csquare Machine Learning (ML) Infrastructure Purpose-Built for Sustainability and Performance Launches in EU

csquare emerges from BETA to deliver the most powerful, efficient, and greenest Machine Learning (ML) platform as a service. The company will celebrate with a special online launch event at the Porsche Winter Testing Center in Arvidsjaur in partnership with Gassecry datacenters on April 28, 2021.

The Artificial Intelligence (AI) services market is projected to rise from $17 billion this year to $22 billion in 2022 — reaching $30 billion in 2024. And Gartner Research previously predicted that the return on that investment will be exceptional — delivering $2.9 trillion in business value and enhancing performance with 6.2 billion hours of additional worker productivity this year alone.

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This rapidly accelerating demand presents unique challenges. For example, generic datacenters and public clouds are not designed to process ML experiments efficiently. Further, processing AI/ML calculations requires significantly more energy and generate more waste heat than conventional business compute.

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The csquare MLOps platform has been scientifically designed and purpose-built to specifically meet these challenges head-on:

• Purpose-built high-performance (HPC) clusters tuned for fast, accurate, and efficient ML experiments.
• Dedicated and intuitive user interface — allowing data scientists to easily load their data, run experiments, and save templates for future use.
• Powered by 100% renewable energy, csquare ZeroEmission clusters achieve 100% heat reuse with Zero% waste water.
• Immersion-cooled infrastructure with heat re-capture that allows processors to run safely at full speed for faster calculations.
• Headquartered in Switzerland with data processing in Europe and compliant with all data sovereignty regulations and best practices.

“The csquare MLOps platform is exactly what the AI community needs today,” said Diarmuid Daltún, CEO of csquare. “The csquare platform beats the competition on performance, efficiency, and environmental footprint.”

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