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Google went so far as to design its own chip, the TPU.
It's also the hardware behind these algorithms.Microsoft's speech rec system relies on large farms of GPU processors, chips that were originally designed for rendering graphics but have proven remarkably adept at running artificial intelligence models.Internet giants like Microsoft, Google, Facebook, and Baidu typically train their deep neural nets using GPUs. So Intel, the world's largest chip maker, is doing the same.It has the infrastructure needed to build chips at scale.It has the sales operation needed to push them into the market. If you do not receive response from us more than 3days, there may be a reasons that you were not able to receive reply e-mail from us.
If so, please check spam mail box would be sincerely appriciated.Then comes the execution stage, when people actually use the neural net to, say, recognize commands spoken into smartphones.Intel's Nervana chip is designed to help with both stages, says Nervana founder Navene Rao, now an Intel vice president and general manager.Today, GPUs are still the most effective way of training AI systems, while companies are exploring all sorts of hardware for execution.Baidu executes with help from GPUs, for instance, while Microsoft uses programmable chips called FPGAs.He was an investor in Nervana when it was a startup.