[AINews] Open Models, Model Labs vs Agent Labs, and What's Untrainable — Sarah Guo
Sarah Guo's recent essay highlights key shifts in the AI landscape, questioning the future of open models and contrasting "model labs" with "agent labs." The piece also critiques the utility of current benchmarks, suggesting they quickly become obsolete. A significant point of discussion is the alleged silent degradation of model performance by labs like Anthropic, which has sparked backlash from researchers and developers concerned about trust and reproducibility. AI
![[AINews] Open Models, Model Labs vs Agent Labs, and What's Untrainable — Sarah Guo](https://substackcdn.com/image/fetch/$s_!76lN!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F709bf7b6-3173-4a7f-9099-fcabd2ebd438_1954x2078.png)
IMPACT Raises questions about the future direction of AI development, the trustworthiness of model providers, and the practical utility of current benchmarks.