Few of the AI hardware startups that have made it through the first round of reality (roughly 2016 until the present) have managed to navigate the choppy waters without shifting course, sometimes wildly. …
During the Intel AI Summit earlier this month where the company demonstrated its initial processors for artificial intelligence training and inference workloads, Naveen Rao, corporate vice president and general manager of the Artificial Intelligence Products Group at Intel, spoke about the rapid pace of evolution in the AI space that also includes machine learning and deep learning. …
Carey Kloss has been intimately involved with the rise of AI hardware over the last several years, most notably with his work building the first Nervana compute engine, which Intel captured and is rolling into two separate products: one chip for training, another for inference. …
Training deep neural networks is one of the more computationally intensive applications running in datacenters today. …
There is a rumor going around that a certain hyperscaler is going to be augmenting its GPU-based machine learning training and will be adopting Intel’s Nervana Neural Network Processor (NNP) for at least some of its workloads. …
In the United Kingdom, there is a topical BBC Radio 4 comedy panel show called I’m Sorry I Haven’t A Clue. …
Almost two years after the acquisition by Intel, the deep learning chip architecture from startup Nervana Systems will finally be moving from its codenamed “Lake Crest” status to an actual product. …
The frameworks are in place, the hardware infrastructure is robust, but what has been keeping machine learning performance at bay has far less to do with the system-level capabilities and more to do with intense model optimization. …
Like all hardware device makers eager to meet the newest market opportunity, Intel is placing multiple bets on the future of machine learning hardware. …
Over the last two years, there has been a push for novel architectures to feed the needs of machine learning and more specifically, deep neural networks. …
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