Category Archives: ai

#99 – Karl Friston: Neuroscience and the Free Energy Principle

Karl Friston is one of the greatest neuroscientists in history, cited over 245,000 times, known for many influential ideas in brain imaging, neuroscience, and theoretical neurobiology, including the fascinating idea of the free-energy principle for action and perception.

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EPISODE LINKS:
Karl’s Website: https://www.fil.ion.ucl.ac.uk/~karl/
Karl’s Wiki: https://en.wikipedia.org/wiki/Karl_J._Friston

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.

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

OUTLINE:
00:00 – Introduction
01:50 – How much of the human brain do we understand?
05:53 – Most beautiful characteristic of the human brain
10:43 – Brain imaging
20:38 – Deep structure
21:23 – History of brain imaging
32:31 – Neuralink and brain-computer interfaces
43:05 – Free energy principle
1:24:29 – Meaning of life

#98 – Kate Darling: Emotional Connection Between Humans and Robots

Kate Darling is a researcher at MIT, interested in social robotics, robot ethics, and generally how technology intersects with society. She explores the emotional connection between human beings and life-like machines, which for me, is one of the most exciting topics in all of artificial intelligence.

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EPISODE LINKS:
Kate’s Website: http://www.katedarling.org/
Kate’s Twitter: https://twitter.com/grok_

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.

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

OUTLINE:
00:00 – Introduction
03:31 – Robot ethics
04:36 – Universal Basic Income
06:31 – Mistreating robots
17:17 – Robots teaching us about ourselves
20:27 – Intimate connection with robots
24:29 – Trolley problem and making difficult moral decisions
31:59 – Anthropomorphism
38:09 – Favorite robot
41:19 – Sophia
42:46 – Designing robots for human connection
47:01 – Why is it so hard to build a personal robotics company?
50:03 – Is it possible to fall in love with a robot?
56:39 – Robots displaying consciousness and mortality
58:33 – Manipulation of emotion by companies
1:04:40 – Intellectual property
1:09:23 – Lessons for robotics from parenthood
1:10:41 – Hope for future of robotics

#97 – Sertac Karaman: Robots That Fly and Robots That Drive

Sertac Karaman is a professor at MIT, co-founder of the autonomous vehicle company Optimus Ride, and is one of top roboticists in the world, including robots that drive and robots that fly.

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EPISODE LINKS:
Sertac’s Website: http://sertac.scripts.mit.edu/web/
Sertac’s Twitter: https://twitter.com/sertackaraman
Optimus Ride: https://www.optimusride.com/

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.

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

OUTLINE:
00:00 – Introduction
01:44 – Autonomous flying vs autonomous driving
06:37 – Flying cars
10:27 – Role of simulation in robotics
17:35 – Game theory and robotics
24:30 – Autonomous vehicle company strategies
29:46 – Optimus Ride
47:08 – Waymo, Tesla, Optimus Ride timelines
53:22 – Achieving the impossible
53:50 – Iterative learning
58:39 – Is Lidar is a crutch?
1:03:21 – Fast autonomous flight
1:18:06 – Most beautiful idea in robotics

#96 – Stephen Schwarzman: Going Big in Business, Investing, and AI

Stephen Schwarzman is the CEO and Co-Founder of Blackstone, one of the world’s leading investment firms with over 530 billion dollars of assets under management. He is one of the most successful business leaders in history, all from humble beginnings back in Philly. I recommend his recent book called What It Takes that tells stories and lessons from this personal journey.

Support this podcast by signing up with these sponsors:
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EPISODE LINKS:
What It Takes (book): https://amzn.to/2WX9cZu

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.

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

OUTLINE:
00:00 – Introduction
04:17 – Going big in business
07:34 – How to recognize an opportunity
16:00 – Solving problems that people have
25:26 – Philanthropy
32:51 – Hope for the new College of Computing at MIT
37:32 – Unintended consequences of technological innovation
42:24 – Education systems in China and United States
50:22 – American AI Initiative
59:53 – Starting a business is a rough ride
1:04:26 – Love and family

#95 – Dawn Song: Adversarial Machine Learning and Computer Security

Dawn Song is a professor of computer science at UC Berkeley with research interests in security, most recently with a focus on the intersection between computer security and machine learning.

Support this podcast by signing up with these sponsors:
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EPISODE LINKS:
Dawn’s Twitter: https://twitter.com/dawnsongtweets
Dawn’s Website: https://people.eecs.berkeley.edu/~dawnsong/
Oasis Labs: https://www.oasislabs.com

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.

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

OUTLINE:
00:00 – Introduction
01:53 – Will software always have security vulnerabilities?
09:06 – Human are the weakest link in security
16:50 – Adversarial machine learning
51:27 – Adversarial attacks on Tesla Autopilot and self-driving cars
57:33 – Privacy attacks
1:05:47 – Ownership of data
1:22:13 – Blockchain and cryptocurrency
1:32:13 – Program synthesis
1:44:57 – A journey from physics to computer science
1:56:03 – US and China
1:58:19 – Transformative moment
2:00:02 – Meaning of life

#94 – Ilya Sutskever: Deep Learning

Ilya Sutskever is the co-founder of OpenAI, is one of the most cited computer scientist in history with over 165,000 citations, and to me, is one of the most brilliant and insightful minds ever in the field of deep learning. There are very few people in this world who I would rather talk to and brainstorm with about deep learning, intelligence, and life than Ilya, on and off the mic.

Support this podcast by signing up with these sponsors:
– Cash App – use code “LexPodcast” and download:
– Cash App (App Store): https://apple.co/2sPrUHe
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EPISODE LINKS:
Ilya’s Twitter: https://twitter.com/ilyasut
Ilya’s Website: https://www.cs.toronto.edu/~ilya/

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.

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

OUTLINE:
00:00 – Introduction
02:23 – AlexNet paper and the ImageNet moment
08:33 – Cost functions
13:39 – Recurrent neural networks
16:19 – Key ideas that led to success of deep learning
19:57 – What’s harder to solve: language or vision?
29:35 – We’re massively underestimating deep learning
36:04 – Deep double descent
41:20 – Backpropagation
42:42 – Can neural networks be made to reason?
50:35 – Long-term memory
56:37 – Language models
1:00:35 – GPT-2
1:07:14 – Active learning
1:08:52 – Staged release of AI systems
1:13:41 – How to build AGI?
1:25:00 – Question to AGI
1:32:07 – Meaning of life

#93 – Daphne Koller: Biomedicine and Machine Learning

Daphne Koller is a professor of computer science at Stanford University, a co-founder of Coursera with Andrew Ng and Founder and CEO of insitro, a company at the intersection of machine learning and biomedicine.

Support this podcast by signing up with these sponsors:
– Cash App – use code “LexPodcast” and download:
– Cash App (App Store): https://apple.co/2sPrUHe
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EPISODE LINKS:
Daphne’s Twitter: https://twitter.com/daphnekoller
Daphne’s Website: https://ai.stanford.edu/users/koller/index.html
Insitro: http://insitro.com

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.

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

OUTLINE:
00:00 – Introduction
02:22 – Will we one day cure all disease?
06:31 – Longevity
10:16 – Role of machine learning in treating diseases
13:05 – A personal journey to medicine
16:25 – Insitro and disease-in-a-dish models
33:25 – What diseases can be helped with disease-in-a-dish approaches?
36:43 – Coursera and education
49:04 – Advice to people interested in AI
50:52 – Beautiful idea in deep learning
55:10 – Uncertainty in AI
58:29 – AGI and AI safety
1:06:52 – Are most people good?
1:09:04 – Meaning of life

#92 – Harry Cliff: Particle Physics and the Large Hadron Collider

Harry Cliff is a particle physicist at the University of Cambridge working on the Large Hadron Collider beauty experiment that specializes in searching for hints of new particles and forces by studying a type of particle called the “beauty quark”, or “b quark”. In this way, he is part of the group of physicists who are searching answers to some of the biggest questions in modern physics. He is also an exceptional communicator of science with some of the clearest and most captivating explanations of basic concepts in particle physics I’ve ever heard.

Support this podcast by signing up with these sponsors:
– ExpressVPN at https://www.expressvpn.com/lexpod
– Cash App – use code “LexPodcast” and download:
– Cash App (App Store): https://apple.co/2sPrUHe
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EPISODE LINKS:
Harry’s Website: https://www.harrycliff.co.uk/
Harry’s Twitter: https://twitter.com/harryvcliff
Beyond the Higgs Lecture: https://www.youtube.com/watch?v=edvdzh9Pggg
Harry’s stand-up: https://www.youtube.com/watch?v=dnediKM_Sts

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.

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

OUTLINE:
00:00 – Introduction
03:51 – LHC and particle physics
13:55 – History of particle physics
38:59 – Higgs particle
57:55 – Unknowns yet to be discovered
59:48 – Beauty quarks
1:07:38 – Matter and antimatter
1:10:22 – Human side of the Large Hadron Collider
1:17:27 – Future of large particle colliders
1:24:09 – Data science with particle physics
1:27:17 – Science communication
1:33:36 – Most beautiful idea in physics

#91 – Jack Dorsey: Square, Cryptocurrency, and Artificial Intelligence

Jack Dorsey is the co-founder and CEO of Twitter and the founder and CEO of Square.

Support this podcast by signing up with these sponsors:
– MasterClass: https://masterclass.com/lex

EPISODE LINKS:
Jack’s Twitter: https://twitter.com/jack
Start Small Tracker: https://bit.ly/2KxdiBL

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.

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

OUTLINE:
00:00 – Introduction
02:48 – Engineering at scale
08:36 – Increasing access to the economy
13:09 – Machine learning at Square
15:18 – Future of the digital economy
17:17 – Cryptocurrency
25:31 – Artificial intelligence
27:49 – Her
29:12 – Exchange with Elon Musk about bots
32:05 – Concerns about artificial intelligence
35:40 – Andrew Yang
40:57 – Eating one meal a day
45:49 – Mortality
47:50 – Meaning of life
48:59 – Simulation

#90 – Dmitry Korkin: Computational Biology of Coronavirus

Dmitry Korkin is a professor of bioinformatics and computational biology at Worcester Polytechnic Institute, where he specializes in bioinformatics of complex disease, computational genomics, systems biology, and biomedical data analytics. I came across Dmitry’s work when in February his group used the viral genome of the COVID-19 to reconstruct the 3D structure of its major viral proteins and their interactions with human proteins, in effect creating a structural genomics map of the coronavirus and making this data open and available to researchers everywhere. We talked about the biology of COVID-19, SARS, and viruses in general, and how computational methods can help us understand their structure and function in order to develop antiviral drugs and vaccines.

Support this podcast by signing up with these sponsors:
– Cash App – use code “LexPodcast” and download:
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EPISODE LINKS:
Dmitry’s Website: http://korkinlab.org/
Dmitry’s Twitter: https://twitter.com/dmkorkin
Dmitry’s Paper that we discuss: https://bit.ly/3eKghEM

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.

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

OUTLINE:
00:00 – Introduction
02:33 – Viruses are terrifying and fascinating
06:02 – How hard is it to engineer a virus?
10:48 – What makes a virus contagious?
29:52 – Figuring out the function of a protein
53:27 – Functional regions of viral proteins
1:19:09 – Biology of a coronavirus treatment
1:34:46 – Is a virus alive?
1:37:05 – Epidemiological modeling
1:55:27 – Russia
2:02:31 – Science bobbleheads
2:06:31 – Meaning of life