If there is one thing that can be said about modern distributed computing that has held true for three decades now, it is that the closer you get to the core of the datacenter, the beefier the compute tends to be. …
Two important changes to the datacenter are happening in the same year—one on the hardware side, another in software. …
When it comes to machine learning training, people tend to focus on the compute. …
Neural networks live on data and rely on computational firepower to help them take in that data, train on it and learn from it. …
The combination of the excitement for new video games, the machine learning software revolution, the buildout of very large supercomputers based on hybrid CPU-GPU architectures, and the mining of cryptocurrencies like Bitcoin and Ethereum have combined into a quadruple whammy that is driving Nvidia to new heights for revenues, profits, and market capitalization. …
There has been much recent talk about the near future of code writing itself with the help of trained neural networks but outside of some limited use cases, that reality is still quite some time away—at least for ordinary development efforts. …
There is increasing pressure in such fields as manufacturing, energy and transportation to adopt AI and machine learning to help improve efficiencies in operations, optimize workflows, enhance business decisions through analytics and reduce costs in logistics. …
Researcher Olexandr Isayev wasn’t just impressed to see an AI framework best the top player of a game so complex it was considered impossible for an algorithm to track. …
It is a renaissance for companies that sell GPU-dense systems and low-power clusters that are right for handling AI inference workloads, especially as they look to the healthcare market–one that for a while was moving toward increasing compute on medical devices. …
There has been a great deal of interest in deep learning chip startup, Graphcore, since we first got the limited technical details of the company’s first-generation chip last year, which was followed by revelations about how their custom software stack can run a range of convolutional, recurrent, generative adversarial neural network jobs. …
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