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#111 – Richard Karp: Algorithms and Computational Complexity

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Richard Karp is a professor at Berkeley and one of the most important figures in the history of theoretical computer science. In 1985, he received the Turing Award for his research in the theory of algorithms, including the development of the Edmonds–Karp algorithm for solving the maximum flow problem on networks, Hopcroft–Karp algorithm for finding maximum cardinality matchings in bipartite graphs, and his landmark paper in complexity theory called "Reducibility Among Combinatorial Problems", in which he proved 21 problems to be NP-complete. This paper was probably the most important catalyst in the explosion of interest in the study of NP-completeness and the P vs NP problem.

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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
03:50 - Geometry
09:46 - Visualizing an algorithm
13:00 - A beautiful algorithm
18:06 - Don Knuth and geeks
22:06 - Early days of computers
25:53 - Turing Test
30:05 - Consciousness
33:22 - Combinatorial algorithms
37:42 - Edmonds-Karp algorithm
40:22 - Algorithmic complexity
50:25 - P=NP
54:25 - NP-Complete problems
1:10:29 - Proving P=NP
1:12:57 - Stable marriage problem
1:20:32 - Randomized algorithms
1:33:23 - Can a hard problem be easy in practice?
1:43:57 - Open problems in theoretical computer science
1:46:21 - A strange idea in complexity theory
1:50:49 - Machine learning
1:56:26 - Bioinformatics
2:00:37 - Memory of Richard's father

Richard Karp is a professor at Berkeley and one of the most important figures in the history of theoretical computer science. In 1985, he received the Turing Award for his research in the theory of algorithms, including the development of the Edmonds–Karp algorithm for solving the maximum flow problem on networks, Hopcroft–Karp algorithm for finding maximum cardinality matchings in bipartite graphs, and his landmark paper in complexity theory called “Reducibility Among Combinatorial Problems”, in which he proved 21 problems to be NP-complete. This paper was probably the most important catalyst in the explosion of interest in the study of NP-completeness and the P vs NP problem.
Support this podcast by supporting our sponsors: 
– Eight Sleep: <a href="https://eightsleep.com/lex">https://eightsleep.com/lex</a> 
– Cash App – use code “LexPodcast” and download: 
– Cash App (App Store): <a href="https://apple.co/2sPrUHe">https://apple.co/2sPrUHe</a> 
– Cash App (Google Play): <a href="https://bit.ly/2MlvP5w">https://bit.ly/2MlvP5w</a>
If you would like to get more information about this podcast go to <a href="https://lexfridman.com/ai">https://lexfridman.com/ai</a> or connect with @lexfridman on <a href="https://twitter.com/lexfridman">Twitter</a>, <a href="https://www.linkedin.com/in/lexfridman/">LinkedIn</a>, <a href="https://www.facebook.com/lexfridman">Facebook</a>, <a href="https://medium.com/@lexfridman">Medium</a>, or <a href="https://www.youtube.com/lexfridman">YouTube</a> where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on <a href="https://podcasts.apple.com/us/podcast/artificial-intelligence/id1434243584">Apple Podcasts</a>, follow on <a href="https://open.spotify.com/show/2MAi0BvDc6GTFvKFPXnkCL">Spotify</a>, or support it on <a href="https://www.patreon.com/lexfridman">Patreon</a>.
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 
03:50 – Geometry 
09:46 – Visualizing an algorithm 
13:00 – A beautiful algorithm 
18:06 – Don Knuth and geeks 
22:06 – Early days of computers 
25:53 – Turing Test 
30:05 – Consciousness 
33:22 – Combinatorial algorithms 
37:42 – Edmonds-Karp algorithm 
40:22 – Algorithmic complexity 
50:25 – P=NP 
54:25 – NP-Complete problems 
1:10:29 – Proving P=NP 
1:12:57 – Stable marriage problem 
1:20:32 – Randomized algorithms 
1:33:23 – Can a hard problem be easy in practice? 
1:43:57 – Open problems in theoretical computer science 
1:46:21 – A strange idea in complexity theory 
1:50:49 – Machine learning 
1:56:26 – Bioinformatics 
2:00:37 – Memory of Richard’s father

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#111 – Richard Karp: Algorithms and Computational Complexity

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