🧠 “LLMs Are Basically Obsolete” — Why AI Pioneer Yann LeCun Thinks the Real AI Revolution Hasn’t Even Started

📢 “Don’t work on LLMs. Work on next-gen AI.”
— Yann LeCun, Chief AI Scientist at Meta

Yann LeCun — one of the “godfathers” of AI and a pioneer of deep learning.

🕳️ Let’s Start With a Plot Twist…

Everyone’s talking about AI.
ChatGPT, Claude, Gemini, Llama — it feels like we’ve hit the future already, right?

But what if one of the guys who actually helped build this future told you…

“This isn’t it.”
“We’re doing it wrong.”
“LLMs are a dead end.”

Yeah. That happened.

⚙️ LLMs Are Impressive… But Kind of Dumb

Here’s LeCun’s beef with today’s large language models:

❌ They don’t understand the world

❌ They can’t plan or reason

❌ They’re guessing, not thinking

What they can do is predict the next word in a sentence.

So sure, they pass the bar exam. But could they walk across a room without falling?

Not a chance.

🐱 “Where’s the AI That’s As Smart As a Cat?”

A cat navigates the real world effortlessly. ChatGPT can’t.

LeCun asks a powerful question:

“Where is a robot that’s as good as a cat in the physical world?”

LLMs can write code, solve math problems, and even generate recipes. But ask one to hand you a cup? Total system failure.

That’s Moravec’s Paradox:
What’s hard for humans is easy for machines. What’s easy for us — like movement and perception — is extremely hard for machines.

🤯 The Illusion of Intelligence

LLMs seem smart because they speak well. But that’s like assuming someone is a doctor because they can say “appendectomy” convincingly.

They’re fluent, not wise.
Reactive, not reflective.
Brilliant at trivia, clueless at reality.

“An LLM produces one token after another… It’s System 1 — reactive, not reasoning.” — Yann LeCun

🧠 Human Brains Don’t Work Like That

Humans don’t think in next-word predictions. We build mental models.
We plan. We improvise. We learn physical rules just by watching the world.

LeCun gives an example:

“A 10-year-old can clear the dinner table the first time you ask them — even if they’ve never done it before.”

That’s not magic. That’s abstract world modeling.

Kids pick up on real-world tasks intuitively. Why can’t AI?

🔮 JEPA: The Future of AI Is Video, Not Text

LeCun and his team at Meta are building something new:
JEPA — Joint Embedding Predictive Architecture

What does it do?

• Learns from video
• Predicts what will happen next
• Plans how to achieve goals in a real, physical space

Instead of predicting text, it predicts world changes.

🎥 Why Video Is the New Frontier

Imagine showing a baby a ball rolling off a table. Eventually, they learn: things fall.

That’s learning from physics, not books.

JEPA works like that — learning from video frames, spotting when something physically impossible happens (like a vanishing object), and flagging it as wrong.

That’s how real-world understanding begins.

🚫 Not Afraid of AI Apocalypse

Unlike some other AI legends (ahem, Geoffrey Hinton), LeCun doesn’t buy the AI-doomsday narrative.

Why?

➤ Intelligence ≠ Power

Just because an AI is smart doesn’t mean it can take over.

As LeCun says:

“Look at the political scene. It’s not the smartest who tend to be leaders.”

🔥 Burn. But fair.

🧩 Intelligence Is Only One Piece

Einstein? Brilliant, but not a king.
Feynman? Genius, not a general.

LeCun says we overestimate intelligence and underestimate infrastructure. AI isn’t going rogue unless we hand it the keys. (Spoiler: We won’t.)

⚔️ AI vs AI: “My Smart Cop vs Your Rogue Bot”

LeCun imagines a society of machines — some smart, some even rogue — but others smarter and built to shut them down.

Like a digital justice league.
Built-in guardrails.
AI systems keeping each other in check.

💬 “Humans can break laws because we have free will. AI systems don’t. You can design them with boundaries.” — Yann LeCun

👑 Humanity Isn’t Getting Replaced — It’s Getting Promoted

“Everybody will become a CEO of some kind.”

That’s LeCun’s vision.

AI isn’t here to take over. It’s here to amplify.
In the future, we’ll manage fleets of intelligent systems — not be replaced by them.

Imagine:
You don’t run the warehouse.
You run the AIs that run the warehouse.

🔓 Why Open Source Is the Key

LeCun is passionate about open-source AI.

“No country will have AI sovereignty without open-source models.”

Because if you don’t control your tools, you don’t control your future.

🧭 So, What Should We Actually Be Building?

LLMs have their place. But the next big leap?

✅ Systems that plan
✅ Systems that learn like kids
✅ Systems that can act in the physical world
✅ Systems with abstract models and hierarchical reasoning

Basically: The first AI that’s smarter than a cat.

💬 “I’d be happy if, by the time I retire, we have systems as smart as a cat.”
— Yann LeCun
(He’s not joking.)

💡 Welcome to the Age of World Models

• 🧠 LLMs are cool, but they don’t reason or plan
• 🐾 A cat still beats ChatGPT in real-world tasks
• 🎥 JEPA models learn by watching and predicting, not just reading
• 🧍 AI isn’t replacing us — it’s augmenting us
• 🛠️ Open source and grounded design are the way forward

✨ What’s Next?

If you’re in tech:
→ Start learning about world modeling, embodied AI, and predictive architectures.

If you’re in policy:
→ Push for open-source AI and AI literacy.

If you’re just a curious mind:
→ Follow thinkers like Yann LeCun, Rodney Brooks, David Eagleman.

📢 SHARE THIS POST IF YOU BELIEVE THE REAL AI REVOLUTION IS JUST BEGINNING.

👇 Drop your thoughts in the comments:
What do you think — are LLMs a dead end, or just the beginning?