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In episode 105 of The Gradient Podcast, Daniel Bashir (twitter.com/spaniel_bashir) speaks to Eric Jang (x.com/ericjang11?s=20).
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Outline:
* () Intro
* () Updates since Eric’s last interview
* () The problem space of humanoid robots
* () Motivations for the book “AI is Good for You”
* () Definitions of AGI
* () ~ AGI timelines ~
* () Do we have the ingredients for AGI?
* () Rediscovering old ideas in AI and robotics
* () Ingredients for AGI
* () Artificial Life
* () Selection at different levels of information—intelligence at different scales
* () AGI as a collective intelligence
* () Human in the loop learning
* () From getting correct answers to doing things correctly
* () Levels of abstraction for modeling decision-making — the neurobiological stack
* () Implementing loneliness and other details for AGI
* () Experience in AI systems
* () Asking for Generalization
* () Linguistic relativity
* () Language vs. complex thought and Fedorenko experiments
* () Efficiency in neural design
* () Generality in the human brain and evolutionary hypotheses
* () Embodiment and real-world robotics
* () Moravec’s Paradox and the importance of embodiment
* () How embodiment fits into the picture—in verification vs. in learning
* () Nonverbal information for training intelligent systems
* () AGI and humanity
* () The positive future with AGI
* () The negative future — technology as a lever
* () AI in the military
* () How AI might contribute to art
* () Eric’s own work and a positive future for AI
* () Outro
Links:
* Eric’s book (evjang.com/book)
* Eric’s Twitter (x.com/ericjang11?s=20) and homepage (evjang.com)
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