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From MIPS to exaflops in mere decades: Compute power is exploding, and it will transform AI
For the first time, we may have the computing power and the intelligence to tackle problems with AI that were once beyond human reach.
FLOPS measures floating-point performance that is crucial for scientific workloads and the heavy number-crunching behind modern AI, such as the matrix math and linear algebra used to train and run machine learning (ML) models. Achieving this level of performance in a single rack means less physical space per unit of work, fewer materials and potentially lower energy use per operation, although the absolute power demands of these systems remain immense. The company said in a blog post that the funding “enables us to push the frontiers of AI research even further, scale our compute infrastructure and deliver increasingly powerful tools for the 500 million people who use ChatGPT every week.”
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