Machine Learning Street Talk (MLST)
Podcast készítő Machine Learning Street Talk (MLST)

Kategóriák:
217 Epizód
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SWaV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments (Mathilde Caron)
Közzétéve: 2020. 09. 14. -
UK Algoshambles, Neuralink, GPT-3 and Intelligence
Közzétéve: 2020. 09. 07. -
Sayak Paul
Közzétéve: 2020. 07. 17. -
Robert Lange on NN Pruning and Collective Intelligence
Közzétéve: 2020. 07. 08. -
WelcomeAIOverlords (Zak Jost)
Közzétéve: 2020. 06. 30. -
Facebook Research - Unsupervised Translation of Programming Languages
Közzétéve: 2020. 06. 24. -
Francois Chollet - On the Measure of Intelligence
Közzétéve: 2020. 06. 19. -
OpenAI GPT-3: Language Models are Few-Shot Learners
Közzétéve: 2020. 06. 06. -
Jordan Edwards: ML Engineering and DevOps on AzureML
Közzétéve: 2020. 06. 03. -
One Shot and Metric Learning - Quadruplet Loss (Machine Learning Dojo)
Közzétéve: 2020. 06. 02. -
Harri Valpola: System 2 AI and Planning in Model-Based Reinforcement Learning
Közzétéve: 2020. 05. 25. -
ICLR 2020: Yoshua Bengio and the Nature of Consciousness
Közzétéve: 2020. 05. 22. -
ICLR 2020: Yann LeCun and Energy-Based Models
Közzétéve: 2020. 05. 19. -
The Lottery Ticket Hypothesis with Jonathan Frankle
Közzétéve: 2020. 05. 19. -
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Közzétéve: 2020. 05. 19. -
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Közzétéve: 2020. 05. 02. -
Exploring Open-Ended Algorithms: POET
Közzétéve: 2020. 04. 24.
Welcome! We engage in fascinating discussions with pre-eminent figures in the AI field. Our flagship show covers current affairs in AI, cognitive science, neuroscience and philosophy of mind with in-depth analysis. Our approach is unrivalled in terms of scope and rigour – we believe in intellectual diversity in AI, and we touch on all of the main ideas in the field with the hype surgically removed. MLST is run by Tim Scarfe, Ph.D (https://www.linkedin.com/in/ecsquizor/) and features regular appearances from MIT Doctor of Philosophy Keith Duggar (https://www.linkedin.com/in/dr-keith-duggar/).