IBM Makes Watson Available Across Amazon, Microsoft, and Google Clouds
For years, IBM has offered corporate customers its Watson data crunching technology—but only if they used it on IBM’s cloud computing service. Now, in an effort to expand Watson’s reach, IBM is also making it available on competing cloud services.
IBM said Tuesday that it would allow businesses to use some of IBM’s Watson-related software with underlying data that is stored in rival cloud data centers like Microsoft’s Azure and Amazon Web Services. Customers will also be able to use Watson with data stored in their own data centers.
“It is enabling a level of openness that hasn’t been available to date,” said Rob Thomas, IBM general manager of data and AI.
The move marks a departure for IBM, which, until now, hasn’t seemed anything but open with its cloud computing service and Watson technologies. In 2016, for example, then-IBM CFO and current IBM senior vice president of global markets Martin Schroeter told analysts during an earnings call, “Watson runs on our cloud, and our technology will run on IBM’s cloud.”
But IBM is now shaking up its strategy in an effort to broaden Watson’s appeal. The change of heart comes as IBM’s public cloud languishes in third place, at best, in terms of market share behind AWS and Microsoft Azure.
Dan Kirsch, a managing director at Hurwitz & Associates, called IBM’s new service “really significant” because businesses are increasingly seeking technology that’s not dependent on a single vendor.
“You look out of touch with your customers if you say you can only have our software and our capabilities if you adopt everything only from us,” Kirsch said.
Nick Patience, a founder and research vice president for 451 Research, said the move is “an acknowledgment by IBM that it’s a hybrid cloud world,” referring to firms wanting to use more than one cloud computing vendor as well as keeping some software running in their internal data centers.
Cloud computing companies like Amazon and Microsoft are pushing artificial intelligence because using technologies like deep learning typically require processing huge amounts of data through their cloud services, Patience explained. IBM deciding to make Watson available on competing cloud services could be a sign that “IBM is acknowledging that AWS, Microsoft, and Google are leading the pack in machine learning,” he said.
Kirsch explained that being more open could help IBM win customers that are concerned about being locked into one company’s cloud service for AI projects. In this way, they’ll be relatively free to pick and chose.
IBM’s new service, Cloud Private for Data (ICP for Data), is built on the popular open source IT software Kubernetes, which was developed by Google as a way to manage data center infrastructure. The free software has become popular with developers because they can use the technology to build complex apps that are powered by multiple databases and services that theoretically don’t have to be tethered to a single cloud provider.
Thomas said IBM hasn’t set a price for the new service and it will likely be tiered based on the customers’ needs. Additionally, while the service is currently compatible with only North American cloud providers like AWS, Asian cloud vendors like China tech giant Alibaba could be added in the future, Thomas said.
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Still, Thomas argues that the best way to run Watson is through IBM’s own cloud computing service. Customers using it can choose from multiple hardware and computer chip configurations that squeeze the most power out of Watson.
“We are confident in the IBM cloud that if clients try our products anywhere, they will eventually be drawn to IBM cloud and the uniqueness it provides,” said Thomas.
Although companies are concerned about being locked into a specific company’s cloud infrastructure when it comes to certain software and IT products, Patience said they are currently in the early stages of using AI and are still willing to upload their corporate data to cloud services like AWS and rely on them for machine learning software. Being locked into a particular vendor when it comes to machine learning projects isn’t yet much of a concern, but IBM is betting that will change.
“We don’t hear a load of companies banging on the door saying, ‘This is outrageous, we demand more portability,'” Patience said.
He continued: “You could say IBM is trying to take back the initiative in machine learning here. The Watson brand has lost a little bit of luster over the years as others has come along. They are trying to take it back.”