One of those major costs is electricity, and Qualcomm has used its history designing chips for battery-powered devices such as smartphones to create a chip called the Cloud AI 100 that aims for parsimonious power consumption. But after those AI models are trained, they are put to wider use in what is called 'inference' by doing tasks like generating text responses to prompts and deciding whether an image contains a cat.Īnalysts believe that the market for data center inference chips will grow quickly as businesses put AI technologies into their products, but companies such as Alphabet Inc's (GOOGL.O) Google are already exploring how to keep the lid on the extra costs that doing so will add.

Nvidia dominates the market for training AI models with huge amounts of data. April 5 (Reuters) - (This April 5 story has been corrected to clarify that Neuchips did not beat Qualcomm and Nvidia in one category of testing as it didn't compete in the categories previously described, and Qualcomm's results and rankings have been rectified in paragraphs 6-8)Īrtificial intelligence chips from Qualcomm Inc (QCOM.O) beat Nvidia Corp (NVDA.O) in two out of three measures of power efficiency in a new set of test data published on Wednesday.

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