- MERL Seminar Series.)
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Date & Time:
Wednesday, January 31, 2024; 12:00 PM
Advances in machine learning have led to powerful models for audio and language, proficient in tasks like speech recognition and fluent language generation. Beyond their immense utility in engineering applications, these models offer valuable tools for cognitive science and neuroscience. In this talk, I will demonstrate how these artificial neural network models can be used to understand how the human brain processes language. The first part of the talk will cover how audio neural networks serve as computational accounts for brain activity in the auditory cortex. The second part will focus on the use of large language models, such as those in the GPT family, to non-invasively control brain activity in the human language system.
Greta Tuckute is a PhD candidate in the Department of Brain and Cognitive Sciences at MIT. Before joining MIT, she obtained her bachelor’s and master’s degrees at The University of Copenhagen in Denmark. Greta works at the intersection of neuroscience, artificial intelligence, and cognitive science. She is interested in understanding how language is processed in the human brain and how the representations learned by humans compare to those of artificial systems.