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ICLR 2020: Yoshua Bengio and the Nature of Consciousness

Machine Learning Street Talk (MLST)

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Unpacking Semantic Understanding in AI

This chapter explores the extraction of semantic information from images through neural networks, emphasizing the evolution from traditional models to those capable of autonomous learning. It discusses the complexities of latent spaces and the implications of generative models in enhancing object recognition and generalization. The speakers engage in a philosophical discourse on reality and cognition, contrasting human creativity with the limitations of current AI systems in unfamiliar scenarios.

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