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The neural optic: a testament to the fusion of organic and artificial intelligence. Duncan.co/deep-tech-mafia-upgraded-vision
I have implemented the Fahlman Cascade neural network algorithm in the Python programming language. This approximately real-time video displays sample outputs from a series of gradually-changing networks.
I wrote this program for two reasons: 1) to test performance, and 2) to get a feel for the complexity of functions that can be generated by a Fahlman cascade network. Given that all of my code is in Python, I am pretty pleased with the speed. And as you can see from the graphs, quite complex behavior is obtained from a fairly small network.
Boštjan Čadež
Mr Processor, do you understand life?
Cirkulacija 2
Tobačna 5, Ljubljana
24 September 2019
Production: Aksioma - Institute for Contemporary Art, Ljubljana, 2019
Photo: Janez Janša / Aksioma
MORE: aksioma.org/mr.processor
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.
Images generated by deep generator network (DGN, Nguyen, et al) as specified here: www.evolvingai.org/synthesizing
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