Gradient Dissent: Conversations on AI
A podcast by Lukas Biewald
115 Episodio
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Dominik Moritz — Building Intuitive Data Visualization Tools
Pubblicato: 25/03/2021 -
Cade Metz — The Stories Behind the Rise of AI
Pubblicato: 18/03/2021 -
Dave Selinger — AI and the Next Generation of Security Systems
Pubblicato: 11/03/2021 -
Tim & Heinrich — Democraticizing Reinforcement Learning Research
Pubblicato: 04/03/2021 -
Daphne Koller — Digital Biology and the Next Epoch of Science
Pubblicato: 18/02/2021 -
Piero Molino — The Secret Behind Building Successful Open Source Projects
Pubblicato: 11/02/2021 -
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
Pubblicato: 05/02/2021 -
Sean Gourley — NLP, National Defense, and Establishing Ground Truth
Pubblicato: 28/01/2021 -
Peter Wang — Anaconda, Python, and Scientific Computing
Pubblicato: 22/01/2021 -
Chris Anderson — Robocars, Drones, and WIRED Magazine
Pubblicato: 14/01/2021 -
Adrien Treuille — Building Blazingly Fast Tools That People Love
Pubblicato: 04/12/2020 -
Peter Norvig – Singularity Is in the Eye of the Beholder
Pubblicato: 20/11/2020 -
Robert Nishihara — The State of Distributed Computing in ML
Pubblicato: 13/11/2020 -
Ines & Sofie — Building Industrial-Strength NLP Pipelines
Pubblicato: 29/10/2020 -
Daeil Kim — The Unreasonable Effectiveness of Synthetic Data
Pubblicato: 16/10/2020 -
Joaquin Candela — Definitions of Fairness
Pubblicato: 01/10/2020 -
Richard Socher — The Challenges of Making ML Work in the Real World
Pubblicato: 29/09/2020 -
Zack Chase Lipton — The Medical Machine Learning Landscape
Pubblicato: 17/09/2020 -
Anthony Goldbloom — How to Win Kaggle Competitions
Pubblicato: 09/09/2020 -
Suzana Ilić — Cultivating Machine Learning Communities
Pubblicato: 02/09/2020
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.