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Vast Data: Big shifts promised for an AI future

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Vast Data will triple engineering investment and promises "very ambitious products" as the company orients towards a future in which machine learning and artificial intelligence (AI) will dominate IT and investment around it. That's according to chief marketing officer Jeff Denworth, who spoke to Computer Weekly this week. He set out a vision of Vast as a rapidly rising star with a product that fits a future of very large volumes of data – generated from machine and human activity – from which organisations will want to quickly gain insight. Vast Data sells what it calls Universal Storage, based on bulk, relatively cheap and rapidly accessible QLC flash with Optane (or near-equivalent) fast cache to smooth input/output. It is file storage, mostly suited to unstructured or semi-structured data, and Vast envisages it as large pools of datacentre storage, an alternative to the cloud. Despite the tie to specific hardware, Vast sells only software – it's based on a containerised control plane – and with customers able to monitor and control fleets of Vast deployments anywhere across the globe via Uplink Cloud Management.


A.I. Could Accurately Predict Those at Risk of Suicide in the Future

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Suicide results in approximately 44,965 American deaths each year and is the tenth leading cause of death in the United States, according to the American Foundation for Suicide Prevention. Deaths from cardiovascular disease and other ailments greatly outnumber those caused by suicide, but suicide rates have either remained steady or even increased in certain parts of the U.S., while heart condition casualties have been decreasing. For science journalist Lydia Denworth, this is a clear sign that current efforts to prevent suicide aren't working. She believes doctors simply aren't able to identify potential risk factors and act on them for all of their patients. Denworth tells Cheddar's Morning Bell that artificial intelligence developed by social scientists could predict who is most at risk so doctors can act more effectively instead of spending time analyzing medical records.