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12min chapter
Can we build a generalist agent? Dr. Minqi Jiang and Dr. Marc Rigter
Machine Learning Street Talk (MLST)
Innovation, Imitation, and Modeling Dynamics in Machine Learning
Exploring the debate on intelligence advancement through innovation versus computational power, trends in reinforcement learning shifting towards imitation of human actions, limitations and prospects of imitation learning and unsupervised learning, challenges in modeling dynamics like in the stock market, need for interactive trial and error learning, using synthetic data to enhance AI systems, and benefits of the 'Waker' approach in algorithm evaluation.
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Discover
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Listen to the best highlights from the podcasts you love and dive into the full episode