Boltzbit Paper Claims BAST Speeds Up LLM Learning Up to 1000x
Boltzbit released a preprint on Infinite-Parameter LLMs, proposing Bayesian Self-learning Transformers (BAST) that dynamically generate and adapt weights from live data, claiming learning speedups of up to 1000x.
2026-09-24 ~ 2026-09-25 · 2 related posts
- Boltzbit's BAST paper claims LLMs can learn 1000x faster by generating weights from live data — ahuja_priyank · 2026-09-24
- Boltzbit paper claims BAST lets LLMs learn up to 1000x faster than SOTA training — HeyToha · 2026-09-25