01:13 Serg's story: computer science, graphics, web

05:10 Serg's transition from web development to data science: optimizing engagement

21:06 Master's in data science after career experience

21:59 Interpretable machine learning

24:21 Intepretation for consumers

25:08 Interpretation for engineers

28:42 The subjectivity of interpretability

33:34 Agriculture and data

39:49 Climate change and agriculture

41:06 Food insecurity by 2050

44:37 Agriculture excitements

45:15 How people can contribute to food security

• 01:26  - Tristan's story
• 05:53 how life differs between MIT, Meta, and Hugging Face
• 16:04 What's an AI language model?
• 18:58 the importance of data versus AI models or architectures
• 22:25 what makes certain model architectures better
• 23:55 Tristan's AI experience
• 25:50 how AI has changed over the last 10 years
• 30:20 Big AI issues we have not solved. 
• 37:11 The road ahead: Solutions concerns, excitements
• 43:59 advice to the AI consumers

• 1:24 Tristan’s Story
• 5:05 Using AI in music (deep learning)
• 10:31 AI music community
• 12:37 Quality AI-assisted songs
• 13:33: Generating singing with text
• 16:15 Future of AI in music
• 23:25 Augmenting human creativity with AI
• 28:43 The future for artists
• 30:44 AI effect on music consumption by society
• 35:47 How coders can try making music with AI
• 38:48 How non-coders can make music with AI
• 40:35 Resources and articles