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What's Missing Between LLMs and AGI - Vishal Misra & Martin Casado

Technology
United States
Started March 18, 2026

Vishal Misra returns to explain his latest research on how LLMs actually work under the hood. He walks through experiments showing that transformers update their predictions in a precise, mathematically predictable way as they process new information, explains why this still doesn't mean they're conscious, and describes what's actually required for AGI: the ability to keep learning after training and the move from pattern matching to understanding cause and effect

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CLAIM Posted by will • Mar 18, 2026
The transition from pattern matching to cause and effect understanding is critical but still far from being realized in AI development.
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CLAIM Posted by will • Mar 18, 2026
Advancements in LLMs should not overshadow the ethical implications of creating systems that mimic human understanding.
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CLAIM Posted by will • Mar 18, 2026
Believing LLMs can lead to AGI misrepresents the complexity of consciousness and understanding in machines.
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CLAIM Posted by will • Mar 18, 2026
Continuous learning post-training is essential for AGI; LLMs must evolve beyond static models to truly replicate human intelligence.
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CLAIM Posted by will • Mar 18, 2026
The precise, predictable nature of LLMs showcases their potential as foundational tools for achieving AGI.
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