HAI Weekly Seminar with Agrim Gupta
Towards Understanding and Building Embodied Intelligence
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Towards Understanding and Building Embodied Intelligence
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.

AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.
How do AI agents influence knowledge work? This paper finds that agents shift worker effort from implementation to supervision, which especially benefits verifiable work and expert workers. I use data from the coding platform Cursor to study agents in software production.
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How do AI agents influence knowledge work? This paper finds that agents shift worker effort from implementation to supervision, which especially benefits verifiable work and expert workers. I use data from the coding platform Cursor to study agents in software production.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.

What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
In contrast to embodied intelligence, which is common in nature, the recent progress in AI has been disembodied. Animals display remarkable degrees of embodied intelligence by leveraging their evolved morphologies to learn complex tasks. In this talk, I will argue that intelligent behavior is a function of the brain, morphology, and the environment. However, the principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control, remain elusive, partially due to the substantial challenge of performing large-scale in silico experiments on evolution and learning. To address this, I will introduce a new framework called DERL which enables us to evolve agents with diverse morphologies to learn hard locomotion and manipulation tasks in complex environments, and reveals insights into relations between environmental physics, embodied intelligence, and the evolution of rapid learning.