Machine Learning Street Talk (MLST)

Podcast készítő Machine Learning Street Talk (MLST)

Kategóriák:

217 Epizód

  1. SWaV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments (Mathilde Caron)

    Közzétéve: 2020. 09. 14.
  2. UK Algoshambles, Neuralink, GPT-3 and Intelligence

    Közzétéve: 2020. 09. 07.
  3. Sayak Paul

    Közzétéve: 2020. 07. 17.
  4. Robert Lange on NN Pruning and Collective Intelligence

    Közzétéve: 2020. 07. 08.
  5. WelcomeAIOverlords (Zak Jost)

    Közzétéve: 2020. 06. 30.
  6. Facebook Research - Unsupervised Translation of Programming Languages

    Közzétéve: 2020. 06. 24.
  7. Francois Chollet - On the Measure of Intelligence

    Közzétéve: 2020. 06. 19.
  8. OpenAI GPT-3: Language Models are Few-Shot Learners

    Közzétéve: 2020. 06. 06.
  9. Jordan Edwards: ML Engineering and DevOps on AzureML

    Közzétéve: 2020. 06. 03.
  10. One Shot and Metric Learning - Quadruplet Loss (Machine Learning Dojo)

    Közzétéve: 2020. 06. 02.
  11. Harri Valpola: System 2 AI and Planning in Model-Based Reinforcement Learning

    Közzétéve: 2020. 05. 25.
  12. ICLR 2020: Yoshua Bengio and the Nature of Consciousness

    Közzétéve: 2020. 05. 22.
  13. ICLR 2020: Yann LeCun and Energy-Based Models

    Közzétéve: 2020. 05. 19.
  14. The Lottery Ticket Hypothesis with Jonathan Frankle

    Közzétéve: 2020. 05. 19.
  15. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

    Közzétéve: 2020. 05. 19.
  16. CURL: Contrastive Unsupervised Representations for Reinforcement Learning

    Közzétéve: 2020. 05. 02.
  17. Exploring Open-Ended Algorithms: POET

    Közzétéve: 2020. 04. 24.

11 / 11

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/).

Visit the podcast's native language site