Clark Barrett - Automated Reasoning, SMT Solvers, Artificial Intelligence • YASP #2
Channel: Yet Another Science Podcast (YASP)
Date: 2023-03-30

Clark Barrett is a Professor (Research) of Computer Science at Stanford University. Before coming to Stanford in 2016, he was an Associate Professor of Computer Science at the Courant Institute of Mathematical Sciences at New York University. His expertise is in automated reasoning and its applications. His PhD dissertation (Stanford, 2003) introduced a novel automated reasoning technique now known as Satisfiability Modulo Theories (SMT). He was an early pioneer in formal hardware verification as part of 0-in Design Automation (now part of Siemens/Mentor Graphics), where he helped build one of the first industrially successful assertion-based verification tool-sets for hardware. More recently, he has also pioneered techniques for applying formal methods to neural networks. His current work focuses on the development and application of automated reasoning techniques to improve reliability and security of software, hardware, and machine learning systems. He is the director of the Stanford Center for Automated Reasoning (Centaur) and co-director of the Stanford Center for AI Safety. He is an ACM Distinguished Scientist and a winner of the 2021 Computer Aided Verification (CAV) award.

GUEST LINKS:
Clark's Website: https://theory.stanford.edu/~barrett/
Clark's Linkedin: https://www.linkedin.com/in/clark-barrett-a5b157/

PODCAST INFO:
Podcast Website: https://www.yasppodcast.com/
Podcast Twitter: https://twitter.com/yasp_podcast

Timestamps
0:00 Intro
ACT 1
0:10 The Automated Reasoning Problem
5:35 Solving Hard and Open Research Problems
9:48 Automated Verification and Safety Critical Systems
19:37 What got you excited when you were a young scholar?
ACT 2
23:05 Satisfiability Modulo Theories (SMT)
28:23 What do these problems look like? Theories, Syntax, Semantics
30:14 Certificate Validity Checker(CVC), CVC5
34:28 Engineering an SMT Solver
38:34 Research Projects with SMT Solvers
41:26 Complexity, Quantifiers, and Undecidability
49:35 AI, Neural Networks, SMT Solvers
55:08 Solving new Research Problems with SMT Solvers
ACT 3
57:44 Solving the modern Entscheidungsproblem
1:01:44 How Amazon Uses SMT Solvers, Zelkova
1:06:48 Malicious use of Automated Reasoning, Hacking Systems
1:09:25 Privacy, Governments
1:11:46 Big Questions, Artificial Intelligence, AGI, Are we close? Fear of AI
1:18:33 Combining logic and machine learning. Neurosymbolic AI
1:21:02 Safe and Explainable AI with Automated Reasoning
1:27:53 Biggest open Questions and Challenges in Automated Reasoning
1:33:33 Outro