Adam Kalai, Microsoft Research

Abstract

An old idea is to design AI systems that improve themselves. We show how to take first steps towards this goal by designing recursively self-improving systems for generating code. That is, starting with a short seed program that improves code at some given task using a language model, the code is used to generate a better improver. We discuss safety concerns and discuss how it may be framed as a game.

[Video]

Speaker bio: Adam Tauman Kalai is a Senior Principal Researcher at Microsoft Research New England. His research includes work on artificial intelligence and algorithms, with a focus on code generation and the responsible use of Language Models. He received his BA from Harvard and PhD from Carnegie Mellon University. He has served as an Assistant Professor at Georgia Tech and the Toyota Technological Institute at Chicago. He is a member of the science team of Project CETI, an interdisciplinary initiative to understand the communication of sperm whales. He has co-chaired AI and crowdsourcing conferences including COLT (the Conference on Learning Theory), HCOMP (the Conference on Human Computation) and NEML. In 2012, he was awarded the Majulook prize.