Melanie Mitchell: Abstraction and Analogy in AI

Melanie Mitchell: Abstraction and Analogy in AI

Author: Daniel Bashir December 15, 2022 Duration: 54:47

Have suggestions for future podcast guests (or other feedback)? Let us know here!

In episode 53 of The Gradient Podcast, Daniel Bashir speaks to Professor Melanie Mitchell.

Professor Mitchell is the Davis Professor at the Santa Fe Institute. Her research focuses on conceptual abstraction, analogy-making, and visual recognition in AI systems. She is the author or editor of six books and her work spans the fields of AI, cognitive science, and complex systems. Her latest book is Artificial Intelligence: A Guide for Thinking Humans

Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter

Outline:

* (00:00) Intro

* (02:20) Melanie’s intro to AI

* (04:35) Melanie’s intellectual influences, AI debates over time

* (10:50) We don’t have the right metrics for empirical study in AI

* (15:00) Why AI is Harder than we Think: the four fallacies

* (20:50) Difficulties in understanding what’s difficult for machines vs humans

* (23:30) Roles for humanlike and non-humanlike intelligence

* (27:25) Whether “intelligence” is a useful word

* (31:55) Melanie’s thoughts on modern deep learning advances, brittleness

* (35:35) Abstraction, Analogies, and their role in AI

* (38:40) Concepts as analogical and what that means for cognition

* (41:25) Where does analogy bottom out

* (44:50) Cognitive science approaches to concepts

* (45:20) Understanding how to form and use concepts is one of the key problems in AI

* (46:10) Approaching abstraction and analogy, Melanie’s work / the Copycat architecture

* (49:50) Probabilistic program induction as a promising approach to intelligence

* (52:25) Melanie’s advice for aspiring AI researchers

* (54:40) Outro

Links:

* Melanie’s homepage and Twitter

* Papers

* Difficulties in AI, hype cycles

* Why AI is Harder than we think

* The Debate Over Understanding in AI’s Large Language Models

* What Does It Mean for AI to Understand?

* Abstraction, analogies, and reasoning

* Abstraction and Analogy-Making in Artificial Intelligence

* Evaluating understanding on conceptual abstraction benchmarks



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
Joanna Bryson: The Problems of Cognition [not-audio_url] [/not-audio_url]

Duration: 1:13:05
In episode 68 of The Gradient Podcast, Daniel Bashir speaks to Professor Joanna Bryson.Professor Bryson is Professor of Ethics and Technology at the Hertie School, where her research focuses on the impact of technology o…
Daniel Situnayake: AI on the Edge [not-audio_url] [/not-audio_url]

Duration: 1:58:07
In episode 67 of The Gradient Podcast, Daniel Bashir speaks to Daniel Situnayake. Daniel is head of Machine Learning at Edge Impulse. He is co-author of the O’Reilly books "AI at the Edge" and "TinyML". Previously, he’s…
Soumith Chintala: PyTorch [not-audio_url] [/not-audio_url]

Duration: 1:08:20
In episode 66 of The Gradient Podcast, Daniel Bashir speaks to Soumith Chintala.Soumith is a Research Engineer at Meta AI Research in NYC. He is the co-creator and lead of Pytorch, and maintains a number of other open-so…
Sewon Min: The Science of Natural Language [not-audio_url] [/not-audio_url]

Duration: 1:42:44
In episode 65 of The Gradient Podcast, Daniel Bashir speaks to Sewon Min.Sewon is a fifth-year PhD student in the NLP group at the University of Washington, advised by Hannaneh Hajishirzi and Luke Zettlemoyer. She is a p…
Richard Socher: Re-Imagining Search [not-audio_url] [/not-audio_url]

Duration: 1:37:49
In episode 64 of The Gradient Podcast, Daniel Bashir speaks to Richard Socher.Richard is founder and CEO of you.com, a new search engine that lets you personalize your search workflow and eschews tracking and invasive ad…
Joe Edelman: Meaning-Aligned AI [not-audio_url] [/not-audio_url]

Duration: 1:06:23
In episode 63 of The Gradient Podcast, Daniel Bashir speaks to Joe Edelman.Joe developed the meaning-based organizational metrics at Couchsurfing.com, then co-founded the Center for Humane Technology with Tristan Harris,…
Ed Grefenstette: Language, Semantics, Cohere [not-audio_url] [/not-audio_url]

Duration: 1:14:16
In episode 62 of The Gradient Podcast, Daniel Bashir speaks to Ed Grefenstette.Ed is Head of Machine Learning at Cohere and an Honorary Professor at University College London. He previously held research scientist positi…
Ken Liu: What Science Fiction Can Teach Us [not-audio_url] [/not-audio_url]

Duration: 2:02:40
In episode 61 of The Gradient Podcast, Daniel Bashir speaks to Ken Liu.Ken is an author of speculative fiction. A winner of the Nebula, Hugo, and World Fantasy awards, he is the author of silkpunk epic fantasy series Dan…
Hattie Zhou: Lottery Tickets and Algorithmic Reasoning in LLMs [not-audio_url] [/not-audio_url]

Duration: 1:42:59
In episode 60 of The Gradient Podcast, Daniel Bashir speaks to Hattie Zhou.Hattie is a PhD student at the Université de Montréal and Mila. Her research focuses on understanding how and why neural networks work, based on…