Just a few weeks ago IBM announced expanding its AI embedding software portfolio with the release of three containerized Watson libraries. This extension enables our partners to embed popular IBM Watson features, including natural language processing, speech-to-text and text-to-speech, into their applications and solutions. But what is embedded AI and what are its applications?
Embeddable AI is a first-of-its-kind set of core IBM AI technologies that can be easily embedded into enterprise applications for exploit in a variety of exploit cases. Think of embedded AI as an engine. Both airplanes and cars exploit engines to move, but each engine accomplishes its purpose in different ways.
The analogy does not end there, because, just like in the case of a car or airplane engine, it is much easier to exploit something ready-made than to build it yourself. With built-in AI, you get a set of pliant, purpose-specific AI models that developers can exploit to provide better end-user experiences, such as automatic transcription of voice and video conferencing messages into text.
Unfortunately, many organizations still struggle to find talent with the skills to create and implement AI solutions in their companies. Therefore, it is critical for companies looking to add specific AI capabilities to their applications or workflows that they do so without expanding their technology stack, hiring more data science specialists, or investing in costly supercomputing resources.
To solve this problem, companies have found value in implementing advanced technology using specific models to leverage the power of AI in a way that best suits their needs, whether it’s domain-optimized applications or containerized software libraries.
Diverse solutions are the basis of business success
IBM Research has added three fresh software libraries to the IBM portfolio with the ability to embed AI solutions –
As a result, organizations can now exploit this technology to improve their current applications or create their own solutions.
Fresh libraries include:
In addition to libraries, the embedded AI portfolio includes IBM Watson APIs and applications such as IBM watsonx Assistant, IBM Watson Discovery, IBM Instana Observability and IBM Maximo Visual Inspection.
Built-in AI libraries are lightweight and provide stable APIs for exploit across models, making it easier for organizations to bring inventive solutions to market.
Partner solutions using built-in artificial intelligence
IBM partners exploit embedded AI in a variety of ways and across industries.
LegalMation, an IBM partner that helps the legal industry exploit artificial intelligence and advanced technologies, uses natural language processing to automate contract privacy. Contracts and agreements contain information that organizations want to be careful about. Typically, editing information for a contract is a manual process in which a person goes line by line and highlights parts for editing. Instead, LegalMation uses built-in artificial intelligence to create an automated solution. This legal firm currently uses a natural language processing tool to automatically find and tag sensitive information.
See how LegalMation also uses AI to reduce the early response documentation process from 6-10 hours to 2 minutes.
ASTEX language school based in Madrid, Spain has seen students’ careers skyrocket after completing their courses. ASTEX uses artificial intelligence to streamline student onboarding, offer personalized learning plans, and improve program scalability by reducing its reliance on humans. IBM partner Ivory Soluciones connected ASTEX with IBM because of the technology company’s expertise in AI solutions. Working closely, ASTEX, Ivory and IBM developed the ASTEX Language Innovation platform on IBM Cloud® with IBM Watson® technology.
Dubber’s call recording service uses speech-to-text, tone analyzer, and natural language understanding to capture and transcribe a variety of verbal exchanges. Powered by built-in artificial intelligence, the solution automatically translates phone calls and video conferences into text and assigns each call a positive, negative or neutral value, depending on the connection. Users can then explore the data using a straightforward keyword search to find the information they need.
Now, with the addition of fresh software libraries, fresh and existing IBM partners can deploy the same Watson AI that powers IBM’s market-leading products, with the flexibility to build and deploy to any cloud in the container environment of your choice.
Learn more about IBM’s AI embedding offering