The chip, codenamed Frozen v2, reportedly targets 6–10× more tokens per watt than Google's newest TPUs. Deployment is planned as early as 2028 as Google seeks to address compute shortages. Alphabet shares rose on the news.
InternLM released the Intern-S2-Preview-397B, a 397-billion parameter model under preview on HuggingFace. The model is already trending with community interest.
Paper scales reinforcement learning with verifiable rewards (zero RL) to a trillion parameters, leading to emergent reasoning capabilities. It elicits chain-of-thought reasoning without human-annotated data.