Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety?
The TDS Podcast is back with an exciting episode on the art of the possible when it comes to China AI policy. Ryan Fedasiuk, a Research Analyst at Georgetown University's Center for Security and Emerging Technology and Adjunct Fellow at the Center for a New American Security, joined host Jeremie Harris to discuss the U.S. and China's shared interest in building safe AI, how reach side views the other, and what realistic China AI policy looks.
Intro music:
➞ Artist: Ron Gelinas
➞ Track Title: Daybreak Chill Blend (original mix)
➞ Link to Track: https://youtu.be/d8Y2sKIgFWc
0:00 Intro + disclaimer
2:15 China as a core point of focus
4:30 Chinese AI strategy
10:00 Competition as risk
17:20 Having constructive conversations
22:20 Understanding China’s policies
27:15 A shared interest in AI alignment
32:45 Issues with regulating AI on an international level
40:15 Is collaboration a good thing?
44:15 Impact of the highly scaled transformer models trend
47:15 Wrap-up
Видео Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety? канала Towards Data Science
Intro music:
➞ Artist: Ron Gelinas
➞ Track Title: Daybreak Chill Blend (original mix)
➞ Link to Track: https://youtu.be/d8Y2sKIgFWc
0:00 Intro + disclaimer
2:15 China as a core point of focus
4:30 Chinese AI strategy
10:00 Competition as risk
17:20 Having constructive conversations
22:20 Understanding China’s policies
27:15 A shared interest in AI alignment
32:45 Issues with regulating AI on an international level
40:15 Is collaboration a good thing?
44:15 Impact of the highly scaled transformer models trend
47:15 Wrap-up
Видео Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety? канала Towards Data Science
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Nicolas Miailhe - AI risk is a global problemYan Li - The surprising challenges of global AI philanthropyKevin Hu - Data observability and why it mattersTan Vachiramon - Choosing the right algorithm for your real-world problem (TDS Podcast - Clip)Danijar Hafner - Gaming our way to AGIBeena Ammanath - Defining trustworthy AIScaling Machine Learning | Razvan PeteanuPanel: Creative Ways to Collect & Use Data for AI | H. Ngo, S. Sun, H. Kontozopoulos, and R. TabriziGeorge Hayward: comedian, lawyer and data scientist (TDS Podcast - Clip)Explaining With Impact | Sheldon Fernandez and Michael St. JulesBen Garfinkel - Superhuman AI and the future of democracy and governmentLast Week In AI — 2021: The (full) year in reviewEliano Marques - The (evolving) world of AI privacy and data securityJoaquin Quinioñero-Candela - Responsible AI at FacebookIrina Rish - Out-of-distribution generalizationReal Talk with the Director of Data Science at Columbia UniversityNew to Data Visualization? Start with New York City | Thomas Hikaru ClarkMax Jaderberg - Open-ended learning at DeepMindKatya Sedova - AI-powered disinformation, present and futureStuart Armstrong - AI: Humanity's Endgame?Fail to Scale | Ian Scott