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Eric Jang: AI is Good For You
Manage episode 393538612 series 2975159
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:
Get full access to The Gradient at thegradientpub.substack.com/subscribe
130 episoade
Manage episode 393538612 series 2975159
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:
Get full access to The Gradient at thegradientpub.substack.com/subscribe
130 episoade
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