Eric Jang: AI is Good For You

Eric Jang: AI is Good For You

Author: Daniel Bashir January 4, 2024 Duration: 1:29:57

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



Get full access to The Gradient at thegradientpub.substack.com/subscribe

Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
Author: Language: English Episodes: 100

The Gradient: Perspectives on AI
Podcast Episodes
C. Thi Nguyen: Values, Legibility, and Gamification [not-audio_url] [/not-audio_url]

Duration: 1:30:13
Episode 127I spoke with Christopher Thi Nguyen about:* How we lose control of our values* The tradeoffs of legibility, aggregation, and simplification* Gamification and its risksEnjoy—and let me know what you think!C. Th…
Vivek Natarajan: Towards Biomedical AI [not-audio_url] [/not-audio_url]

Duration: 1:55:03
Episode 126I spoke with Vivek Natarajan about:* Improving access to medical knowledge with AI* How an LLM for medicine should behave* Aspects of training Med-PaLM and AMIE* How to facilitate appropriate amounts of trust…
Thomas Mullaney: A Global History of the Information Age [not-audio_url] [/not-audio_url]

Duration: 1:43:45
Episode 125False universalism freaks me out. It doesn’t freak me out as a first principle because of epistemic violence; it freaks me out because it works. I spoke with Professor Thomas Mullaney about:* Telling stories a…
Seth Lazar: Normative Philosophy of Computing [not-audio_url] [/not-audio_url]

Duration: 1:50:17
Episode 124You may think you’re doing a priori reasoning, but actually you’re just over-generalizing from your current experience of technology.I spoke with Professor Seth Lazar about:* Why managing near-term and long-te…
Suhail Doshi: The Future of Computer Vision [not-audio_url] [/not-audio_url]

Duration: 1:08:07
Episode 123I spoke with Suhail Doshi about:* Why benchmarks aren’t prepared for tomorrow’s AI models* How he thinks about artists in a world with advanced AI tools* Building a unified computer vision model that can gener…
Azeem Azhar: The Exponential View [not-audio_url] [/not-audio_url]

Duration: 1:46:25
Episode 122I spoke with Azeem Azhar about:* The speed of progress in AI* Historical context for some of the terminology we use and how we think about technology* What we might want our future to look likeAzeem is an entr…
David Thorstad: Bounded Rationality and the Case Against Longtermism [not-audio_url] [/not-audio_url]

Duration: 2:19:02
Episode 122I spoke with Professor David Thorstad about:* The practical difficulties of doing interdisciplinary work* Why theories of human rationality should account for boundedness, heuristics, and other cognitive limit…
Michael Sipser: Problems in the Theory of Computation [not-audio_url] [/not-audio_url]

Duration: 1:28:21
In episode 119 of The Gradient Podcast, Daniel Bashir speaks to Professor Michael Sipser.Professor Sipser is the Donner Professor of Mathematics and member of the Computer Science and Artificial Intelligence Laboratory a…