Forbes December 14, 2024
AI is smart. But shouldn’t AI designed to serve retail customers with “loyal sushi customer” special offers be engineered to run at one level, with AI tasked with serving not just mission-critcal but also life-critical scientific AI use cases be even smarter? If the answer is yes (which it almost certainly is), then we will need to engineer that science-tasked AI with an unfathomably large data access channel that is as diverse as it is controlled.
The news follows on a string of recently signed partnerships between TetraScience and Google Cloud, Databricks and Nvidia, each of which support the startup’s ambitions to transform siloed, proprietary and unstructured scientific data so it can be used by engineers and scientists for AI...
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