Towards Data Science

131 Episodes

1. 131. Jeremie Harris - TDS Podcast Finale: The future of AI, and the risks that come with it

   Published: 10/19/2022
2. 130. Edouard Harris - New Research: Advanced AI may tend to seek power *by default*

   Published: 10/12/2022
3. 129. Amber Teng - Building apps with a new generation of language models

   Published: 10/5/2022
4. 128. David Hirko - AI observability and data as a cybersecurity weakness

   Published: 9/28/2022
5. 127. Matthew Stewart - The emerging world of ML sensors

   Published: 9/21/2022
6. 126. JR King - Does the brain run on deep learning?

   Published: 9/14/2022
7. 125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?

   Published: 9/7/2022
8. 124. Alex Watson - Synthetic data could change everything

   Published: 5/18/2022
9. 123. Ala Shaabana and Jacob Steeves - AI on the blockchain (it actually might just make sense)

   Published: 5/12/2022
10. 122. Sadie St. Lawrence - Trends in data science

    Published: 5/4/2022
11. 121. Alexei Baevski - data2vec and the future of multimodal learning

    Published: 4/27/2022
12. 120. Liam Fedus and Barrett Zoph - AI scaling with mixture of expert models

    Published: 4/20/2022
13. 119. Jaime Sevilla - Projecting AI progress from compute trends

    Published: 4/13/2022
14. 118. Angela Fan - Generating Wikipedia articles with AI

    Published: 4/6/2022
15. 117. Beena Ammanath - Defining trustworthy AI

    Published: 3/30/2022
16. 116. Katya Sedova - AI-powered disinformation, present and future

    Published: 3/23/2022
17. 115. Irina Rish - Out-of-distribution generalization

    Published: 3/9/2022
18. 114. Sam Bowman - Are we *under-hyping* AI?

    Published: 3/2/2022
19. 113. Yaron Singer - Catching edge cases in AI

    Published: 2/9/2022
20. 112. Tali Raveh - AI, single cell genomics, and the new era of computational biology

    Published: 2/2/2022