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OpenAI, Anthropic, Google Face Antitrust Class Action

Consumers filed an antitrust suit against OpenAI, Anthropic, Google and SpaceXAI, alleging they conspired to slow AI development in violation of Sherman Act Section 1. The complaint says Dario Amodei's essay 'We Must Pace the Frontier' was endorsed by Musk, Sam Altman and Demis Hassabis, forming an output-restricting cartel; plaintiffs seek class certification and an injunction.

Bloomberg Law News ·

Column: Keep US-China AI Safety Talks Separate

A column noted the US and China agreed to resume AI safety talks after a two-year pause, possibly this month. It argued the goal should be mutual visibility into AI capability concerns and management efforts rather than a package deal, and that the talks must stay insulated from broader US-China economic competition. Beijing has warned safety talks should not become a tool to contain China's tech rise.

The Virginian-Pilot ·

Two Lawsuits Against X.AI Dismissed

According to the Arkansas Democrat-Gazette, families dismissed two lawsuits against X.AI that had alleged the platform was used to create child pornography. The subscriber-exclusive report did not disclose the reason for dismissal or any settlement details.

The Arkansas Democrat-Gazette ·

World model companies keep product plans under wraps

World-model firms are attracting cash and buzz but stay secretive about their products and commercialization paths. AMI Labs co-founder Michael Rabbat said the company is still in a research and building phase and won't discuss product plans or timelines; World Labs' Marble is among the most developed products and its demos are largely capability showcases. The tech centers on automating spatial intelligence, with potential in robotics, interactive video and self-driving.

TechCrunch ·

ICLR Submission ID Sparks Confusion

A researcher said their ICLR submission ID was 47647 and asked the community why such a large ID appeared. The post offered no further context beyond the submission ID itself.

r/MachineLearning ·

Study flags 'linguistic illegibility' for LLM security

In a paper, James Mickens introduces the concept of linguistic illegibility: an LLM's externalized language and mechanistically probed linguistic features may not reflect its internal computation. Security mechanisms relying on linguistic self-reporting, such as chain-of-thought monitoring, constitutional self-critique and activation probing, can therefore never be fully sound; sandboxes need isolation techniques that don't depend on reading a model's linguistic state. The author calls taint tracking a promising approach and suggests robust virtualization and third-party auditing as complements.

Hacker News ·
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