Open-source LLM debate: without shared training data, 'we basically have no open models'
jpschroeder · x · 2026-10-27
Yacine MTB argues an LLM is a closed binary whose compilation 'takes boiling a few oceans' — the source can still be open without compiling it, but trustworthy open-source LLMs must share training data so users can trust their behavior.
Respondent jpschroeder agrees but notes that's a very high bar that would give away labs' competitive edge, since they all have profit motives: 'We basically have no open-source models today.'
The exchange hits the core definitional controversy: open weights ≠ open source, and data/process transparency is what enables reproducibility and trust.
Related event: Yacine sparks debate: open-source LLMs must release training data(3 posts)→
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