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In episode 105 of The Gradient Podcast, Daniel Bashir speaks to Eric Jang. Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter Outline: * (00:00) Intro * (01:25) Updates since Eric’s last interview * (06:07) The problem space of humanoid robots * (08:42) Motivations for the book “AI is Good for You” * (12:20) Definitions of AGI * (14:35) ~ AGI timelines ~ * (16:33) Do we have the ingredients for AGI? * (18:58) Rediscovering old ideas in AI and robotics * (22:13) Ingredients for AGI * (22:13) Artificial Life * (25:02) Selection at different levels of information—intelligence at different scales * (32:34) AGI as a collective intelligence * (34:53) Human in the loop learning * (37:38) From getting correct answers to doing things correctly * (40:20) Levels of abstraction for modeling decision-making — the neurobiological stack * (44:22) Implementing loneliness and other details for AGI * (47:31) Experience in AI systems * (48:46) Asking for Generalization * (49:25) Linguistic relativity * (52:17) Language vs. complex thought and Fedorenko experiments * (54:23) Efficiency in neural design * (57:20) Generality in the human brain and evolutionary hypotheses * (59:46) Embodiment and real-world robotics * (1:00:10) Moravec’s Paradox and the importance of embodiment * (1:05:33) How embodiment fits into the picture—in verification vs. in learning * (1:10:45) Nonverbal information for training intelligent systems * (1:11:55) AGI and humanity * (1:12:20) The positive future with AGI * (1:14:55) The negative future — technology as a lever * (1:16:22) AI in the military * (1:20:30) How AI might contribute to art * (1:25:41) Eric’s own work and a positive future for AI * (1:29:27) Outro Links: * Eric’s book * Eric’s Twitter and homepage
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