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Monday 9 November 2026 edition

AI Watch, Monday 9 November 2026Fine-tuning a model erodes its safety guardrails

Masteria editorial team, led by Mathias Nizan · , 18:41

Nvidia's CEO admits an affair with an alleged Beijing spy, and Asian markets sell off on AI.

  • More quietly, research shows that a model's safety guardrails fade as soon as it is specialised.
14 stories14 sources7 min read
Top story

Nvidia's CEO admits an affair with an alleged Beijing spy

Jensen Huang, Nvidia's chief executive, admitted on Sunday 9 November to an extramarital affair in a memo sent to his staff and published on the company's website: "I was unfaithful to my wife. My actions hurt her and our children. There is no excuse."

The board opened an independent investigation that same day, following press reports that the woman involved, Alice Huang, an AI executive, had been recruited by China's Ministry of State Security to approach the chief executive.

The affair touches a company valued at around $4.5 trillion, which makes the chips at the heart of the technology rivalry between Washington and Beijing. Donald Trump backed Huang publicly, calling him "a good guy" and saying he should keep his job; Nvidia shares fell at the open.

In an interview filmed on 14 October, before the revelation, Huang was defending exactly that sale of chips to China, calling US export policy "a mistake" and stating that China "is not our enemy." The same man concentrates the suspicion of a foreign intelligence operation and Nvidia's line of defence in Washington.

SourceLe Monde

Europe and France

Villeroy de Galhau wants to anchor the recovery to three European projects

In an interview with Le Monde, the former governor of the Banque de France (France's central bank), who left his post in June, argues for repairing public finances through spending efficiency and three shared projects by 2029: artificial intelligence, energy and defence.

AI moves from the register of innovation to that of strategic European investment, on a par with the power grid and weapons. The argument targets both the funding of the social model and the continent's technological sovereignty.

SourceLe Monde

The "neoclouds" worry the stock market

Numerama details the model of CoreWeave, Nebius and IREN, these renters of computing power for AI (they buy chips, install them in data centres and rent out compute time). Their fragility comes from heavy debt taken on to buy processors that depreciate quickly, backed by rental contracts whose term poorly covers repayment.

When the market doubts demand for compute, these players fall first and drag down the rest of the sector.

SourceNumerama

Aboriginal art targeted by generated counterfeits

The Journal du Net reports the proliferation of fake Aboriginal works produced by AI and sold online, from coasters to canvases. The counterfeiting deprives Australian First Nations artists of income and dilutes a culture whose motifs carry ritual meaning. The case extends the European debate on training image models from protected works without consent or payment.

International

Asian markets sell off on AI

The stock markets of Taiwan, South Korea and Japan fell heavily, with Taiwan extending its longest losing streak since 2022, in a global correction of AI-linked stocks. Taiwanese authorities announced measures to restore investor confidence, and the index rebounded immediately.

In Sydney, an official at Australia's central bank, Sarah Hunter, warned that the scale of AI investment will fuel demand and weigh on prices in the short term, as the bank raises rates to contain inflation. Stock-market doubt and the energy bill for building data centres are starting to echo each other.

SourceBloomberg

The rights holders of Elvis Presley and Eminem sue Suno

The AI music generator faces two new lawsuits in the United States. The holders of the rights to Elvis Presley's work and the publisher of some major Eminem tracks accuse Suno of producing songs and lyrics that imitate the voice and words of these artists.

The Presley suit relies in particular on the Tennessee law that protects the right to one's image and voice (the "right of publicity"). Suno, which says it refuses to compose from an artist's name, was already facing lawsuits from record labels. The proceedings are multiplying around a single question: can a model trained on a catalogue reproduce its style without permission.

SourceThe Verge

Anthropic promises fortunes to its staff, on condition

Ahead of an IPO, the Journal du Net reports that the shares held by Anthropic's employees could represent around $200 billion, paid out on condition that they stay with the company. Between taxes and holding periods before sale, this wealth will remain virtual at first.

The arrangement works as a retention lock in a talent war where an experienced researcher commands a premium.

Apple speeds up on a Siri that acts

According to Mark Gurman (Bloomberg), Apple's general manager, John Ternus, is pressing AI chief Craig Federighi to speed up Siri's roadmap and deliver an agent able to act on your behalf, not only answer (booking, sorting, chaining actions across your apps). The stated goal is to compete with OpenAI's agents and Meta's Muse.

Federighi has already delivered a working version of AI Siri on a tight schedule, but Apple acknowledges it is behind on this agentic ground. The file measures the difficulty, for a company committed to on-device privacy, of keeping pace with a market shifting toward autonomous assistants.

SourceThe Verge

China and Asia

Cited in the analysis

Tencent's AI chief warns that models will master biology

Yao Shunyu, chief AI scientist at Tencent and a former well-known OpenAI researcher, said on Saturday, in a rare public appearance, that models will soon be powerful enough to master biology, with serious benefits and risks. State-of-the-art systems are increasingly applied to medicine and biology, where they can speed up the discovery of treatments.

Yao warns against the use malicious actors could make of them to design pathogens. The signal comes from a Chinese executive trained in the United States, at a distance from the usual Western discourse on AI safety.

Chinese tech out in force at the Lisbon Web Summit

From 9 to 12 November, the Web Summit brings a large part of the global digital economy to Lisbon. La Tribune notes the place taken by China, which in a few years has become a key player thanks to a competitive cost-performance ratio, from robots to autonomous vehicles. The push is happening on European soil, just as the Union debates its own capacity to fund AI.

Research

Research and papers

For technical teams

Fine-tuning a model for a domain erodes its safety refusals

A study posted on 9 November audits language models fine-tuned (retrained on a business corpus) for biomedicine. The authors measure, across several architectures and fine-tuning methods, abstention: the model's ability to refuse to answer when it does not know or when the request is dangerous. This abstention degrades with fine-tuning, even as domain performance improves.

A second paper from the same day, on the WMDP dataset, shows that the multiple-choice questionnaire format underestimates the danger: forced to tick a letter, the model (Llama-3.1-8B and Qwen3-8B in the experiment) gives up on refusing. The two results converge: we evaluate specialised models on what they get right, rarely on what they have stopped refusing.

SourcearXiv
The rest of the news

In brief

  • Meta opens its Muse agent to tools described in natural language

    Clubic reports that users can ask Muse, Meta's AI agent, to build a tool (gift tracking, wedding planning) by describing it in the conversation, then keep it up to date from connected services.

    SourceClubic
  • Microsoft files a patent for live video translation with lip synchronisation

    The system described rewrites in real time the speech of a filmed person into another language and redraws their lips so they articulate the translation.

    SourceClubic
  • Geoffrey Hinton wonders whether humanity would have been better off not developing AI

    The Nobel laureate in physics, a pioneer of neural networks, predicts a "Chernobyl" of AI this year or next, in the form of a massive failure of the power grid or the banking system.

    SourceClubic
The Masteria read

Specialising an open model on your data erodes its guardrails, and almost no one retests them

A 9 November audit shows that fine-tuning a model on your business data removes its safety refusals; customising an open model means retesting its guardrails afterwards, not only its accuracy.

A research team posts on 9 November an audit of language models fine-tuned for medicine. The result fits in one sentence: fine-tuning a model on business data (retraining it on your own corpus) erases part of its safety refusals.

The guardrails, those responses by which a model declines a dangerous request, erode without anyone having decided it, while medical accuracy improves. The organisation that measures the second ignores the first.

The same day, a second paper shows that safety tests in multiple-choice questionnaire format underestimate the danger: forced to tick a letter, the model gives up on refusing. The two signals point to the same place. We evaluate customised models on what they get right, almost never on what they have stopped refusing.

Set this work against the week. Yao Shunyu, who moved from OpenAI to Tencent, warns that models will soon master biology, both benefit and threat. Geoffrey Hinton, a Nobel laureate, predicts a major AI accident.

These statements remain views from above. The biomedical audit, for its part, describes a move that thousands of teams are already making: take an open model, specialise it on their files, put it into service.

Since 4 November, we have written that choosing and running an open model arbitrates your costs and your control of data. Its safety is the hidden face of this. Specialising a model requires one more step: replaying, after fine-tuning, the battery of refusals the model gave before, and treating any regression as a blocking defect, on the same footing as a bug.

A French organisation deploying an assistant on its health, legal or human-resources data inherits this risk without seeing it. The remedy is methodical before it is technical: who, in your organisation, retests the guardrails after each training run? As long as the answer is no one, the model you hardened on your data has also softened where it needed to hold.

The Masteria editorial team

Mathias Nizan, founder of Masteria
Mathias Nizan
Editor of AI Watch
Method

56 articles read, 14 kept

Selected on the morning of 9 November from 38 news feeds. Our method (in French)

Today's sourcesLe MondeNumeramaJournal du NetBloombergThe VergeSouth China Morning PostLa TribunearXivClubic

Next edition: Tuesday 10 November.

What the 9 November edition means for your teams

Nvidia's CEO admits an affair with an alleged Beijing spy. Does it touch your teams? Let's talk.

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