Alphabet Inc's Google on Tuesday released new details about the supercomputers it uses to train its artificial intelligence models, saying the systems are both faster and more power-efficient than comparable systems from Nvidia Corp .
Google has designed its own custom chip called the Tensor Processing Unit, or TPU. It uses those chips for more than 90% of the company's work on artificial intelligence training, the process of feeding data through models to make them useful at tasks like responding to queries with human-like text or generating images.
Improving these connections has become a key point of competition among companies that build AI supercomputers because so-called large language models that power technologies like Google's Bard or OpenAI's ChatGPT have exploded in size, meaning they are far too large to store on a single chip. Google said its supercomputers make it easy to reconfigure connections between chips on the fly, helping avoid problems and tweak for performance gains.
While Google is only now releasing details about its supercomputer, it has been online inside the company since 2020 in a data center in Mayes County, Oklahoma. Google said that startup Midjourney used the system to train its model, which generates fresh images after being fed a few words of text.
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