Today in AI

A widely cited analysis argues that the more consequential AI competition has shifted away from frontier labs chasing benchmark records and toward the fast-moving open-weight ecosystem, where Chinese models now account for a large share of downloads on Hugging Face. The piece points to open models increasingly matching closed ones on practical tasks at a fraction of the cost. If the trend holds, it reshapes which companies actually control how most AI gets used day to day.

Microsoft CEO Satya Nadella cautioned companies against treating AI adoption as a substitute for actually rethinking how work gets done, warning that bolting AI onto old processes mostly just makes old processes faster, not better. The comments stand out coming from the head of one of the AI industry's biggest backers. It's a useful check against the assumption that deploying AI tools alone guarantees a productivity payoff.

A group of publishers and authors — including Hachette, Cengage, Elsevier, and novelist Scott Turow — filed a class action against Google, alleging its Gemini models were trained on their copyrighted books and that Google altered or removed copyright information to obscure the sourcing. It's the latest in a growing docket of training-data suits against major labs, following Anthropic's recent settlement. The size and profile of the plaintiff group suggests Google is unlikely to settle quietly or quickly.

Waze rolled out AI-powered updates including routes personalized to a driver's trip history and a city's traffic patterns, a new motorcycle mode that flags two-wheeler-specific hazards and shortcuts, and conversational map edits — you can now just say "the road is closed here" instead of filling out a report. Some features run on Google's Gemini, reflecting how deeply Gemini is now embedded across Google's product lineup. It's a good example of AI showing up as a quiet feature upgrade rather than a flashy standalone launch.

OpenAI researcher Miles Wang is reportedly in talks to raise around $200 million for a new AI drug discovery startup at a $2 billion valuation. It's part of a broader pattern of senior researchers at frontier labs spinning out into applied, vertical-specific AI companies rather than staying at general-purpose model shops. Drug discovery in particular keeps drawing outsized valuations relative to how early-stage these companies actually are.