From ExtremeTech: There’s been a huge surge of interest in topics like AI, machine learning, and deep learning over the last few years. Thus far, we’ve seen much of the market flow towards either GPUs (almost entirely Nvidia, though AMD might be tipping a toe into those waters), or to specialized architectures designed by specific companies. Google has TensorFlow, Fujitsu is working on its own platform, Microsoft uses FPGAs to accelerate web searches, and multiple companies are designing self-driving car hardware around various commercial solutions. Intel, in contrast, has been a smaller player. While it owns Movidius and that company’s Myriad processors, it hasn’t commanded the same mind-share as some of its competitors.
That may change in the future, if Intel’s latest AI bet takes off. The company has announced a new neuromorphic chip, codenamed Loihi, designed for AI and deep learning workloads. Intel’s Dr. Michael Mayberry claims that Loihi does not need to be trained in the traditional way and that it takes a new approach to this type of computing by using asynchronous spiking. Unlike a transistor, neurons do not constantly flip back and forth between a 0 and a 1. They trigger when signal thresholds are reached, and continue to fire so long as the number of spikes exceeds a given threshold. The strength of a muscle flex, for example, is based on the average number of spikes the muscle receives over a given unit of time.
Intel claims that Loihi is up to a million times faster than other “typical” spiking neural nets when solving MNIST digit recognition problems, though it doesn’t say what those typical nets consist of, or how they are constructed. It also claims that Loihi is much more efficient when used for convolutional neural networks or deep learning tasks.
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