Simple Guy

Engineering Leadership| Fitness enthusiast | Aspiring iron man athelete 2026

[Naval @naval]

If You Want to Learn, Do.

[Sam ꕤ @SamInkedArt]

Happy Monday All

[Dima Zeniuk @DimaZeniuk]

Good morning, 𝕏

Wishing you a wonderful week ahead

[Dima Zeniuk @DimaZeniuk]

“Our next product is Blindsight, which will enable those who have total loss of vision, including if they've lost their eyes or the optic nerve, or maybe have never seen even blind from birth, to be able to see again.”

— Elon Musk

[Karl Mehta @karlmehta]

In a world where AI shapes every business decision, trust isn't optional.

It's the only competitive advantage that matters.

And there's one thing that builds AI trust faster than anything else:

[Karl Mehta @karlmehta]

While everyone's racing to build next-generation AI, the smart money is positioning for what makes them trustworthy.

The companies that survive this transition won't just have better models.

They'll have the governance frameworks to validate them at scale.

[Karl Mehta @karlmehta]

LeCun's warning reveals the hidden opportunity:

As companies abandon LLMs for world models, they're creating a massive validation gap.

These new architectures aren't just different - they're fundamentally harder to monitor and govern.

[Karl Mehta @karlmehta]

How to prepare:

Researchers: "Don't work on LLMs. Focus on world models and sensory learning."

Companies: Build on open-source foundations like PyTorch and Llama.

When the shift happens, you adapt instantly.

The window to position yourself is closing:

[Karl Mehta @karlmehta]

The economic implications are massive.

Companies building on OpenAI APIs could see foundations crumble in 3-5 years.

But early movers positioning for JEPA? They'll capture the next $10 trillion wave.

LeCun's advice for surviving this transition:

[Karl Mehta @karlmehta]

5. AI assistants replace all digital interfaces

Ray-Ban Meta glasses: Look at Polish menu, get translation. Ask about plants, get species ID.

That's primitive compared to what's coming.

AI will mediate ALL digital interactions.

Here's what this means for your business:

[Karl Mehta @karlmehta]

Every company betting only on GPT-style scaling will be blindsided.

LeCun calls the "country of geniuses in a data center" idea "complete nonsense."

The smart money is repositioning for the architecture shift.

[Karl Mehta @karlmehta]

4. AGI timeline is 2027-2034

@ylecun's exact words: "3-5 years to get world models working. Then scaling until human-level AI... within a decade or so."

But it won't come from scaling LLMs.

[Karl Mehta @karlmehta]

"Foundation models will be open source and trained in a distributed fashion."

A few companies controlling our digital lives? "Not good for democracy or anything else."

Progress is faster in the open. The world will demand diversity and control.

LeCun's timeline will surprise you:

[Karl Mehta @karlmehta]

3. Proprietary AI models will "disappear"

LeCun's exact words: "Proprietary platforms, I think, are going to disappear."

He calls it "completely inevitable."

OpenAI's closed approach? Google's secret models? All doomed.

His reasoning will shock the industry:

[Karl Mehta @karlmehta]

Babies learn gravity and physics by 9 months. Before they speak.

"We're never going to get human-level AI unless systems learn by observing the world."

Companies building video-first AI will leapfrog text-based systems.

Here's what Meta is secretly building:

[Karl Mehta @karlmehta]

2. Video-based AI will make text training primitive

LeCun's calculation: A 4-year-old processes 10¹⁴ bytes through vision alone.

That equals ALL the text used to train GPT-4.

In 4 years. Through one sense.

This changes everything about how AI should learn:

[Karl Mehta @karlmehta]

Every token an LLM generates compounds tiny errors exponentially.

The longer the output, the higher the probability of hallucination.

This is why ChatGPT makes up facts. Why scaling won't save current models.

Mathematical certainty.

But LeCun didn't stop there:

[Karl Mehta @karlmehta]

1. "Nobody in their right mind will use autoregressive LLMs a few years from now."

The technology powering ChatGPT and GPT-4? Dead within years.

The problem isn't fixable with more data or compute. It's architectural.

Here's where it gets interesting...