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1
Bridging AI & Science: The Impact of Machine Learning on Material Innovation with Joe Spisak of Meta
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2
Unlocking the Power of Language Models in Enterprise: A Deep Dive with Chris Van Pelt
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3
Providing Greater Access to LLMs with Brandon Duderstadt, Co-Founder and CEO of Nomic AI
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4
Exploring PyTorch and Open-Source Communities: Interview with Soumith Chintala
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5
Andrew Feldman: Advanced AI Accelerators and Processors
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6
Stella Biderman: How EleutherAI Trains and Releases LLMs
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7
Building a Q&A Bot for Weights & Biases' Gradient Dissent Podcast
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8
Aidan Gomez - Scaling LLMs and Accelerating Adoption
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9
Jonathan Frankle: Neural Network Pruning and Training
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10
Sarah Catanzaro — Remembering the Lessons of the Last AI Renaissance
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11
Cristóbal Valenzuela — The Next Generation of Content Creation and AI
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12
Jeremy Howard — The Simple but Profound Insight Behind Diffusion
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13
Jerome Pesenti — Large Language Models, PyTorch, and Meta
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14
D. Sculley — Technical Debt, Trade-offs, and Kaggle
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15
Emad Mostaque — Stable Diffusion, Stability AI, and What’s Next
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16
Jehan Wickramasuriya — AI in High-Stress Scenarios
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17
Will Falcon — Making Lightning the Apple of ML
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18
Aaron Colak — ML and NLP in Experience Management
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19
Jordan Fisher — Skipping the Line with Autonomous Checkout
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20
Drago Anguelov — Robustness, Safety, and Scalability at Waymo
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21
James Cham — Investing in the Intersection of Business and Technology
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22
Tristan Handy — The Work Behind the Data Work
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23
Johannes Otterbach — Unlocking ML for Traditional Companies
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24
Mircea Neagovici — Robotic Process Automation (RPA) and ML
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25
Amelia & Filip — How Pandora Deploys ML Models into Production
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26
Wojciech Zaremba — What Could Make AI Conscious?
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27
Chris Mattmann — ML Applications on Earth, Mars, and Beyond
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28
Piero Molino — The Secret Behind Building Successful Open Source Projects
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29
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
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30
Sean Gourley — NLP, National Defense, and Establishing Ground Truth
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31
Peter Wang — Anaconda, Python, and Scientific Computing
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32
Chris Anderson — Robocars, Drones, and WIRED Magazine
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33
Adrien Treuille — Building Blazingly Fast Tools That People Love
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34
Peter Norvig – Singularity Is in the Eye of the Beholder
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35
Robert Nishihara — The State of Distributed Computing in ML
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36
Ines & Sofie — Building Industrial-Strength NLP Pipelines
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37
Daeil Kim — The Unreasonable Effectiveness of Synthetic Data
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38
Joaquin Candela — Definitions of Fairness
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39
Richard Socher — The Challenges of Making ML Work in the Real World
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40
Zack Chase Lipton — The Medical Machine Learning Landscape
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41
Anthony Goldbloom — How to Win Kaggle Competitions
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42
Suzana Ilić — Cultivating Machine Learning Communities
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43
Jeremy Howard — The Story of fast.ai and Why Python Is Not the Future of ML
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44
Anantha Kancherla — Building Level 5 Autonomous Vehicles
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45
Bharath Ramsundar — Deep Learning for Molecules and Medicine Discovery
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46
Chip Huyen — ML Research and Production Pipelines
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47
Peter Skomoroch — Product Management for AI
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48
Josh Tobin — Productionizing ML Models
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49
Miles Brundage — Societal Impacts of Artificial Intelligence
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50
Hamel Husain — Building Machine Learning Tools
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51
Vicki Boykis — Machine Learning Across Industries
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52
Angela & Danielle — Designing ML Models for Millions of Consumer Robots
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53
Jack Clark — Building Trustworthy AI Systems
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54
Rachael Tatman — Conversational AI and Linguistics
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55
Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars
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56
Brandon Rohrer — Machine Learning in Production for Robots
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57
Sean and Greg — Biology and ML for Drug Discovery
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58
Chris, Shawn, and Lukas — The Weights & Biases Journey
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59
Pete Warden — Practical Applications of TinyML
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60
Pieter Abbeel — Robotics, Startups, and Robotics Startups
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61
Emily M. Bender — Language Models and Linguistics
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62
Chris Albon — ML Models and Infrastructure at Wikimedia
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63
Jensen Huang — NVIDIA's CEO on the Next Generation of AI and MLOps
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64
Peter & Boris — Fine-tuning OpenAI's GPT-3
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65
Ion Stoica — Spark, Ray, and Enterprise Open Source
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66
Stephan Fabel — Efficient Supercomputing with NVIDIA's Base Command Platform
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67
Chris Padwick — Smart Machines for More Sustainable Farming
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68
Kathryn Hume — Financial Models, ML, and 17th-Century Philosophy
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69
Jeff Hammerbacher — From data science to biomedicine
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70
Josh Bloom — The Link Between Astronomy and ML
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71
Xavier Amatriain — Building AI-powered Primary Care
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72
Spence Green — Enterprise-scale Machine Translation
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73
Roger & DJ — The Rise of Big Data and CA's COVID-19 Response
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74
Luis Ceze — Accelerating Machine Learning Systems
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75
Matthew Davis — Bringing Genetic Insights to Everyone
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76
Clément Delangue — The Power of the Open Source Community
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77
Phil Brown — How IPUs are Advancing Machine Intelligence
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78
Alyssa Simpson Rochwerger — Responsible ML in the Real World
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79
Sean Taylor — Business Decision Problems
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80
Polly Fordyce — Microfluidic Platforms and Machine Learning
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81
Adrien Gaidon — Advancing ML Research in Autonomous Vehicles
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82
Nimrod Shabtay — Deployment and Monitoring at Nanit
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83
Vladlen Koltun — The Power of Simulation and Abstraction
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84
Dominik Moritz — Building Intuitive Data Visualization Tools
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85
Cade Metz — The Stories Behind the Rise of AI
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86
Dave Selinger — AI and the Next Generation of Security Systems
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87
Tim & Heinrich — Democraticizing Reinforcement Learning Research
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88
Daphne Koller — Digital Biology and the Next Epoch of Science
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89
Peter Welinder — Deep Reinforcement Learning and Robotics
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