The AI revolution is just beginning, and its future depends on how we shape its systems, data, and ethics today. In Part 1 of this two-part episode, Elisa sits down with Dr. Vijay Janapa Reddi, Harvard professor and AI systems expert, to break down the three core categories of AI systems—generative, predictive, and prescriptive—and how they function in the real world. Together they examine how large language models rely on the data they’re fed, why that data matters, and what challenges arise in sourcing it responsibly.
Vijay Janapa Reddi is the John L. Loeb Associate Professor of Engineering and Applied Sciences at Harvard University and Vice President and co-founder of MLCommons, a nonprofit organization committed to accelerating machine learning (ML) innovation for all.
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Dr. Janapa Reddi is author and editor of the open-source AI textbook, "Machine Learning Systems"
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