Machine Learning Street Talk (MLST) cover image

#104 - Prof. CHRIS SUMMERFIELD - Natural General Intelligence [SPECIAL EDITION]

Machine Learning Street Talk (MLST)

00:00

Unraveling the Reward Hypothesis

This chapter explores the intricacies of the reward hypothesis and its impact on intelligent behavior and reinforcement learning. It critiques behaviorism and its limitations in defining intelligence, emphasizing the need for systems that can autonomously set goals. The discussion also addresses historical biases in intelligence testing and the significance of cultural context in understanding intelligence across different paradigms.

Transcript
Play full episode

The AI-powered Podcast Player

Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
App store bannerPlay store banner
Get the app