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BI 209 Aran Nayebi: The NeuroAI Turing Test

Brain Inspired

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Advancements in Cognitive Architecture

This chapter explores the evolution of cognitive architecture in AI, focusing on generalized embodied intelligence and the role of brain data in enhancing AI capabilities. It discusses the significance of convolutional neural networks for visual recognition, the importance of sensory world models, and the challenges of modeling intuitive physics. Additionally, the chapter highlights the shift towards biologically inspired learning rules, examining backpropagation and its alternatives in the context of neural network advancements.

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