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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
In this image, Duncan Rawlinson brilliantly blurs the lines between photography and modern AI-powered image generation tools to produce a visually captivating portrayal of OpenAI's ChatGPT.
Rawlinson starts with his signature photographic method, leveraging his prowess in capturing the nuances of his subjects. His choice of the Phase One XF IQ4 150MP Camera ensures an unmatched level of detail, a testament to his commitment to quality.
From this photographic foundation, Rawlinson skillfully transitions to the digital art realm. The AI's "head" and its complex neural network are not captured through the lens, but through the precise and calculated application of AI image generation tools. These tools allow him to visualize an abstract concept like a neural network, converting it into tangible lines and nodes, interweaving through the AI's head.
The creation process is thus a symbiotic dance between high-resolution photography and AI-driven digital art. Rawlinson marries the tactile realism of photography with the boundless possibilities of AI-powered graphic design. The result is a unique hybrid image, demonstrating how AI can be used as an artistic tool to bring abstract concepts to life.
By creating the image in his signature style, Rawlinson adds a layer of artistic interpretation to the AI's representation. He invites the viewer to appreciate not only the AI's intricate complexity but also the novel way in which traditional photography can be elevated by modern AI tools. This image stands as a testament to the intersection of art, technology, and human creativity.
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
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
Took a while to fix a sort of 'Alzheimer's degradation in this net: at some nods burnt bulbs cause the whole 'dendrites go bust' :)
But you have to do a bit of elemental 'brutal search' in order to find the bad ones. That's time consuming.
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
In this image, Duncan Rawlinson brilliantly blurs the lines between photography and modern AI-powered image generation tools to produce a visually captivating portrayal of OpenAI's ChatGPT.
Rawlinson starts with his signature photographic method, leveraging his prowess in capturing the nuances of his subjects. His choice of the Phase One XF IQ4 150MP Camera ensures an unmatched level of detail, a testament to his commitment to quality.
From this photographic foundation, Rawlinson skillfully transitions to the digital art realm. The AI's "head" and its complex neural network are not captured through the lens, but through the precise and calculated application of AI image generation tools. These tools allow him to visualize an abstract concept like a neural network, converting it into tangible lines and nodes, interweaving through the AI's head.
The creation process is thus a symbiotic dance between high-resolution photography and AI-driven digital art. Rawlinson marries the tactile realism of photography with the boundless possibilities of AI-powered graphic design. The result is a unique hybrid image, demonstrating how AI can be used as an artistic tool to bring abstract concepts to life.
By creating the image in his signature style, Rawlinson adds a layer of artistic interpretation to the AI's representation. He invites the viewer to appreciate not only the AI's intricate complexity but also the novel way in which traditional photography can be elevated by modern AI tools. This image stands as a testament to the intersection of art, technology, and human creativity.