Self-Supervised Learning and the Future of AI - from a lecture given by Yann LeCun

episode

Build Wiz AI Show not yet transcribed

▲ 0

Transcript

This episode hasn't been transcribed yet Upvotes decide what gets transcribed next — 0 so far. Sign in to upvote

Related

recent transcribed audio

Your partner wants profit. You want freedom. Now what? 22 min · 16 Sep 2026 · The Optometry Success Podcast

Board of County Supervisors Meeting - Work Session - Sep 15, 2026 3h 17m · 15 Sep 2026 · Prince William County Board of Supervisors

Finance and Budget Committee - Sep 15, 2026 1h 43m · 15 Sep 2026 · Prince William County Finance and Budget Committee

The Art of True Happiness | Dr. Arthur Brooks 2h 49m · 14 Sep 2026 · Huberman Lab

The Chris Wolfe Podcast: The Power of Quality Supplements 48 min · 14 Sep 2026 · EyeCode Media

NPR News: 09-13-2026 6PM EDT 4 min · 13 Sep 2026 · NPR News Now

Report any issue

Source

Recorded07 Oct 2025

Publisheranchor.fm ↗

Handlerec:12512883

Show notes

Join us as Turing Award recipient Yann LeCun, Chief Scientist at Meta, critiques the state of AI, arguing that current systems, including Large Language Models (LLMs), are nowhere near matching the learning efficiency observed in humans and animals. LeCun proposes a major architectural shift, advocating that AI must abandon generative models for training and instead focus on building internal "World Models" to enable reasoning and planning. Discover how the Joint Embedding Predictive Architecture (JEPA) uses self-supervised learning to train machines to acquire robust, abstract representations of reality, a crucial step toward achieving common sense and human-level intelligence.

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.

Sign in