Towards Data Science

131 Avsnitt

1. 111. Mo Gawdat - Scary Smart: A former Google exec’s perspective on AI risk

   Publicerades: 2022-01-26
2. 110. Alex Turner - Will powerful AIs tend to seek power?

   Publicerades: 2022-01-19
3. 109. Danijar Hafner - Gaming our way to AGI

   Publicerades: 2022-01-12
4. 108. Last Week In AI — 2021: The (full) year in review

   Publicerades: 2022-01-05
5. 107. Kevin Hu - Data observability and why it matters

   Publicerades: 2021-12-15
6. 106. Yang Gao - Sample-efficient AI

   Publicerades: 2021-12-08
7. 105. Yannic Kilcher - A 10,000-foot view of AI

   Publicerades: 2021-12-01
8. 104. Ken Stanley - AI without objectives

   Publicerades: 2021-11-24
9. 103. Gillian Hadfield - How to create explainable AI regulations that actually make sense

   Publicerades: 2021-11-17
10. 102. Wendy Foster - AI ethics as a user experience challenge

    Publicerades: 2021-11-10
11. 101. Ayanna Howard - AI and the trust problem

    Publicerades: 2021-11-03
12. 100. Max Jaderberg - Open-ended learning at DeepMind

    Publicerades: 2021-10-27
13. 99. Margaret Mitchell - (Practical) AI ethics

    Publicerades: 2021-10-20
14. 98. Mike Tung - Are knowledge graphs AI’s next big thing?

    Publicerades: 2021-10-13
15. 97. Anthony Habayeb - The present and future of AI regulation

    Publicerades: 2021-10-06
16. 96. Jan Leike - AI alignment at OpenAI

    Publicerades: 2021-09-29
17. 95. Francesca Rossi - Thinking, fast and slow: AI edition

    Publicerades: 2021-09-22
18. 94. Divya Siddarth - Are we thinking about AI wrong?

    Publicerades: 2021-07-28
19. 93. 2021: A year in AI (so far) - Reviewing the biggest AI stories of 2021 with our friends at the Let’s Talk AI podcast

    Publicerades: 2021-07-21
20. 92. Daniel Filan - Peering into neural nets for AI safety

    Publicerades: 2021-07-14