IBM expands embeddable AI software portfolio

IBM has expanded its embeddable AI software portfolio with the release of three new libraries for natural language processing, speech to text , and text to speech.

Developed in IBM Research, these libraries provide independent software vendors (ISVs) a scalable way to build natural language processing, speech to text, and text to speech capabilities into applications across any hybrid, multi-cloud environment.

They are designed to help lower the barrier for AI adoption by addressing the skills shortage and development costs required to build machine learning and AI models from scratch.

Developer and IT teams can embed the new Watson libraries into their applications to help create customised and compelling products without data science expertise.

“Enterprises must commit to a significant investment in expertise, resources and time required to build, deploy and manage AI-powered solutions. 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,” said Kate Woolley, General Manager of IBM Ecosystem.