Big data was all the rage a few years ago, but data in and of itself is actually not that helpful without applied analytics. Because of this, companies today need to focus on the modern technologies that have emerged in recent months, including deep learning and other artificial intelligence methods trained to extract value from vast amounts of data.

“Big data had its glory days, but now they’re coming to the end of that crescendo, because people realized that what they got was sort of [an] aggregate of what they couldn’t make too much sense of,” said Liran Zvibel, co-founder and chief executive officer of WekaIO Inc.

Zvibel sat down with Stu Miniman (@stu) for a CUBE Conversation at theCUBE’s studio in Palo Alto, California. They discussed the ways big data will connect with new and improved AI technologies.

The connection of big data and machine learning

Now that companies recognize data as an asset, they’ve begun to seek out efficient methods to contextualize it all. It turns out, human thought processes could be the perfect inspiration. “People really understand that for you to make better use of your data, you need to employ ways similarly to how the brain works,” Zvibel said.

For Zvibel, it’s all about feedback and how data can learn from itself. “Customers end up collecting vast amounts of data, and then they train their models on this kind of data, and then they’re pushing these intelligent models to these edges,” Zvibel said.

These are considered closed-looped systems, according to Zvibel. “We’re now at the infancy of a lot of these loops, but … I think probably two to five years will take us through a very fascinating evolution where systems all around us will become way, way more intelligent,” he said.

WekaIO fits in here by creating the fastest file system tuned for AI and machine learning and training, according to Zvibel. The company also tiers to effective object storage that runs into the exabytes. “[Clients] finish training sessions 10 times faster than how they would use traditional … solutions just based on the different way we handle data,” he said.

Here’s the entire video interview with Gibson, part of a series of SiliconANGLE’s and theCUBE’s CUBE Conversations.

Photo: SiliconANGLE