IBM’s newest libraries expand its embeddable AI portfolio
IBM is unveiling its latest expansion to its embeddable AI software portfolio with three new software libraries, empowering AI-powered solution development and end-user experience with ease. IBM ecosystem partners, Independent Software Vendors (ISVs), and developers can achieve cost-effective AI adoption without struggling over skill gaps, extended development times, and costs, across hybrid, multi-cloud environments, according to the company.
Building AI models from scratch is time consuming, resource heavy, and requires elevated skill sets. IBM’s expanded portfolio, whose AI libraries are the same that fuel IBM Watson products, aims to lower the barrier for AI adoption for increased developer accessibility. Developers have long struggled with the time, skills, and resources necessary to build AI and make it operational; IBM’s portfolio aims to provide the building blocks to make that goal not only possible, but simple and resource mindful.
“Enterprises must commit to a significant investment in expertise, resources, and time required to build, deploy, and manage AI-powered solutions,” said Kate Woolley, general manager at IBM Ecosystem. “By bringing to market the same portfolio of embeddable AI technology that powers our industry-leading IBM Watson products, we are helping Ecosystem partners more efficiently deliver AI experiences that can drive business value for their clients.”
The latest libraries included in IBM’s expanded portfolio can be accessed and selected based on their functionality, and directly embedded into parts of an application. Among the additions is the IBM Watson Natural Language Processing Library, designed to aid developers in supplying human language processing functions in their applications to conjure meaning and context through intent and sentiment. The IBM Watson Speech to Text Library allows fast and accurate speech transcription for overall enhanced customer service experiences. Finally, the IBM Watson Text to Speech Library provides developers with the ability to convert written text into accurate, natural-sounding audio—in a variety of languages and voices—within an existing application.
“We wanted to make sure that we offered our IBM Watson technology in a way that application developers could easily embed in their application without deep expertise in AI or machine learning. So internally we studied products that developers love, and realized they all had a few things in common,” said Hemanth Manda, head of strategic partnerships for data and AI at IBM. “Developers need to be able to start getting value from technology in hours, not days or weeks, and they want a modular architecture so different capabilities can be pieced together like Lego blocks, making it faster to implement interesting AI use cases. Fast forward to today, we’ve developed a set of embeddable AI libraries that are used internally by IBM’s development teams across many of our popular software products—like Watson Assistant, Watson Discovery, Cloud Pak for Watson AIOps, and many more.”
IBM’s embeddable AI brings flexibility and customizability into the conversation of AI development. The developer is in control; where the AI is embedded and its management—whether on-premises, in a hosted cloud, or at the edge—is in the hands of the developer, according to the company. ISVs and their teams can adopt AI-powered capabilities to bring more novel solutions the market, faster. The addition of these latest libraries continues to mark IBM’s commitment to the IBM Ecosystem, helping partners access IBM solutions, resources, and expertise to go to market faster and develop their enterprises.
For more information regarding IBM’s embeddable AI and the latest libraries, please visit https://www.ibm.com/us-en?lnk=m.