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X-WR-CALNAME:Jump-starting Embodied Intelligence
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UID:2024-04-08-unnat-jain@cml.ics.uci.edu
DTSTAMP:20240408T000000Z
SEQUENCE:57690
DTSTART;TZID=America/Los_Angeles:20240408T110000
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SUMMARY:[CML Seminar] Unnat Jain: Jump-starting Embodied Intelligence
LOCATION:Donald Bren Hall 4011
DESCRIPTION:Unnat Jain\, Postdoctoral Researcher\, Carnegie Mellon Universi
ty\, Fundamental AI Research (FAIR) at Meta\n\nTitle: Jump-starting Embodi
ed Intelligence\n\nAbstract: AI has revolutionized the way we interact onl
ine. Despite this\, it hasn't quite made the leap when it comes to tasks l
ike cooking dinner or cleaning our desks. Why has AI excelled in automatin
g our digital interactions but not in assisting us with physical tasks? In
my talk\, I will explore the challenges of applying AI to embodied tasks
— those requiring physical interaction with the environment. To address
these challenges\, I turn to the efficient pathways humans use to achieve
embodied intelligence and propose three strategies to jump-start the learn
ing process for embodied AI agents: (1) combining learning from both teach
ers and own experience\, (2) leveraging external information or hints to s
implify learning\, such as using maps to learn about physical spaces\, and
(3) learning intelligent behaviors by simply observing others.\n\nhttps:/
/cml.ics.uci.edu/seminars/2024-04-08-unnat-jain
X-ALT-DESC;FMTTYPE=text/html:Unnat Jain\, Postdoctoral R
esearcher\, Carnegie Mellon University\, Fundamental AI Research (FAIR) at
Meta
Title: Jump-starting Embodied Intelligence
A
bstract: AI has revolutionized the way we interact online. Despite thi
s\, it hasn't quite made the leap when it comes to tasks like cooking dinn
er or cleaning our desks. Why has AI excelled in automating our digital in
teractions but not in assisting us with physical tasks? In my talk\, I wil
l explore the challenges of applying AI to embodied tasks — those requir
ing physical interaction with the environment. To address these challenges
\, I turn to the efficient pathways humans use to achieve embodied intelli
gence and propose three strategies to jump-start the learning process for
embodied AI agents: (1) combining learning from both teachers and own expe
rience\, (2) leveraging external information or hints to simplify learning
\, such as using maps to learn about physical spaces\, and (3) learning in
telligent behaviors by simply observing others.
https://cml.ics.uci.edu/semi
nars/2024-04-08-unnat-jain
URL:https://cml.ics.uci.edu/seminars/2024-04-08-unnat-jain
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