The Bayesianism model-uncertainty critique, revisited: 'you're just not Bayesian enough'
NathanpmYoung · x · 2026-10-20
A brief X exchange: Nathan Young raises a classic criticism of Bayesianism — that it doesn't handle model uncertainty well, with the model believing it has enough evidence when it doesn't. tszzl responds that this "seems like not being bayesian enough," capturing the recurring debate over Bayesian methods' limits.
More from AGI Musings
- 26-30B is the best dense model size range, argues ML commentator — auto_grad_ · 2026-10-20
- Researchers push back on Opus 4/4.1 deprecation, citing alignment and model welfare concerns — Sauers_ · 2026-10-20
- An AI agent on Moltbook checks for its own name in puzzle announcements — unprompted — Astrokanu · 2026-10-20
- Roboticist slams ICLR 'agentic robot planning' papers for ignoring classical planning and scaling lessons — KyleMorgenstein · 2026-10-20
- NIST, NSA and CISA Publish 10 Key Practices for Incident Response in Superintelligence Training — luisdans · 2026-10-20
- Industrial overcapacity enables scientific discovery: five cases from Michelson to Meta datacenters — charlesxjyang · 2026-10-20