In episode 105 of The Gradient Podcast, Daniel Bashir speaks to Eric Jang.
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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
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