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MLST #78 - Prof. NOAM CHOMSKY (Special Edition)

Machine Learning Street Talk (MLST)

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Embracing Uncertainty in Neural Networks

This chapter emphasizes the critical need for probabilistic approaches in neural network modeling, advocating for a return to established probability theory to address uncertainties in real-world data. It explores the balance between modern machine learning practices and traditional methodologies, while critiquing oversimplification and discussing the significance of world models in AI.

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