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SUMMARY:What is Next for the Efficient Machine Learning Revolution?  - Nic
 holas Lane
DTSTART:20201117T131500Z
DTEND:20201117T141500Z
UID:TALK152020@talks.cam.ac.uk
CONTACT:Mateja Jamnik
DESCRIPTION:"Join us on Zoom":https://zoom.us/j/99166955895?pwd=SzI0M3pMVE
 kvNmw3Q0dqNDVRalZvdz09\n\nMobile and embedded devices increasingly rely on
  locally executing deep neural networks to understand the world -- a forme
 rly impossible feat that would have overwhelmed their system resources jus
 t a few years ago. The age of on-device artificial intelligence is now upo
 n us\; but incredibly\, these dramatic changes are just the beginning. Loo
 king ahead\, machine learning on IoT devices will extend beyond simply cla
 ssifying categories and perceptual tasks\, to performing roles that alter 
 how every part of the systems stack of smart device function. This next ev
 olution in constrained-resource computing will finally produce devices tha
 t meet our expectations in how they can learn\, reason and react to the re
 al-world. In this talk\, I will briefly discuss the initial breakthroughs 
 that allowed us to reach this point\, and outline a number of looming open
  problems we must overcome to bring about this next phase in the deep tran
 sformation of mobile and embedded computing.\n
LOCATION:Zoom
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