Future of Machine Learning
Minqi and Marc discuss the future of machine learning, emphasizing the limitations of scaling raw supervised and unsupervised learning. They delve into the necessity of self-improving systems to generate synthetic data and break beyond existing data limits, highlighting the importance of exploration and world models in driving performance further.In this clip
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Machine Learning Street Talk (MLST)
Can we build a generalist agent? Dr. Minqi Jiang and Dr. Marc Rigter
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