AI's Language Leap: MIT CSAIL Associate Professor Jacob Andreas Explores NLP and LLMs

In this episode

MIT CSAIL Associate Professor Jacob Andreas walks listeners through how LLMs like ChatGPT evolved from academic curiosities to industry-disrupting technologies. 


Reflecting on the transformations he has observed in AI research, Professor Andreas discusses how some ideas—like linking NLP research to cognitive science—have taken a backseat, while others—like the importance of large-scale training data—remain central.

 
He offers insights on AI use cases, the emergence of models like DeepSeek, and the critical role of human oversight in AI deployment. Acknowledging both the excitement and concerns surrounding AI, Professor Andreas believes that educators and industry alike face a challenge in keeping pace with the ‘moving target’ of AI progress. 


Plus: learn how AI can be used to decode the language of sperm whales!

 

MIT's CSAIL Alliances Podcast is your guide to how AI & computer science research impact how we live, work, play, and learn. Listener discounts, meet the host, and more: csail.mit.edu/podcast

 

For a full, uncut video version of this show (shot in Professor Andreas' MIT CSAIL office!), watch on YouTube:


 

About the speakers

Associate Professor, MIT EECS

Jacob Andreas is interested in language as a communicative and computational tool. People learn to understand and generate novel utterances from remarkably little data. Having learned language, we use it acquire new ideas and to structure our reasoning. Current machine learning techniques fall short of human abilities in both their capacity to learn language and learn from language about the rest of the world. His research aims to (1) understand the computational mechanisms that make efficient language learning possible, and (2) build general-purpose intelligent systems that can communicate effectively with humans and learn from human guidance.

Jacob is an assistant professor at MIT in EECS and CSAIL. he did his PhD work at Berkeley, where he was a member of the Berkeley NLP Group and the Berkeley AI Research Lab. He also spent time with the Cambridge NLIP Group, and the Center for Computational Learning Systems and NLP Group at Columbia.