
Su Park
81 posts

Su Park
@sunotsue_
terminal bench · post-training & evals against global banality prev @ltiatcmu @columbia


Every single startup selling AI Training Data (July 2026) >50 cos sell data and RL environments to big AI labs and drive AI progress behind the scenes. They total ~$8.5B in rev and ~$100B in valuation, >75% of which are just 4 players: Scale, Surge, Mercor and Handshake.

Every single startup selling AI Training Data (July 2026) >50 cos sell data and RL environments to big AI labs and drive AI progress behind the scenes. They total ~$8.5B in rev and ~$100B in valuation, >75% of which are just 4 players: Scale, Surge, Mercor and Handshake.








Post-training for domain-specific tasks is commoditised. @thinkymachines provides really good Claude Code / Codex skills for anyone out there to finetune open-source models. For inference, use @baseten or @FireworksAI_HQ as per your choice.

I’m walking back from an AI event to my hotel and I look up and see a rock climbing gym called “Benchmark.” Is this what living in SF is like?


We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2. Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication. We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating. 🧵👇














