Public transcript

Yann LeCun 氏　ビデオメッセージ

By: FRONTia_ch
Length: 5 min
Language: English
Text from: the video's captions
Transcribed: 14 October 2026

Read the full transcript Open on YouTube

Notes in English.

Summary

This is a short video message from Yann LeCun recorded for an event launching in Tokyo on July 16th. He introduces his background at NYU, AMI, and Meta FAIR, and argues that AI is at a turning point from disembodied generative models toward physical AI. He explains that world models will let AI systems predict, plan, and act in the real world, and that Japan is uniquely positioned to lead this shift thanks to its manufacturing and robotics expertise.

Key points

Yann LeCun is a professor at New York University, chairman and co-founder of AMI (Advanced Machine Intelligence), and a Turing Award recipient.
He spent 12 years at Meta, where he founded FAIR and served as Chief AI Scientist.
He was inspired early in his career by the foundational neural network work of Professor Amari and Fukushima from the 1970s and 1980s.
Generative AI over the last 5 years has been largely disembodied, strong on language, code, and mathematics but unable to apprehend the physical world.
The next frontier is physical AI: systems that perceive, reason about, and act in any environment, understanding causality and physical reality.
AMI's mission is building agent AI systems around world models that predict the evolution of the environment and the consequences of their own actions.
Applications include manufacturing, autonomous robots in complex unstructured environments, infrastructure operation, and real-time grid management for sustainable energy.
Japan's decades of mastery in precision manufacturing, industrial robotics, and engineering make it uniquely positioned to lead in physical AI.

Questions it answers

00:00Introduction and credentials

Who is Yann LeCun and why is he speaking?

He opens with greetings and says he is honored to address the Tokyo launch on July 16th, though sorry he cannot attend in person. He introduces himself as a professor at New York University, chairman and co-founder of AMI, and a Turing Award recipient.

He spent 12 years at Meta, founded FAIR, and served as Chief AI Scientist.
He was inspired early in his career by Professor Amari and Fukushima's neural network work.

01:02The turning point toward physical AI

Why does LeCun see AI at a turning point?

He says generative AI over the last 5 years has been largely disembodied, excelling at language, code, and mathematics but unable to apprehend the physical world. The next frontier is physical AI that can perceive, reason about, and act in any environment.

Physical AI means systems that understand causality, physical reality, and real-world constraints.
He calls it possibly the most important scientific and engineering challenge of our generation.

01:43World models at AMI

What technical approach does AMI pursue?

AMI builds agent AI systems around world models, which predict the evolution of the environment and the consequences of their own actions, enabling planning of action sequences. This requires new architectures learning from continuous, high-dimensional, noisy sensor data like video.

Models must build an internal representation of the world and predict action consequences.
World models enable planning to accomplish particular tasks.

02:56Applications of physical AI

What can physical AI be used for?

Applications include manufacturing, autonomous robots that handle new situations in complex unstructured environments without prior training, and operating infrastructure and managing grids in real time for sustainable energy. He stresses these are not distant promises, as foundational work is happening now.

Robots will go beyond scripted recipes.
Physical AI can accelerate the transition to sustainable, resilient energy at scale.

03:20Japan's leadership role

Why is Japan well positioned for physical AI?

Japan's decades of mastery in precision manufacturing, industrial robotics, and engineering excellence give it exactly the foundation physical AI demands, with factory floors as training grounds for intelligent systems. He says Japan does not need to catch up but needs to lead, through genuine international collaboration.

The Tokyo initiative signals Japan is ready to be a full partner in shaping this future.
He looks forward to working with Japan's scientists, engineers, and policymakers.

Notes

Speaker Background

Yann LeCun is a professor at New York University, chairman and co-founder of Advanced Machine Intelligence (AMI), and a Turing Award recipient.
He spent 12 years at Meta, founded FAIR (Meta's Fundamental AI Research Lab), and served as Chief AI Scientist.
Early in his career he was inspired by the foundational neural network work of Professor Amari and Fukushima from the 1970s and 1980s.

The Turning Point in AI

For the last 5 years, AI through generative models has been largely a disembodied technology.
It is extraordinarily good at processing human language, computer code, and mathematics, but fundamentally unable to apprehend the physical world.
The next frontier is physical AI: systems that can perceive, reason about, and act in any environment, understanding causality, physical reality, and real-world constraints.
LeCun calls this possibly the most important scientific and engineering challenge of our generation.

World Models and New Architectures

Getting there requires new architectures that learn from real-world sensor data that is continuous, high-dimensional, and noisy, such as video.
AI models must build an internal representation of the world and predict the consequences of their actions.
AMI's mission is building agent AI systems around the concept of world models.
With world models, systems can predict the evolution of their environment, predict the consequences of their own actions, and plan action sequences to accomplish tasks.

Applications

Industry applications such as manufacturing.
A new generation of autonomous robots operating in complex unstructured environments, going beyond scripted recipes to handle new situations without prior training.
Operating infrastructure, managing grids in real time, and accelerating the transition to sustainable, resilient energy at scale.

Japan's Role

Japan's decades of mastery in precision manufacturing, industrial robotics, and engineering excellence provide exactly the foundation physical AI demands.
The factory floor and industrial environments are training grounds for the next generation of intelligent systems.
In physical AI, Japan does not need to catch up; it needs to lead, through genuine international collaboration among researchers, industries, and governments.

Text from the video's own captions. Summary and notes written by AI from the transcript, so check anything important against the recording.