E40: How can brain activity improve how we teach computers to talk?

The Ask AI interview with Dr. Alona Fyshe, Assistant Professor at University of Alberta

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Dr. Alona Fyshe is a leading researcher whose interests include Computational Linguistics, Machine Learning and Neuroscience and her work combines all three areas to study the way the human brain processes language.

Computer models of language are typically built using large bodies of text (corpora) collected from the Internet. These models have become very large and very accurate, but they still fall short in a few ways. First, they need a huge amount of data to train. Secondly, they misjudge meaning when inference or common sense is required.

Using data from brain imaging technologies like EEG and fMRI, Dr. Fyshe's research takes inspiration from what we know about the brain in order to improve language models, making them more efficient and more effective.

Tune in to this episode of the Ask AI podcast as host Melissa Kargiannakis sits down with Dr. Alona Fyshe, Assistant Professor at University of Alberta to ask the question:

How can brain activity improve how we teach computers to talk?

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Episode links

• Dr. Fyshe home

• University of Alberta

• Alberta Machine Intelligence Institute

• Dr. Fyshe on LinkedIn

• Dr. Fyshe on Twitter

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Episode credits

• Sponsor: Microsoft Canada's Free AI Business School

• Sponsor: Cinchy, the Dataware platform that makes Data Integration obsolete

• Chatbot partner: Ada Support

• Series Producer: Chris McLellan

• Episode Host: Jaxson Khan

• Series Editor: James Fajardo

• Original music: Mike LeTourneau

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Ask AI is a volunteer project exploring Canada's fast-emerging artificial intelligence sector. Our projects include thought leader interviews, team check-ins, and live events. To learn more about sponsorships, guest blogs, and volunteering, please contact us or ask our chatbot.