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AI accelerators and open software transform the computing landscape

Three years ago, we had maybe six or less AI accelerators, today there’s over two dozen, and more are coming. One of the first commercially available AI training accelerators was the GPU, and the undisputed leader of that segment was Nvidia. Nvidia was already preeminent in machine learning (ML) and deep learning (DL) applications and adding neural net acceleration was ...

Jon Peddie

Three years ago, we had maybe six or less AI accelerators, today there’s over two dozen, and more are coming. One of the first commercially available AI training accelerators was the GPU, and the undisputed leader of that segment was Nvidia. Nvidia was already preeminent in machine learning (ML) and deep learning (DL) applications and adding neural net acceleration was a logical and rather straight-forward step for the company. Nvidia  enabled a treasure-trove of applications with their GPUs based on the company’s proprietary development language CUDA. The company developed CUDA in 2006 and empowered hundreds of universities to give courses
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