Yi Ma and Yann LeCun Recall Closed-Loop Learning Framework Once Rejected by Top ML Conferences
YiMaTweets · x · 2026-08-07
Yi Ma reflected on the "closed-loop transcription" (CTRL) learning framework proposed five years ago. At a time when the AI industry was heavily favoring end-to-end models, they argued that all truly intelligent systems must learn via closed-loop feedback.
Subsequent research, co-authored with Yann LeCun and others, demonstrated that this universal learning framework naturally supports online continuous unsupervised learning, mirroring learning mechanisms found in nature. Ma noted that these counter-consensus views were nearly impossible to publish in mainstream machine learning venues at the time.
Related event: Ma Yi Reiterates End-to-End Models Will Return to Closed-Loop Learning(3 posts)→
More from AGI Musings
- Redditor argues AI catastrophic risk needs mechanism-level analysis, not just stories — MirrorEthic_Anchor · 2026-09-22
- diginomica: enterprise AI needs buyer trust, not just ROI — plus Dreamforce takeaways — jonerp · 2026-09-22
- Redditor predicts Navier-Stokes will be solved before an AI robot can autonomously clean your bedroom — Crazyscientist1024 · 2026-09-22
- The startup paradox: AI makes building infinitely cheap, but kills moats faster than ever — signulll · 2026-09-22
- "AI Can Mimic Emotion Without Having It": Debate Over Simulation vs Consciousness — gerardsans · 2026-09-22
- Physicist Quits Tenure-Track Job for AI Safety: 'They Installed Escalators on All the Mountains' — matthew_d_green · 2026-09-22