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A typical AI project has three main stages. Development, where you prepare your data and test your concepts; Training which scale your chosen model; and Inferencing, where you deploy your final model in the real world. The complexities of this three stage process can be daunting. We make it simple, by bringing together nine complementary areas into the Scan AI Ecosystem, to guide you through your AI journey, supported by our expert data scientists and system engineers at every stage.
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Scan worked with King’s College London and the AI Centre for Value Based Healthcare, to rollout GPU-accelerated clusters to numerous NHS Trusts, in order to accelerate real-time medical image diagnosis and improve patient outcomes.
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Can machine learning onboard space observatories and on Earth help build a near real-time warning system for potentially dangerous solar weather events?
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