View allAll Photos Tagged NeuralNetworks,
A poster I made to promote the graduate science program at the University of Minnesota, Duluth.
My idea was based around neural networks. Most of the neural network diagrams I saw were an arrangement of circles connected together.
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
Images generated by deep generator network (DGN, Nguyen, et al) as specified here: www.evolvingai.org/synthesizing
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
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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