The merged computing power can give rise to faster and more accurate machine learning applications.
, thousands of years, to solve. The former will be able to solve in minutes or hours. These problems include developing new products and materials, for example, in the pharmaceutical, chemical, and battery industries.The connection relies on the secure HTTPS protocol between the endpoints, said Kotovirta. "Users develop a hybrid algorithm on the LUMI side and submit the job to the LUMI queuing system for execution.
After which, the result is returned to the LUMI side of the program that made the call. "The program might then combine the result with whatever classical computation it may have performed. Then it might start the next iteration, or it might display the results to the user," said Kotovirta.machine learning applications to generate novel molecular structures, accelerating the process of new material design.
Advantages can be expected in areas that demand high accuracy and quality of computational predictions, such as short-term weather prediction. It is imperative to predict thunderstorms, hurricane paths, and tsunami propagation accurately. "This is connected to real-time analysis of Earth observation data from satellites. In the long term, high-quality image processing could, for example, detect a budding forest fire before it spreads uncontrollably. In the financial sector, higher accuracy in algorithmic trading naturally comes with an instant reward," said the release.
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