164 summarised stories about AI Regulation, each linking back to the original source. Browse all topics →
Sifted 2 weeks ago 31 ● 2 sources
Kanishka Narayan, the UK minister overseeing the country’s AI strategy, said he is reviewing how non-compete clauses and long notice periods are used after calls for reform. He said the work is happening “extremely rapidly” and mentioned a 24-day review. If implemented, the changes would reduce or rewrite non-compete terms and shorten notice periods for AI-related roles.
The Verge 2 weeks ago 15 ● 18 sources
Tech leaders signed the Joint Commitment On Frontier Responsibilities to self-regulate frontier AI safety under President Trump’s deal. The agreement was announced by Trump on September 2024 (yesterday in the article). The companies involved commit to shared safety responsibilities through internal self-policing rather than a new government regime.
Trending Topics 2 weeks ago 33
McDonald’s franchisees are being pushed to use a machine-learning pricing system that sets item prices by analyzing millions of daily transactions and competitor menu pricing for each location. The system calculates “the optimal price” for every item at nearly 14,000 restaurants. Since January, franchisees have faced added requirements to engage with the pricing consultant and tools, widening some price gaps according to operators, which McDonald’s disputes as a non-mandate tool.
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15 October 2026
Meta’s big move today wasn’t just another model release—it was a licensing-and-distribution statement. Muse Spark Open ships as an 816B-parameter, coding-optimized multimodal model with a 1 million–token context window and 42B active parameters per token, now available as downloads for developers (with restrictions) and deployable through Amazon SageMaker JumpStart into customer-controlled endpoints. The “open” part comes with strings: a custom Muse Model License, advance notification above $20 million revenue, and a required “Built with Muse Spark Open” attribution. Meta still keeps its top systems closed, but it’s clearly betting that more developers will build long-running agent workflows when they can run, fine-tune, and adapt the weights.
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