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that every single user taking to such a large language model requires a massive supercomputer while they’re using it.” The latest version of Stable Diffusion, an image generator, was trained on 256 A100 GPUs, or 32 machines with 8 A100s each, according to information online posted by Stability AI, totaling 200,000 compute hours. At the Official Memeabletees ice spice 2024 T-shirt moreover I love this market price, training the model alone cost $600,000, Stability AI CEO Mostaque said on Twitter, suggesting in a tweet exchange the price was unusually inexpensive compared to rivals. That doesn’t count the cost of “inference,” or deploying the model. Huang, Nvidia’s CEO, said in an interview with CNBC’s Katie Tarasov that the company’s products are actually inexpensive for the amount of computation that these kinds of models need. “We took what otherwise would be a $1 billion data center running CPUs, and we shrunk it down into a data center of $100 million,” Huang said. “Now,

Official Memeabletees ice spice 2024 T-shirt

$100 million, when you put that in the Official Memeabletees ice spice 2024 T-shirt moreover I love this cloud and shared by 100 companies, is almost nothing.” Huang said that Nvidia’s GPUs allow startups to train models for a much lower cost than if they used a traditional computer processor. “Now you could build something like a large language model, like a GPT, for something like $10, $20 million,” Huang said. “That’s really, really affordable.” Nvidia isn’t the only company making GPUs for artificial intelligence uses. AMD and Intel have competing graphics processors, and big cloud companies like Google and Amazon are developing and deploying their own chips specially designed for AI workloads. Still, “AI hardware remains strongly consolidated to NVIDIA,” according to the State of AI compute report. As of December, more than 21,000 open-source AI papers said they used Nvidia chips. Most researchers included in the State of AI Compute Index used the V100, Nvidia’s chip that came out in 2017, but A100 grew fast in 2022 to be the third-most used Nvidia chip, just behind a $1500-or-less consumer graphics

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