EPISODE · Oct 11, 2022 · 46 MIN
Pete Warden - Bringing Deep Learning to Microcontrollers with TinyML
from Conversations on Applied AI · host Justin Grammens
The conversation this week is with Pete Warden. Pete's mission is simple: Organizing the physical world's information to make it universally accessible and useful. He was the founder and CTO at Jetpac where he built a technical team and created a unique data product that analyzed the pixel data, over 140 million photos from Instagram and turn them into in depth guides for more than 5000 cities around the world. Jetpac was acquired by Google in 2014. From there, he was a founding member and technical lead of the TensorFlow mobile team responsible for deep learning on mobile and embedded devices. Today, he is the CEO at Useful Sensors. He is also the co-author of the highly successful book entitled TinyML published by O'Reilly. Pete holds a Bachelors of Science from University of Manchester and a Doctor of Philosophy and a PhD in computer science from Stanford University.If you are interested in learning about how AI is being applied across multiple industries, be sure to join us at a future AppliedAI Monthly meetup and help support us so we can make future Emerging Technologies North non-profit events!Emerging Technologies NorthAppliedAI MeetupResources and Topics Mentioned in this EpisodePete Warden on TwitterPeteWarden.comJetpacTensorFlowTinyMLQuantizationWake WordsEvgeni GousevArduinoEnjoy!Your host,Justin Grammens
What this episode covers
The conversation this week is with Pete Warden. Pete's mission is simple: Organizing the physical world's information to make it universally accessible and useful. He was the founder and CTO at Jetpac where he built a technical team and created a unique data product that analyzed the pixel data, over 140 million photos from Instagram and turn them into in depth guides for more than 5000 cities around the world. Jetpac was acquired by Google in 2014. From there, he was a founding member and te...
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Pete Warden - Bringing Deep Learning to Microcontrollers with TinyML
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