AI services like Apple's Siri and others operate by sending your queries to faraway data centers, which send back responses. The reason they rely on cloud-based computing is that today's electronics don't come with enough computing power to run the processing-heavy algorithms needed for machine learning. The typical CPUs most smartphones use could never handle a system like Siri on the device. But Dr. Chris Eliasmith, a theoretical neuroscientist and co-CEO of Canadian AI startup Applied Brain Research, is confident that a new type of chip is about to change that. "Many have suggested Moore's law is ending and that means we won't get'more compute' cheaper using the same methods," Eliasmith says.
NengoDL is a software framework designed to combine the strengths of neuromorphic modelling and deep learning. NengoDL allows users to construct biologically detailed neural models, intermix those models with deep learning elements (such as convolutional networks), and then efficiently simulate those models in an easy-to-use, unified framework. In addition, NengoDL allows users to apply deep learning training methods to optimize the parameters of biological neural models. In this paper we present basic usage examples, benchmarking, and details on the key implementation elements of NengoDL. More details can be found at https://www.nengo.ai/nengo-dl .
A screen capture from a simulation movie of Spaun in action shows the input image on the right. The output is drawn on the surface below Spaun's arm. Neuron activity is approximately mapped to relevant cortical areas and shown in color (red is high activity, blue is low). Chris Eliasmith has spent years trying to figure out the ingredients and precise recipe for building a brain. He even has a book coming out in February--called "How to Build A Brain"--describing gray matter, dendritic connections and other brainy anatomy.
Though parts of the world have succeeded in suppressing the coronavirus and are now opening up, it will be some time before we can start traveling to conferences again. I was supposed to attend two meetings this spring and then the Telluride Neuromorphic Engineering Workshop this summer. I enjoy poring through the literature, but was looking forward to hearing from the researchers themselves. So I decided to console myself by putting together a list of (mostly) recent technical neuromorphic video talks available online and have shared these with the neuromorphic community (and now with you). I find conference presentations a much better way into new subject matter than papers: you get a context, explanation, and overview without being bogged down with technical details.