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IBM has announced the availability of three containerized Watson libraries, expanding their offering of embeddable AI software. With this update, IBM partners may now include well-known IBM Watson features like natural language processing, speech-to-text, and text-to-speech into their products and services. But what exactly is embeddable AI and how may it be used?
Embeddable AI is a new set of IBM core AI technologies that can be quickly linked to business applications to address a wide range of use cases. Imagine embedded AI to be an engine. Engines are used to move both planes and cars, but they generally serve a different way.
The similarity doesn’t end there either, as it is far easier to use a pre-made item than to create it yourself, just like with a car or airplane engine. Developers can improve end-user experiences by using embeddable AI to deliver a set of adaptable, fit-for-purpose AI models, such as those that automatically convert voicemails and video conferences to text.
However, a lot of businesses still have difficulty finding employees who have the necessary skills to create and implement AI solutions in their business. Therefore, it’s important for businesses that want to add specialized AI capabilities to their applications or workflows to be able to do so without having to upgrade their IT infrastructure, hire more data science, or make expensive supercomputing resource investments.
Businesses have discovered value in integrating strong technology with specific models to take advantage of AI’s potential in the manner that best suits their requirements in order to address this, whether it be through domain-optimized applications or containerized software libraries.
Three new software libraries from IBM Research have been added to IBM’s portfolio of embeddable AI solutions. These libraries are not systems and may be used in public clouds, on-premises, and at the edge.
As a result, businesses may now use this technology to improve the apps they already have or to create new ones.
The new libraries include:
In addition to the libraries, the embeddable AI portfolio includes IBM Watson APIs and applications like IBM Watson Assistant, IBM Watson Discovery, IBM Instana Observability, and IBM Maximo Visual Inspection.
Embeddable AI libraries are small and offer consistent APIs for use across models, making it simpler for businesses to market creative solutions.
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