Understanding Large Language Models' Effects on Programming with Saman Amarasinghe

In this episode

CSAIL Professor Saman Amarasinghe discusses how Large Language Models like Chat GPT, will alter the future of programming. Professor Amarasinghe also examines how structured data fits into the equation.

A full transcript of this podcast can be viewed here.

About the speakers

Professor, MIT EECS

Saman Amarasinghe received a bachelor’s degree in electrical engineering and computer science from Cornell University (1988), a master’s degree and PhD in electrical engineering from Stanford University (1990). Then in 1997, Amarasinghe joined the MIT faculty as an assistant professor and now leads the Commit complier research group at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). He is the world leader in the field of high-performance domain-specific languages. The research focus concentrates on programming languages and compliers that maximize application performance on modern computing platforms. Some of Amarasinghe’s developments include: the Halide, TACO, Simit, StreamIT, StreamJIT, PetaBricks, MILK, Cimple, and GraphIt.

Industry Impact
Program languages and software engineering improve the performance and reliability of computer programs and systems that allow companies around the globe to connect, collaborate, and prosper. Logical and experiential fundamentals help to simplify software development, analysis, and maintenance which are crucial in ensuring the integrity of software running in the cloud. The tools, techniques, and language are shared with the global computing community to foster the production of secure, reliable, and robust computer programs and systems. With that said, programs and software’s prove to be pioneering research and serve as an opportunity to impact the rapid evolution of technology through many companies.