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Eric Jang: AI is Good For You
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Eric Jang: AI is Good For You

On the path to AGI, and our collective future with it.
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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

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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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