Towards Data Science

131 Episodo

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Publicado: 2/2/2022