Creating Robust Language Representations with Jamie Macbeth
EPISODE 477
|
APRIL
22,
2021
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About this Episode
Today we're joined by Jamie Macbeth, an Assistant Professor in the Department of Computer Science at Smith College.
In our conversation with Jamie, we explore his work at the intersection of cognitive systems and natural language understanding, and how to use AI as a vehicle for better understanding human intelligence. We discuss the tie that binds these domains together, if the tasks are the same as traditional NLU tasks, and what are the specific things he's trying to gain deeper insights into.
One of the unique aspects of Jamie's research is that he takes an "old-school AI" approach, and to that end, we discuss the models he handcrafts to generate language. Finally, we examine how he evaluates the performance of his representations if he's not playing the SOTA "game," what he bookmarks against, identifying deficiencies in deep learning systems, and the exciting directions for his upcoming research.
About the Guest
Jamie Macbeth
Smith College
Resources
- Book: Scripts, Plans, Goals, and Understanding: An Inquiry Into Human Knowledge Structures
- On defining image schemas
- Cyc
- Reinforcement Learning for Industrial AI with Pieter Abbeel - #476
- Paper: Enhancing Learning with Primitive-Decomposed Cognitive Representations
- Paper: Crowdsourcing Image Schemas
