With IBM Corp.’s opening of Watson’s core machine learning component to businesses, a quick understanding of what that enables for savvy enterprises will be key to prompt capitalization.

One of the easiest ways to approach it is to think of the new private cloud option “more as branding, and Watson is a bigger solution set,” according to IBM’s Steven Astorino.

Astorino (pictured), vice president of development, private cloud platform and z Analytics at IBM Canada, spoke with Dave Vellante (@dvellante) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, in New York City at the IBM Machine Learning Launch Event 2017 NYC. The discussion covered several aspects of the new machine learning access, and how customers can best leverage it for their needs. (*Disclosure below.)

As Astorino noted, a big part of the benefit comes from how the new tech allows machine learning to be automated,” making it much easier for data scientists and businesses to work together. Asked whether it was simply a new presentation for the same Watson technology, Astorino stated, “Watson is our [public] cloud solution … We’re [now] building something on private cloud for private cloud customers.”

With open-source and open platform elements a prominent part of IBM’s design-first approach to the new services, along with integration of its own in-house research and other capabilities, Astorino highlighted freedom, productivity and trust as the three key pieces the company is using as the cornerstones on which to build.

Understanding application potential

“When you’re building a model, you want to have your choice of the tooling you use,” Astorino noted, addressing that and other ways in which IBM is aiming to provide as much flexibility as possible with this direct line between businesses and machine learning, including the automation of the Cognitive Assisting for Data Scientists assistant, which determines the best model and algorithm to use in each specific situation.

But while opening that link to machine learning is relatively simple, the bigger challenges come immediately after that step. “I think the hardest thing is [customers] want it, but they don’t know how to apply it,” Astorino commented. As a way to address that uncertainty, IBM is establishing a hub in Silicon Valley where customers can visit and get help figuring out how to use machine learning in their businesses.

“At the end of the day, we’re trying to provide similar product on both public cloud and private cloud. … We want to be able to target the other environments behind the firewall in the private cloud environment,” Astorino said.

And while clearing that obstacle will be a significant part of IBM’s focus for the near future, he was confident that the company would achieve it. “As users and customers get more comfortable with understanding how they’ll leverage this in their businesses … it really helps them be more competitive in their own space with the services they’re providing.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the IBM Machine Learning Launch Event 2017 NYC. (*Disclosure: TheCUBE is a media partner at the conference. Neither IBM nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo by SiliconANGLE