Closed-model research distorts science when architectures and training data stay hidden
joshua_saxe · x · 2026-07-27
The author says open literature and posts from researchers such as @natolambert taught them as much about LLM development as direct work on Meta's Llama efforts. They then argue that studying closed models without knowing their architectures, training methods, or training data creates a major distortion in science.
More from AGI Musings
- Did Altman already secretly claim OpenAI hit AGI? Netizens dig through old interviews — RileyRalmuto · 2026-09-23
- Mathematician Elliot Glazer argues OpenAI should "slop drop" all its math results rather than hide them — burny_tech · 2026-09-23
- Grady Booch doubts AI's Navier-Stokes claim: insights may come from human experts — Grady_Booch · 2026-09-23
- Grady Booch: Contemporary AI Still Lacks Abductive Reasoning, Just 'Next-Token Prediction' — Grady_Booch · 2026-09-23
- AI solves Navier-Stokes-related problem as machines upend mathematics, New Scientist reports — burny_tech · 2026-09-23
- Mathematician says OpenAI likely proved a significant partial case of the Hodge conjecture — burny_tech · 2026-09-23