Moonshot's K2.7-Code cuts costs but skips independent benchmarks

Mistral is in talks to raise €3 billion at a €20 billion valuation, nearly doubling its Series C valuation of €11.7 billion. The funding round would value the French AI company at approximately $23.15 billion. The raise reflects continued investor appetite for large language model developers outside the US market.

Google researchers propose 'faithful uncertainty,' a technique that allows large language models to express qualified guesses rather than either confidently hallucinating or refusing to answer. The approach reframes hallucinations as 'confident errors' and enables models to hedge responses appropriately, preserving utility while maintaining trustworthiness. This addresses a core tradeoff in LLM deployment where eliminating factual errors typically forces models to abstain from answering questions they actually know.

Researchers from NYU, Columbia, Princeton, University of Maryland, Harvard, and Lawrence Livermore National Laboratory published a paper introducing Latent Context Language Models (LCLMs), a compression technique that reduces LLM input by 16x while maintaining accuracy better than existing methods. Unlike KV cache compression, LCLMs compress tokens before decoder processing, delivering 8.8x faster output on long-context benchmarks. The models are open-sourced on HuggingFace and designed to integrate into existing LLM stacks.

Anthropic has released Claude Fable 5, making its Mythos-class model available to the public for the first time. The model includes built-in guardrails that restrict responses in high-risk domains including cybersecurity and biology. This release marks a significant step in bringing advanced AI capabilities to broader audiences while attempting to manage safety concerns.