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In Your Mind
The tree - your neural network, your brain
The fruits - your memories
The birds - your outside world
and, the cocktail - your dreams!
No Photoshop! See Exif Data!
Photo of the Day - londonist.com
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
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A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering
Congratultions to @ucsandiego bioengineers and alumni, whose work on a new neuromorphic chip was published today in @nature_the_journal! You can learn more here: bit.ly/NeuRRAMchipNature
@ucsdalumni
#bioengineering #electricalengineering #AI #neuralnetworks #neuromorphiccomputing #semiconductors Pictures by David Baillot
A team led by Duygu Kuzum's lab has developed a neuroinspired hardware-software co-design approach that could make neural network training more energy-efficient and faster. Their work could one day make it possible to train neural networks on low-power devices such as smartphones, laptops and embedded devices.
Full story: jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=2692
Photo credit: David Baillot/UC San Diego Jacobs School of Engineering