E1005: Scale AI CEO & Co-founder Alexandr Wang creates training data for all AI applications to improve machine learning, shares insights on the future of autonomous vehicles, China’s AI advantages ov

1:04 Jason intros Alexandr

2:19 Alexandr shares his personal startup history

5:17 How & why did Scale start?

8:26 What is the best example of Scale in practice? What problem are they solving?

10:44 Video demo of Scale's platform

15:34 Acquiring the scale.com domain name & insights on the unique spelling of Alexandr

17:31 How does Scale deal with data-sharing between customers?

21:34 LIDAR vs. non-LIDAR... or both?

32:29 When will we have capable self-driving vehicles from Palo Alto to San Francisco? Over/under 2030? How will gov't regulations affect self-driving?

36:03 China vs. US in the race of self-driving

41:22 Explainability in ML

47:26 Does it matter that we sometimes don't know the answer to ML systems?

51:39 Should explainability have to be proven in ML?

55:13 How should inherently biased data-sets (like US justice system) be handled via ML?

1:00:00 Importance of focusing on higher-value work

1:02:41 Are dangers of AI overblown?

1:08:50 Will "General AI" happen in our lifetime?

1:12:26 What's the next major AI trend after self-driving?

1:23:46 Does Alexandr remember a time before the Internet?

1:26:35 Jason plays "good tweet/bad tweet" with Alexandr