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BI 209 Aran Nayebi: The NeuroAI Turing Test

Brain Inspired

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Navigating AI's Cognitive Challenges

This chapter explores the complexities of artificial neural networks in measuring brain data and their implications for understanding intelligent behavior. It discusses the evolution of AI models from traditional symbolic approaches to contemporary connectionist ones, highlighting the roles of architecture and task specification. Additionally, the conversation delves into the challenges of programming intrinsic goals within AI, including the phenomena of reward hacking and the distributed nature of goal computation in the brain.

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