IBM makes Watson Portable across all clouds

10 | Flipkart (Image: Reuters)

IBM announced that it has made Watson portable across any cloud to empower businesses to prevent vendor lock-in and start deploying AI wherever their data resides.

"Businesses have largely been limited to experimenting with AI in sales due to the limitations caused by cloud provider lock-in of their data," said Rob Thomas, General Manager, IBM Data and AI. "With most large organizations storing data across hybrid cloud environments, they need the freedom and choice to apply AI to their data wherever it is stored. By breaking open that siloed infrastructure we can help businesses accelerate their transformation through AI."

Watson, IBM's AI, is designed to help organizations put AI to work to improve the performance of the business. The company also introduced a new set of Watson microservices, based on the open-source Kubernetes technology, which can be run on IBM Cloud, and other public, hybrid or multi-cloud environments.

The announcements provide businesses with a simpler, faster way to build, deploy and run AI models and applications across any cloud. With these tools in place, organizations can:

• Run IBM Watson services, including Watson Assistant and Watson OpenScale, on any cloud. Through their integration with IBM Cloud Private for Data (ICP for Data), Watson and Watson OpenScale can now be run any environment – on premises, or on any private, public or hybrid-multi-cloud – enabling businesses to apply AI to data wherever it is hosted. Businesses will be able to infuse AI into their apps, regardless of where they reside.
• Deploy AI software that automates business processes for improved efficiencies and performance. New AI digital automation software is designed to enable clients to discover patterns in their business processes and then create AI-embedded programs to automate certain workflows.

Though the use of AI continues to gain attention in business, many organizations are still challenged to move projects forward. According to an MIT Sloan report, 81 percent1 of enterprises do not understand what data is required for AI, or how to access it. And a recent Gartner study found that, "data and analytics leaders continue to struggle with the complexity, time to integration and cost implications of their data integration projects, thereby inflating their schedules and delivery costs with multiple cycles of revised project scope."