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BEGIN:VEVENT
DTSTAMP:20260618T085154Z
DTSTART:20260707T120000Z
DTEND:20260707T130000Z
SUMMARY:Gateway to Translation Webinar Series -  Wearables Are Getting Sm
 arter: Deploying AI on Microcontrollers
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}m2bk-mqj9c7
 vy-oyipby
DESCRIPTION:Translation Manchester are excited to announce the return of 
 our popular monthly webinar series ‘Gateway to Translation (G2T)’! \n\nT
 he “Gateway to Translation” (G2T) webinar series is a joint initiative b
 etween the University of Cambridge (Cambridge Academy of Therapeutic Sci
 ences\, CATS) and The University of Manchester (Translation Manchester).
  The aim of these monthly webinars is to stimulate the translation of re
 search into the clinics by educating academics about trends\, technologi
 es and research in the commercial sphere and by facilitating collaborati
 ons between academia and the medtech\, biotech and pharma industry secto
 rs.  \n\nThis month's talk will explore how AI can be deployed on resour
 ce?constrained microcontrollers\, enabling intelligent functions on smal
 l\, low?power devices. Using audio as a running example\, the session wi
 ll unpack the technical challenges\, trade?offs\, and practical solution
 s involved in bringing machine learning models onto embedded systems in 
 real?world applications. \n\nSpeaker: Luke Taylor\, Founder of DeepGate.
 ai\nChair: Dr Garreth Prendergast\, Lecturer in Audiology/Hearing Scienc
 es\, University of Manchester\n\nAbout this webinar\nArtificial intellig
 ence is increasingly moving away from the cloud and onto tiny\, low?powe
 r devices. This webinar will explore how AI can be deployed on resource?
 constrained microcontrollers\, enabling intelligent functions on small\,
  low?power devices. Using audio as a running example\, the session will 
 unpack the technical challenges\, trade?offs\, and practical solutions i
 nvolved in bringing machine learning models onto embedded systems in rea
 l?world applications.\n\nSpeaker\nLuke Taylor is the founder of DeepGate
 \, a company building ultra-efficient machine learning tooling for micro
 controllers and embedded systems. He completed his DPhil at the Universi
 ty of Oxford\, where he conducted computational neuroscience research in
  the Auditory Neuroscience Group with a focus on spiking neural network 
 models. Inspired by the energy efficiency of the brain\, his work today 
 focuses on making machine learning smaller\, faster\, and more energy-ef
 ficient for real-world edge devices.\n\nDeepGate builds efficient toolin
 g for developing\, optimising\, and deploying machine learning models on
  microcontrollers. The company focuses on reducing latency\, memory usag
 e\, and power consumption for edge AI applications\, while simplifying d
 evelopment workflows for developers. Alongside its tooling platform\, De
 epGate develops licensable embedded AI models\, including object detecti
 on\, wake-word\, and audio enhancement systems.\n\nWho should attend?\nT
 his webinar is aimed at:\n• Academic researchers (PIs\, postdocs\, and P
 hD students)\n• Engineers and data scientists working on AI\, wearables\
 , or embedded systems\n• Researchers interested in translational and ind
 ustry?facing AI technologies\n• Anyone curious about deploying AI beyond
  the cloud and onto real?world devices
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:https://teams.microsoft.com/meet/31966727195510?p=esarehPbpKB1y8
 e2nt
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