concerns in the U.S. intelligence community that Ms. Huang was spying on behalf of Beijing were taken so seriously that Mr. Trump was twice briefed on it, late last year and again this spring." Haberman tagged both co authors and added "me," marking the post as coming from the reporting team.

The linked Times story is titled "Nvidia Scandal Prompts Questions of What It Means to Be a Spy." The card text on Haberman's post says US intelligence agencies believe a woman who had an affair with Jensen Huang was a Chinese asset, and that they are still assessing more about her role. Those are the Times's characterizations, not an official US finding in the posts reviewed here.

The official New York Times account did not post this article with 100,000 or more views in this scan. Julian Barnes reposted Haberman's post, but that repost had only 127 views. Haberman therefore leads, and the Times article is linked and attributed.

This reporting sits next to, but is not the same as, two other stories already in this deck. CNN, in a separate report led by Natasha Bertrand, said President Trump was briefed more than once, including verbally by Secretary of State and National Security Adviser Marco Rubio aboard Air Force One in May. The Times account adds a count of two briefings and an earlier window, late last year, as well as this spring. David Sacks later argued that Times coverage of Alice Huang relied on unconfirmed claims; that dispute is a separate opinion story.

Jensen Huang resigned as Nvidia's CEO on November 12. Officials, including Attorney General Todd Blanche, have said in earlier coverage that Justice and the FBI have reached no public conclusion about who Alice Huang is or is not.

Watch for any on the record confirmation from the White House or from US intelligence that those two briefings took place, and for how the Times timeline sits beside CNN's account of a May briefing on Air Force One. Nvidia reports third quarter results on November 17, which may bring questions about what the board was told. A public statement from the administration, or a denial, would test the Times's unnamed official sources.

Megaspeed International is a Singapore based cloud company that US agencies suspect of routing restricted Nvidia chips to China, and CBS News reports it was previously led by Alice Huang, whose relationship with Jensen Huang preceded his resignation as Nvidia CEO. The Commerce Department controls the US Entity List, which restricts access to American technology. Megaspeed was still not on that list as of November 13, according to TokenPost.

Treasury Secretary Scott Bessent told CNBC's Squawk Box on November 13 that the Treasury, War and State departments and the Office of the US Trade Representative "were in favor of putting Megaspeed on the entity list for months." According to CBS News, he added that "Commerce has the pen" and that questions about its internal processes should go to the Commerce Department, which Howard Lutnick leads.

CNBC reported that the remarks followed an Axios report that Bessent had asked Lutnick in the White House Situation Room why he resisted export controls on Megaspeed. A Commerce spokeswoman told CNBC there was "no such conversation," and Bessent said, "We don't repeat conversations in the Situation Room." He said he was frustrated because President Trump had made clear that China should not receive Nvidia chips above H100s, and that any leakage hurts US companies in the AI race.

Bessent also turned to Nvidia itself. "The real story here should be: Did Nvidia know their client," he told CNBC, adding that anyone at the company should be held accountable if it sold to obvious shell companies acting as pass throughs. TokenPost reports that Megaspeed denies illegal transfers.

CBS News reported, citing a US official, that Lutnick agreed to testify before the Senate Banking Committee on December 10. CNBC said Sen. Tim Scott had announced that both Huang and Lutnick were asked to testify.

Watch whether Commerce adds Megaspeed to the Entity List before Lutnick's Senate Banking Committee appearance on December 10, and whether the White House settles the dispute in public. Nvidia is set to report third quarter results on November 17, its first report since Huang left, where customer screening and China exposure could draw questions. The Justice Department's criminal investigation of Megaspeed, reported by TokenPost, is a separate track that could move on its own timeline.

Georgi Gerganov, the creator of llama.cpp, posted on November 13 that llama.cpp v1.0.0 is now available, and linked to a Hugging Face blog post by the ggml org team. The blog says the 1.0.0 release covers both the llama.cpp inference library and the ggml tensor library, and that future major version bumps will mark incompatible changes to the public C API. The project has been used for local and private model inference for about three and a half years.

Georgi Gerganov posted on November 13 that llama.cpp v1.0.0 is now available, and linked to a Hugging Face blog post titled llama.cpp v1.0.0 : A stronger foundation for the local AI ecosystem. The blog, published the same day by the ggml org team, says the release highlights the project's responsibility to downstream developers who depend on its library interfaces.

According to the post, the 1.0.0 milestone applies to both llama.cpp, the C and C++ library for LLM inference (libllama), and ggml, the tensor library (libggml). Going forward, the team says both projects will use semantic versioning: a major version bump for a breaking change to the public C API in the include headers, a minor bump for backward compatible features or API additions, and a patch bump for bug fixes with no API change.

The blog says the project began about three and a half years ago and that llama.cpp currently supports more than 150 architecture variants as well as mainstream speculative decoding methods. It also lists distribution channels including Docker, Debian, Homebrew, conda forge, MacPorts, Winget and an XCFramework for iOS and macOS, and says hardware support for CI runners comes from NVIDIA, AMD, Qualcomm, Arm, IBM and Intel.

Watch the project's release notes and packaging channels for how strictly the new versioning is applied, and whether downstream apps start pinning to the 1.0 API. Follow up posts may cover desktop apps or additional backends. Independent packagers will show how quickly v1.0.0 lands in Homebrew, Debian, Docker and other channels named in the blog. If a later release has to bump the major version, that will test the new contract.