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#111 – Richard Karp: Algorithms and Computational Complexity
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: https://eightsleep.com/lex
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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
03:50 – 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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By Lex Fridman
4.7
1187911,879 ratings
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: https://eightsleep.com/lex
– Cash App – use code “LexPodcast” and download:
– Cash App (App Store): https://apple.co/2sPrUHe
– Cash App (Google Play): https://bit.ly/2MlvP5w
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
03:50 – 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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