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Recently, IBM announced that they have added three new containerized libraries to their portfolio of embeddable AI software. These new libraries allow partners to incorporate popular IBM Watson capabilities, such as natural language processing, speech-to-text, and text-to-speech, into their own applications and solutions. But what exactly is embeddable AI and what are its uses?
Embeddable AI is a suite of IBM’s core AI technologies that can be easily integrated into enterprise applications for a variety of purposes. It can be thought of as an engine that can be used in different ways, just like how an engine in a plane or a car helps those vehicles to function.
Similar to how using a pre-made engine is easier than building one from scratch, using embeddable AI allows developers to take advantage of a set of pre-made, flexible AI models that can be used to provide enhanced user experiences, such as automatically transcribing voice messages and video conferences into text.
However, many organizations still struggle to find talented individuals with the necessary skills to build and deploy AI solutions within their businesses. Therefore, it is important for companies that want to incorporate specific AI capabilities into their applications or workflows to do so without having to expand their technology stack, hire additional data science talent, or invest in expensive supercomputing resources.
To solve this problem, businesses have begun using embeddable AI technology and specific models to harness AI’s potential in the way that best fits their needs, whether it is through domain-optimized applications or containerized software libraries.
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IBM Research has added three new software libraries to IBM’s portfolio of embeddable AI solutions. These libraries are not tied to any particular platform and can be run across a range of environments, including public clouds, on-premises systems, 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:
The embeddable AI portfolio also includes IBM Watson APIs and programs including IBM Watson Assistant, IBM Watson Discovery, IBM Instana Observability, and IBM Maximo Visual Inspection in addition to the libraries.
These libraries are lightweight and offer stable APIs that can be used across different models, making it easier for organizations to develop and introduce new solutions to the market.
Embeddable AI is being used by IBM partners in a lot of situations and industries.
Natural language processing is used by LegalMation, an IBM partner that helps the legal industry in using AI and reducing technologies, to automate contract privacy. Information that should be carefully considered by businesses is usually included in contracts and agreements. Redacting data from a contract is typically a manual process that involves marking passages for redaction line by line. Instead, LegalMation develops an automated approach using embeddable AI. The legal firm now employs a natural language processing technology to automatically identify and mark sensitive information.
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