Towards Data Science

131 Episodes

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

   Published: 1/26/2022
2. 110. Alex Turner - Will powerful AIs tend to seek power?

   Published: 1/19/2022
3. 109. Danijar Hafner - Gaming our way to AGI

   Published: 1/12/2022
4. 108. Last Week In AI — 2021: The (full) year in review

   Published: 1/5/2022
5. 107. Kevin Hu - Data observability and why it matters

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

   Published: 12/8/2021
7. 105. Yannic Kilcher - A 10,000-foot view of AI

   Published: 12/1/2021
8. 104. Ken Stanley - AI without objectives

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

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

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

    Published: 11/3/2021
12. 100. Max Jaderberg - Open-ended learning at DeepMind

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

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

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

    Published: 10/6/2021
16. 96. Jan Leike - AI alignment at OpenAI

    Published: 9/29/2021
17. 95. Francesca Rossi - Thinking, fast and slow: AI edition

    Published: 9/22/2021
18. 94. Divya Siddarth - Are we thinking about AI wrong?

    Published: 7/28/2021
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

    Published: 7/21/2021
20. 92. Daniel Filan - Peering into neural nets for AI safety

    Published: 7/14/2021