#post-training

Radar · 2026-06-15

Nathan Lambert leaving Ai2 exposes the fragile side of open models

Nathan Lambert announced his departure from the Allen Institute for AI and used it to reflect on work around Olmo. This is not just a personnel note. It is a reminder that open models depend on institutions that must outlast one strong team.

Radar · 2026-06-15

Raschka's LLM paper list shows research splitting into production layers

Sebastian Raschka published a curated list of LLM papers from January to May 2026. It is a useful filter for teams trying to separate the research feed from topics that matter for architecture, agents and inference.

Radar · 2026-06-09

Claude Fable 5 turns safety into a question of access to the best model

Nathan Lambert reads the Claude Fable 5 release as a dispute over who gets to use a frontier model without routing and filters. The important layer is not only model capability, but the governance system that decides when the user is really talking to the strongest model.

Radar · 2026-06-01

Open models win on cost, but frontier intelligence still sells at a premium

Nathan Lambert argues that open and closed models are improving on different economic curves. The real question is not open source ideology, but where companies will keep paying a premium for the best model.