Gradient Dissent: Conversations on AI
Een podcast door Lukas Biewald
120 Afleveringen
-
Polly Fordyce — Microfluidic Platforms and Machine Learning
Gepubliceerd: 29-4-2021 -
Adrien Gaidon — Advancing ML Research in Autonomous Vehicles
Gepubliceerd: 22-4-2021 -
Nimrod Shabtay — Deployment and Monitoring at Nanit
Gepubliceerd: 15-4-2021 -
Chris Mattmann — ML Applications on Earth, Mars, and Beyond
Gepubliceerd: 8-4-2021 -
Vladlen Koltun — The Power of Simulation and Abstraction
Gepubliceerd: 1-4-2021 -
Dominik Moritz — Building Intuitive Data Visualization Tools
Gepubliceerd: 25-3-2021 -
Cade Metz — The Stories Behind the Rise of AI
Gepubliceerd: 18-3-2021 -
Dave Selinger — AI and the Next Generation of Security Systems
Gepubliceerd: 11-3-2021 -
Tim & Heinrich — Democraticizing Reinforcement Learning Research
Gepubliceerd: 4-3-2021 -
Daphne Koller — Digital Biology and the Next Epoch of Science
Gepubliceerd: 18-2-2021 -
Piero Molino — The Secret Behind Building Successful Open Source Projects
Gepubliceerd: 11-2-2021 -
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
Gepubliceerd: 5-2-2021 -
Sean Gourley — NLP, National Defense, and Establishing Ground Truth
Gepubliceerd: 28-1-2021 -
Peter Wang — Anaconda, Python, and Scientific Computing
Gepubliceerd: 22-1-2021 -
Chris Anderson — Robocars, Drones, and WIRED Magazine
Gepubliceerd: 14-1-2021 -
Adrien Treuille — Building Blazingly Fast Tools That People Love
Gepubliceerd: 4-12-2020 -
Peter Norvig – Singularity Is in the Eye of the Beholder
Gepubliceerd: 20-11-2020 -
Robert Nishihara — The State of Distributed Computing in ML
Gepubliceerd: 13-11-2020 -
Ines & Sofie — Building Industrial-Strength NLP Pipelines
Gepubliceerd: 29-10-2020 -
Daeil Kim — The Unreasonable Effectiveness of Synthetic Data
Gepubliceerd: 16-10-2020
Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Dive into fascinating conversations with industry giants from NVIDIA, Meta, Google, Lyft, OpenAI, and more. Explore the cutting-edge of AI and learn the intricacies of bringing models into production.