Adaptivity in Machine Learning with Samory Kp...

As context windows grow into the millions of tokens, many AI practitioners are questioning whether retrieval-augmented generation (RAG) is still necessary. If modern models can ingest entire libraries of documents, why bother with retrieval at all? In this episode, Alex Bowcut, H ...  Show more

In this episode, Jure Leskovec, co-founder and chief scientist at Kumo and professor of computer science at Stanford, joins us to explore two fronts of his work: AI for science and relational deep learning. We begin with AI Virtual Cell, a multiscale effort to learn data-driven r ...  Show more

Over the past several years, we have seen many success stories in machine learning brought about by deep learning techniques. While the practical success of deep learning has been phenomenal, the formal guarantees have been lacking. Our current theoretical understanding of the ma ...  Show more

How Zack went from being a musician to professor, how medical applications of Machine Learning are developing, and the challenges of counteracting bias in real world applications. Zachary Chase Lipton is an assistant professor of Operations Research and Machine Learning at Carneg ...  Show more

From ChatGPT to self-driving cars, AI is everywhere these days – but its rollout hasn’t always been entirely smooth. Tom Griffiths, PhD, a professor of psychology and computer science at Princeton University, talks about how artificial intelligence works, how AI differs from huma ...  Show more

<span style="font-weight: 400;">Sam Harris speaks with Jeff Hawkins about the nature of intelligence. They discuss how the neocortex creates models of the world, the role of prediction in sensory-motor experience, cortical columns, reference frames, thought as movement in conc ...