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Godfather of AI: How To Make Safe Superintelligent AI – Yoshua Bengio
2:35:26
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Godfather of AI: How To Make Safe Superintelligent AI – Yoshua Bengio

The 'Predictor' Architecture: Bayesian Posterior Approximation — 80,000 Hours

From Godfather of AI: How To Make Safe Superintelligent AI – Yoshua Bengio. Category: Tech. Format: Interview. This is a single keypoint from the analysis.

The core of Bengio's proposal is a 'predictor' model trained to approximate the Bayesian posterior over natural language queries. This model outputs probabilities for statements being true, distinguishing between communication acts and factual claims, and aims to best explain all observed data.

Impact: High. This approach fundamentally differs from current LLMs by focusing on truth modeling rather than next-token prediction or human preference, offering a more robust foundation for understanding the world.

In the source video, this keypoint occurs from 00:01:15 to 00:03:56.

Sources in support: Yoshua Bengio (Guest, AI Researcher)

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