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Output of a simple connectionist neural network model as the synaptic weights are varied with time and position.
This is a frame from a video. You can watch it on Vimeo.
Well, I finally got something approximating a working neural network. It's based on Geoffrey Hinton's presentation on Restricted Boltzmann Machines (look it up on YouTube, it's very good if you're interested in machine learning). Trouble is, the stupid thing refuses to actually WORK. Oh well, at least it looks nice.
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
Each time Umberta lost a book, she lost a part of her brain—that book and that part of her brain were one and the same thing. If asked a question regarding some fact in the lost book, she would reply, "I don't remember."
Then there was the day she lost her connection to the internet: she forgot everything.
Blueprint of the future: a digital eye that architects a new way of seeing. Duncan.co/deep-tech-mafia-upgraded-vision