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To support its plans, the company, which is raising a new funding round, aims to spend $10 billion over the next three years building one of Europe’s largest AI supercomputers in Italy, in partnership with NVIDIA and G42.
Its model is designed for banks, pharmaceutical firms, governments, and defense companies that want to keep control of their own data and models. It is being released through Microsoft’s Foundry platform.
“We saw a white space not just enabling regulated industries to adopt AI, but to actually own and be an AI company in their market,” CEO Uljan Sharka said at Semafor World Economy in Washington.
For such industries ownership matters because, once a model has been trained on proprietary data it is difficult to separate that information from the system itself. It is like “putting sugar in a cake and once you bake it — which is the training process of the model — you cannot get it back,” Sharka said.
That concern is particularly important in sectors that restrict the sharing of sensitive data with third-party AI providers. These more focused models, trained on industry-specific information, can also outperform larger general-purpose systems, he added.
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