Geoffrey Hinton Warns of Major AI Incident by 2027

Nov 4, 2026
Geoffrey Hinton predicts that a major AI attack or failure could occur by 2027 and calls for independent model testing before release.

Geoffrey Hinton warned that a major AI attack or failure could occur later in 2026 or during 2027, according to ResultSense's account of a Guardian interview. He said such an incident could cause a power brownout or disrupt financial systems for a week.

Hinton compared recent incidents involving OpenAI agents and Hugging Face with the Three Mile Island accident, describing them as warnings of a potentially larger event. He said he did not trust OpenAI chief executive Sam Altman "at all", and that Altman, Elon Musk and Mark Zuckerberg understand the dangers, adding: "They'd rather have the money." The Guardian report carries no response from the three.

Hinton called for an independent authority to assess AI models before release, similar to how the US Food and Drug Administration reviews medicines. Companies would need to provide statistical evidence that a model's expected benefits outweigh its potential harms before launching it. He cited thalidomide to argue against releasing products first and settling harms in court later.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like AI Policy Brief or Daily AI Brief.

Also, consider following us on social media:

AI Safety & Regulation AI Brief AI Brief (X)
Free newsletter

AI Policy Brief

Weekly report on AI regulations, safety standards, government policies, and compliance requirements worldwide.

Guide
Humanoid Robot Makers

Humanoid Robot Makers

Companies building humanoid robots, from startups to Tesla and Boston Dynamics

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.