Public transcript

How Far Can Artificial Intelligence Really Go? | Yann LeCun - World Governments Summit

By: World Governments Summit
Length: 7 min
Language: English
Text from: the video's captions
Transcribed: 14 October 2026

Read the full transcript Open on YouTube

Notes in English.

Summary

In this interview at the World Governments Summit, Yann LeCun, Turing Award Laureate and Meta's Chief AI Scientist, argues that open-source AI is essential for security, customization, and diversity of opinion, comparing it to the role of a free press. He contends that AI will become the infrastructure of the digital world and that infrastructure software historically becomes open source. He also pushes back on fears of AI taking over, saying we are still very far from human-level intelligence and that current LLMs lack persistent memory, reasoning, planning, and an understanding of the physical world.

Key points

Yann LeCun argues we need free and diverse AI platforms for the same reason we need a free and diverse press, so a single opinion doesn't dominate.
He says infrastructure software historically becomes open source because it is more secure, more customizable, and enables ecosystems to form on top of it.
He claims open source software like Linux is more secure because more eyeballs are on it, and Linux now runs most of the world's systems.
He states we are still very far from matching human and animal intelligence with AI systems, and it will not happen in the next 2 years.
He says current large language models lack persistent memory, reasoning, and planning, and cannot understand how the world works.
He notes LLMs are trained on roughly 10 trillion tokens, which would take a single person 150,000 to 200,000 years to read 8 hours a day.
He compares AI understanding of the physical world unfavorably to that of a cat, while acknowledging humans also run into glass doors.

Questions it answers

00:00The case for open-source AI

Why does Yann LeCun believe open-source AI is the way forward?

He argues all digital interactions will soon be mediated by AI, so we need diverse platforms serving different languages, cultures, and values — which cannot come from a few US West Coast companies or one country.

AI assistants will become a repository of all human knowledge and a kind of infrastructure.
We need free and diverse AI platforms for the same reason we need a free and diverse press.

02:09Open source as infrastructure

What evidence does he cite of open-source AI in practice?

He points to Llama 2 being customized for vertical business applications and for particular languages and cultures, mirroring how infrastructure software like Linux became dominant.

Infrastructure software historically becomes open source because it is more secure and customizable.
Open source enables an ecosystem to form on top of it.

03:16Security through more eyeballs

Why is open source more secure?

He says open source software has more eyeballs on it, making it more secure — noting Linux runs most phones, web servers, cloud services, cars, and even the helicopter on Mars.

The entire world runs on Linux because it can be ported anywhere and made more secure.
The only reason to oppose open sourcing is a belief AI will take over the world, which he rejects.

04:04AI's current limits

How far is AI from human-level intelligence?

He says we are still very far from matching human and animal intelligence, that it will not happen in the next 2 years, and that scientific breakthroughs are still needed.

Machines still cannot understand how the world works, remember facts, reason, or plan.
Even a cat understands the physical world better than the most powerful AI systems.

05:45The scale of LLM training data

How much data are LLMs trained on?

He explains LLMs are trained on about 10 trillion tokens, which would take one person 150,000 to 200,000 years to read at 8 hours a day, suggesting these systems are incredibly smart.

10 trillion tokens equals roughly 2 × 10 to the 13th bytes.
LeCun uses this scale to argue current systems digest enormous knowledge despite their limitations.

Notes

Open-Source AI as Infrastructure

Yann LeCun, Turing Award Laureate and VP & Chief AI Scientist at Meta, argues AI will soon mediate all our interactions with the digital world, as seen with AI-backed replacements for search engines.
This requires a wide diversity of AI systems serving different languages, cultures, value systems, and interests — something that cannot be produced by a small number of companies on the West Coast of the US or by any single country.
History shows infrastructure software ends up open source because it is more secure, more customizable, and enables ecosystems on top of it — as with the internet and cell phone software stacks.
Since Llama 2 became available, people have been customizing open source models for vertical business applications and for particular languages and cultures.

Why Open Source Is Safer

"We need free and diverse AI platforms for the same reason that we need free and diverse press, so we don't have a single opinion coming to us from AI."
Open source software is historically more secure because there are more eyeballs on it.
Linux runs the world: most phones (everything not an iPhone), web servers, cloud services, car microcontrollers, and even the helicopter on Mars.
The only reason to oppose open sourcing AI is a belief that AI is so powerful it will take over the world — which LeCun says is not happening.

How Far AI Can Really Go

We are still very far from matching human and animal intelligence and learning capacities; it is not going to happen in the next 2 years.
Scientific breakthroughs are still needed for machines to understand how the world works, remember facts (persistent memory), reason, and plan — essential characteristics of intelligent behavior that current LLMs lack.
LLMs are trained on roughly 10 trillion tokens (10 to the 13th power), about 2 × 10 to the 13th bytes, which would take one person 150,000 to 200,000 years to read at 8 hours a day.
Even a cat has a much better understanding of the physical world than the most powerful AI systems — though LeCun concedes he has run into glass doors himself.

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