Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI

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Melanie Mitchell is a professor of computer science at Portland State University and an external professor at Santa Fe Institute. She has worked on and written about artificial intelligence from fascinating perspectives including adaptive complex systems, genetic algorithms, and the Copycat cognitive architecture which places the process of analogy making at the core of human cognition. From her doctoral work with her advisors Douglas Hofstadter and John Holland to today, she has contributed a lot of important ideas to the field of AI, including her recent book, simply called Artificial Intelligence: A Guide for Thinking Humans.

This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode Links:
AI: A Guide for Thinking Humans (book)

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
02:33 – The term “artificial intelligence”
06:30 – Line between weak and strong AI
12:46 – Why have people dreamed of creating AI?
15:24 – Complex systems and intelligence
18:38 – Why are we bad at predicting the future with regard to AI?
22:05 – Are fundamental breakthroughs in AI needed?
25:13 – Different AI communities
31:28 – Copycat cognitive architecture
36:51 – Concepts and analogies
55:33 – Deep learning and the formation of concepts
1:09:07 – Autonomous vehicles
1:20:21 – Embodied AI and emotion
1:25:01 – Fear of superintelligent AI
1:36:14 – Good test for intelligence
1:38:09 – What is complexity?
1:43:09 – Santa Fe Institute
1:47:34 – Douglas Hofstadter
1:49:42 – Proudest moment

Jim Gates: Supersymmetry, String Theory and Proving Einstein Right

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Jim Gates (S James Gates Jr.) is a theoretical physicist and professor at Brown University working on supersymmetry, supergravity, and superstring theory. He served on former President Obama’s Council of Advisors on Science and Technology. He is the co-author of a new book titled Proving Einstein Right about the scientists who set out to prove Einstein’s theory of relativity.

This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode Links:
Proving Einstein Right (book)

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:13 – Will we ever venture outside our solar system?
05:16 – When will the first human step foot on Mars?
11:14 – Are we alone in the universe?
13:55 – Most beautiful idea in physics
16:29 – Can the mind be digitized?
21:15 – Does the possibility of superintelligence excite you?
22:25 – Role of dreaming in creativity and mathematical thinking
30:51 – Existential threats
31:46 – Basic particles underlying our universe
41:28 – What is supersymmetry?
52:19 – Adinkra symbols
1:00:24 – String theory
1:07:02 – Proving Einstein right and experimental validation of general relativity
1:19:07 – Richard Feynman
1:22:01 – Barack Obama’s Council of Advisors on Science and Technology
1:30:20 – Exciting problems in physics that are just within our reach
1:31:26 – Mortality

Sebastian Thrun: Flying Cars, Autonomous Vehicles, and Education

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Sebastian Thrun is one of the greatest roboticists, computer scientists, and educators of our time. He led development of the autonomous vehicles at Stanford that won the 2005 DARPA Grand Challenge and placed second in the 2007 DARPA Urban Challenge. He then led the Google self-driving car program which launched the self-driving revolution. He taught the popular Stanford course on Artificial Intelligence in 2011 which was one of the first MOOCs. That experience led him to co-found Udacity, an online education platform. He is also the CEO of Kitty Hawk, a company working on building flying cars or more technically eVTOLS which stands for electric vertical take-off and landing aircraft.

This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:24 – The Matrix
04:39 – Predicting the future 30+ years ago
06:14 – Machine learning and expert systems
09:18 – How to pick what ideas to work on
11:27 – DARPA Grand Challenges
17:33 – What does it take to be a good leader?
23:44 – Autonomous vehicles
38:42 – Waymo and Tesla Autopilot
42:11 – Self-Driving Car Nanodegree
47:29 – Machine learning
51:10 – AI in medical applications
54:06 – AI-related job loss and education
57:51 – Teaching soft skills
1:00:13 – Kitty Hawk and flying cars
1:08:22 – Love and AI
1:13:12 – Life

Michael Stevens: Vsauce

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Michael Stevens is the creator of Vsauce, one of the most popular educational YouTube channel in the world, with over 15 million subscribers and over 1.7 billion views. His videos often ask and answer questions that are both profound and entertaining, spanning topics from physics to psychology. As part of his channel he created 3 seasons of Mind Field, a series that explored human behavior.

This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode links:
Vsauce YouTube: https://www.youtube.com/Vsauce
Vsauce Twitter: https://twitter.com/tweetsauce
Vsauce Instagram: https://www.instagram.com/electricpants/

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
02:26 – Psychology
03:59 – Consciousness
06:55 – Free will
07:55 – Perception vs reality
09:59 – Simulation
11:32 – Science
16:24 – Flat earth
27:04 – Artificial Intelligence
30:14 – Existential threats
38:03 – Elon Musk and the responsibility of having a large following
43:05 – YouTube algorithm
52:41 – Mortality and the meaning of life

Rohit Prasad: Amazon Alexa and Conversational AI

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Rohit Prasad is the vice president and head scientist of Amazon Alexa and one of its original creators.

This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

The episode is also supported by ZipRecruiter. Try it: http://ziprecruiter.com/lexpod

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
04:34 – Her
06:31 – Human-like aspects of smart assistants
08:39 – Test of intelligence
13:04 – Alexa prize
21:35 – What does it take to win the Alexa prize?
27:24 – Embodiment and the essence of Alexa
34:35 – Personality
36:23 – Personalization
38:49 – Alexa’s backstory from her perspective
40:35 – Trust in Human-AI relations
44:00 – Privacy
47:45 – Is Alexa listening?
53:51 – How Alexa started
54:51 – Solving far-field speech recognition and intent understanding
1:11:51 – Alexa main categories of skills
1:13:19 – Conversation intent modeling
1:17:47 – Alexa memory and long-term learning
1:22:50 – Making Alexa sound more natural
1:27:16 – Open problems for Alexa and conversational AI
1:29:26 – Emotion recognition from audio and video
1:30:53 – Deep learning and reasoning
1:36:26 – Future of Alexa
1:41:47 – The big picture of conversational AI

Judea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI

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Judea Pearl is a professor at UCLA and a winner of the Turing Award, that’s generally recognized as the Nobel Prize of computing. He is one of the seminal figures in the field of artificial intelligence, computer science, and statistics. He has developed and championed probabilistic approaches to AI, including Bayesian Networks and profound ideas in causality in general. These ideas are important not just for AI, but to our understanding and practice of science. But in the field of AI, the idea of causality, cause and effect, to many, lies at the core of what is currently missing and what must be developed in order to build truly intelligent systems. For this reason, and many others, his work is worth returning to often.

This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:18 – Descartes and analytic geometry
06:25 – Good way to teach math
07:10 – From math to engineering
09:14 – Does God play dice?
10:47 – Free will
11:59 – Probability
22:21 – Machine learning
23:13 – Causal Networks
27:48 – Intelligent systems that reason with causation
29:29 – Do(x) operator
36:57 – Counterfactuals
44:12 – Reasoning by Metaphor
51:15 – Machine learning and causal reasoning
53:28 – Temporal aspect of causation
56:21 – Machine learning (continued)
59:15 – Human-level artificial intelligence
1:04:08 – Consciousness
1:04:31 – Concerns about AGI
1:09:53 – Religion and robotics
1:12:07 – Daniel Pearl
1:19:09 – Advice for students
1:21:00 – Legacy