Every few years or so, a development in computing results in a sea change and a need for specialized workers to take advantage of the new technology. Whether that’s COBOL in the 60s and 70s, HTML in ...

This is because GPUs, the heart of Nvidia's competitive advantage, aren't designed for AI. This basically means that the field is open for specialist silicon purposely designed for AI, although that ...

Why it matters: Nvidia introduced CUDA in 2006 as a proprietary API and software layer that eventually became the key to unlocking the immense parallel computing power of GPUs. CUDA plays a major role ...

Hardware requirements vary for machine learning and other compute-intensive workloads. Get to know these GPU specs and Nvidia GPU models. Chip manufacturers are producing a steady stream of new GPUs.

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