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#54 Gary Marcus and Luis Lamb - Neurosymbolic models

Machine Learning Street Talk (MLST)

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Unlocking AI Abstraction

This chapter explores the complexities of abstraction within artificial intelligence, particularly focusing on how systems like GPT-4 can achieve effective generalization. It discusses the limitations of neural networks in comparison to human reasoning and advocates for a hybrid approach that combines neural and symbolic methods. The speakers also highlight the historical context of AI research and call for a collaborative future among diverse methodologies.

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