Yann LeCun: AGI is not just around the corner, and people claiming it is have been “systematically wrong.” “It’s not going to be an event. It’s going to be gradual progress.” “We still need systems that can properly understand the world, remember, reason and plan.” “Getting all of those things to work together is another story.” “This is going to take at least a decade, and probably much more.” “I’ve been hearing for 12–15 years that AGI is just around the corner.” “They were systematically wrong. I called their bullshit.”

Yann LeCun says that once Meta decided it had fallen behind, the research with the longest payoff was the first thing to lose priority. He is describing the period after Llama 4 disappointed Mark Zuckerberg, when Meta reorganized its AI effort and refocused on catching up with the rest of the industry. In his account, the company got what it asked for, and something else went quiet: "And the sad side effect of it is that a lot of the exploratory research was basically not given high priority anymore." He says his own work was protected. Zuckerberg, CTO Andrew Bosworth and others believed in the long-term impact of the world-model research he was running. That protection did not change where the organization's attention actually went: "But the rest of the company was just totally, entirely focused on LLMs." That is what made him leave. He says it became clear Meta was no longer the right place to push that project. Worth saying plainly: LeCun now runs a startup built on the research direction he says Meta sidelined, so he has an interest in this story. This is his account of what happened inside Meta, not a company statement. When an organization decides it is behind, the work with the longest payoff loses first, and in AI labs that is the same shelf where interpretability, evaluation and safety research sit. A race never announces that it is deprioritizing understanding the systems, it just reassigns the people. This is why verification cannot live inside the company shipping the model. - Yann LeCun (@ylecun) on Unsupervised Learning with Jacob Effron (@jacobeffron), recorded May 2026.

Yann LeCun sat across from Lex Fridman and quietly proved that intelligence has nothing to do with thinking. He did it with two sentences about a trophy. “The trophy doesn’t fit in the suitcase because it’s too big.” “The trophy doesn’t fit in the suitcase because it’s too small.” Same words. One swap at the end. In the first, “it” is the trophy. In the second, “it” is the suitcase. You solved both before you finished reading. Nobody taught you that. There is no rule for it. No logic chain. No formula. You knew because you’ve held things. Packed things. Felt the resistance of something too large for the space it was meant to fill. LeCun calls this grounding. “A big object doesn’t fit in a small object.” The machine has read that line a billion times. It has never once picked anything up. It knows the word “big.” It has never been small enough to be lifted, or large enough to be the problem. So when the sentence turns, it has nothing to turn on. You didn’t solve that riddle by thinking. You solved it by having lived. Every object your hands ever closed around. Every door you misjudged. Every suitcase you overpacked and forced shut. Decades of physics written into your nervous system so deep you can’t even find it. That is what answered the question. Not your mind. Your life. LeCun: “You have this knowledge of how the world works, of geometry, and things like that.” Now point that at yourself. Most of what you understand, you could never explain. You cannot describe how you catch a ball. How you judge the weight of a bag before you lift it. How you know a staircase is wrong before your foot confirms it. Your deepest intelligence has no language in it at all. We spent centuries convinced that thinking was the highest act of the mind. LeCun is pointing at something underneath it. Something older. Something the body learned long before the mouth could speak. Intelligence was never computation. It was accumulation. The slow, silent record of a life spent touching the world. The machine holds every word ever written about it. It has never once been in it. We keep asking whether it thinks. It cannot even tell us which “it” we mean.

Yann LeCun says robotics could become a huge market, but the industry still doesn't know how to make humanoid robots useful The missing piece is AI that can understand the physical world and handle tasks with generality and adaptability "LLMs are useful, but for different problems"

Yann LeCun says LLMs aren’t a bubble in value or investment—they’ll drive many real-world applications and justify current infrastructure spend. The actual bubble lies in assuming LLMs can become human-level thinkers.

Wu Yanni took bronze in the women's 100m hurdles at the Asian Games on Sunday, clocking 13.12 in Nagoya — three years after her false-start disqualification in Hangzhou. Japan's Mako Fukube won gold, leading a home one-two. Wu remains one of China's most-followed track athletes.

Milo Yiannopoulos deported back to the UK following his ICE arrest. The controversial commentator was deported on Friday, just one day after his arrest at Louis Armstrong New Orleans International Airport in Louisiana. Source: DHS