Gradient Dissent: Conversations on AI
Podcast tekijän mukaan Lukas Biewald
120 Jaksot
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Polly Fordyce — Microfluidic Platforms and Machine Learning
Julkaistiin: 29.4.2021 -
Adrien Gaidon — Advancing ML Research in Autonomous Vehicles
Julkaistiin: 22.4.2021 -
Nimrod Shabtay — Deployment and Monitoring at Nanit
Julkaistiin: 15.4.2021 -
Chris Mattmann — ML Applications on Earth, Mars, and Beyond
Julkaistiin: 8.4.2021 -
Vladlen Koltun — The Power of Simulation and Abstraction
Julkaistiin: 1.4.2021 -
Dominik Moritz — Building Intuitive Data Visualization Tools
Julkaistiin: 25.3.2021 -
Cade Metz — The Stories Behind the Rise of AI
Julkaistiin: 18.3.2021 -
Dave Selinger — AI and the Next Generation of Security Systems
Julkaistiin: 11.3.2021 -
Tim & Heinrich — Democraticizing Reinforcement Learning Research
Julkaistiin: 4.3.2021 -
Daphne Koller — Digital Biology and the Next Epoch of Science
Julkaistiin: 18.2.2021 -
Piero Molino — The Secret Behind Building Successful Open Source Projects
Julkaistiin: 11.2.2021 -
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
Julkaistiin: 5.2.2021 -
Sean Gourley — NLP, National Defense, and Establishing Ground Truth
Julkaistiin: 28.1.2021 -
Peter Wang — Anaconda, Python, and Scientific Computing
Julkaistiin: 22.1.2021 -
Chris Anderson — Robocars, Drones, and WIRED Magazine
Julkaistiin: 14.1.2021 -
Adrien Treuille — Building Blazingly Fast Tools That People Love
Julkaistiin: 4.12.2020 -
Peter Norvig – Singularity Is in the Eye of the Beholder
Julkaistiin: 20.11.2020 -
Robert Nishihara — The State of Distributed Computing in ML
Julkaistiin: 13.11.2020 -
Ines & Sofie — Building Industrial-Strength NLP Pipelines
Julkaistiin: 29.10.2020 -
Daeil Kim — The Unreasonable Effectiveness of Synthetic Data
Julkaistiin: 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.