Tag: models
Schulman, Millidge and O'Neill on why model providers do not consolidate — anything RL teaches is a few bits and copies easily, but only with the right prompt distribution. The router-data argument, the "benchmaxxing versus realism" explanation for why a distilled student can match the benchmarks and not the feel, and the monoculture it produces.
TypeSafe's Diogo Almeida on Jev, a "System 1" model trained for calibrated decisions that software calls in a loop — three primitives, no refusals, no public benchmarks, intelligence per dollar. Also the identification of the author of the earlier KV-cache post, and his view of coding agents without a KV cache.
Two OpenAI people on what changed in computer use since this spring (writing code, accessibility trees, speed), then the API stack — async tool calls, mid-turn steering, 12-hour cache guarantees — and how the Decisions API came out of Jev's launch in about a week. The first answer here to "can a big lab just copy it".
OpenRouter's CEO and an early backer on the multi-model bet, why labs struggle to get a finished checkpoint into developers' hands, the Mistral price war, the roads not taken (tuning, memory, fusion), and why Stripe bought it — token fraud as the next payments problem. Plus a speaker-label problem in the capture.