It’s said that Henry Ford’s customers wanted a “a faster horse”. If Henry Ford was selling us artificial intelligence today, what would the customer call for, “a smarter human”? That’s certainly the picture of machine intelligence we find in science fiction narratives, but the reality of what we’ve developed is far more mundane. ... Show More
Oct 2025
Advances in Garbled Circuits
MT25 Strachey Lecture - Professor Rafail Ostrovsky: Advances in Garbled Circuits Nearly 40 years ago, Andy Yao proposed the construction of “Garbled Circuits,” which had an enormous impact on the field of secure computation -- both in theory and in practice. In Garbled Circuits, ... Show More
48m 12s
Aug 2024
AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki
In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fa ... Show More
25m 37s
Nov 2024
AI and the Future of Math, with DeepMind’s AlphaProof Team
In this week’s episode of No Priors, Sarah and Elad sit down with the Google DeepMind team behind AlphaProof, Laurent Sartran, Rishi Mehta, and Thomas Hubert. AlphaProof is a new reinforcement learning-based system for formal math reasoning that recently reached a silver-medal st ... Show More
39m 21s
Feb 2017
MLG 002 Difference Between Artificial Intelligence, Machine Learning, Data Science
<div> <div> <p>Artificial intelligence is the automation of tasks that require human intelligence, encompassing fields like natural language processing, perception, planning, and robotics, with machine learning emerging as the primary method to recognize patterns in data and make ... Show More
1h 5m
Oct 2025
Evals, error analysis, and better prompts: A systematic approach to improving your AI products | Hamel Husain (ML engineer)
Hamel Husain, an AI consultant and educator, shares his systematic approach to improving AI product quality through error analysis, evaluation frameworks, and prompt engineering. In this episode, he demonstrates how product teams can move beyond “vibe checking” their AI systems t ... Show More
54m 48s
<p>In episode 66 of The Gradient Podcast, <a target="_blank" href="https://twitter.com/spaniel_bashir">Daniel Bashir</a> speaks to <a target="_blank" href="https://twitter.com/soumithchintala?s=20">Soumith Chintala</a>.</p><p>Soumith is a Research Engineer at Meta AI Research in ... Show More
