The ‘next big thing’ in data analytics? Rolling it out, says Diveplane CEO
RALEIGH – Forget trying to look into a magic ball to predict the “next big thing” in data analytics. To Diveplane’s CEO Michael Capps, it’s pretty clear.
“Actually, it’s rolling it out,” he said as part of a Q&A session, held shortly after his closing keynote for North Carolina Technology Association’s State of Technology virtual event on Friday.
Capps know data. The former CEO of Epic Games is the founder of the Raleigh-based Diveplane, an artificial intelligence startup that helps financial organizations move data without any privacy concerns.
“Right now, 50 percent of corporations aren’t using it all,” he said. “The ones that are, are barely using it; and everyone’s having trouble integrating.”
It’s a reality check for executives and business leaders who gathered online for the conference to explore how data is impacting our lives, personally and professionally.
For those not in the know, “big data” is the digital convergence of structured data found inside databases, and unstructured data flowing from new sources like social networks, mobile devices, sensors, RFID, smart meters and financial systems.
Today, organizations can capture and analyze any data, regardless of what type, to make more informed decisions.
But as Capps points out, the technology curve of AI is “insane.’
“I mean, it’s not doubling every year; it’s 20-xing every year, and nobody can to keep track of it.”
Interestingly, he says it’s the small companies that will win in a rapid rollout.
“That’s the transition you’ll see. It’ll be a couple of big ones that are hard to cut down; but the small banks, the small healthcare pairs, the small loyalty programs, whatever it is — those are the ones that will win quickly and take over because they can adapt.
Founded in 2018, Diveplane develops technology that helps businesses and government organizations understand AI with a trainable, interpretable and auditable.
Last October, also released a new tool called ALLUVION. Created specifically for the commercial real estate industry, its algorithms identify constantly changing trends and analyze variable volatility to accurately project market growth, instead of basing predictions solely off past observations.
That same month, it also released GEMINAI, which creates a verifiable synthetic “twin” dataset that maintains the same statistical properties of the original data, but doesn’t include any real-world confidential or personal information.
The end result: businesses, like financial institutions, can analyze and share relevant data while safely knowing that should this data be mishandled, lost, or stolen, it contains no real, sensitive information.
Original Article Source: WRAL TechWire