Science Corporation implants vision chip in first Stargardt patient

AI developers are shifting from relying on readable 'chains of thought' to understand model decision-making toward mechanistic interpretability, a field that examines the internal workings of AI systems. Leading AI companies have established mechanistic interpretability teams, and startups like Goodfire AI have emerged to help decode AI decisions. Goodfire's chief scientist Tom McGrath discussed the approach in a recent interview, highlighting growing recognition that understanding how AI models actually function internally is critical as their reasoning becomes harder to parse.

LMArena, the company behind a popular AI model leaderboard, raised $200 million in a funding round led by Lightspeed and Khosla Ventures, nearly doubling its valuation to $3.1 billion in 10 months. The company is expanding its leaderboard methodology to measure AI models on alignment issues, including whether models tend to lie. The funding reflects investor confidence in third-party AI evaluation tools as model proliferation accelerates.

Google DeepMind, Meta, and Isomorphic Labs are jointly investing $300 million into Biohub, Mark Zuckerberg and Priscilla Chan's nonprofit biomedical research organization. The funding supports a $1.8 billion initiative to build AI datasets enabling researchers to simulate biological systems digitally. Biohub, founded in 2016, aims to develop a 'virtual cell' that could accelerate disease prevention and management research.

OpenAI released 722 manuscripts containing solutions to hundreds of long-standing mathematics problems generated by an unreleased frontier model. The batch covers 372 result families and was coordinated through AGMAI, an independent advisory group of elite mathematicians formed to handle responsible communication of the findings. The release extends OpenAI's recent run of mathematical breakthroughs while raising ongoing questions about research ethics and academic conduct in AI-driven discovery.