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In 2018, OpenAI reported that the amount of computing power used in large-scale AI training runs had been doubled every 3.4 months since 2012. Around the same time, the volume of data generated also increased dramatically. ....
Great teams incorporate a variety of skill sets. For example, a football team consisting of 11 quarterbacks would get crushed in a game against talented linemen, running backs and receivers. It’s no different when building a team for an enterprise AI project; you can’t just throw a bunch of data scientists into a room and expect them to come up with a revenue-generating or efficiency-improving project without support from other members of the enterprise. ....
SANTA CLARA, Calif., March 22, 2022 (GLOBE NEWSWIRE) GTC NVIDIA today announced the fourth-generation NVIDIA® DGX™ system, the world’s first AI platform to be built with new NVIDIA H100 Tensor Core GPUs. DGX H100 systems deliver the scale demanded to meet the massive compute requirements of large language models, recommender systems, healthcare research and climate science. Packing eight NVIDIA… ....