Attending a recent IBM Watson event, somebody in the crowd asked the speaker, “So, what is Watson? ” It’s a good question – and one isn’t really a straightforward answer to. Is it a brand? A supercomputer? A technology? Something else?
Essentially, it is an IBM technology that combines artificial intelligence and sophisticated analytics to provide a supercomputer named after IBM’s founder, Thomas J. Watson. While interesting enough, the real question, to my mind, is this: “What sort of cool stuff can businesses do with the very smart services and APIs provided by IBM Watson?”
IBM provides a variety of services, available through Application Programmable Interfaces (APIs) that can developers can use to take advantage of the cognitive elements and power of Watson. The biggest challenge to taking advantage of these capabilities is to “Think cognitively” and imagine how they could benefit your business or industry to give you a competitive edge – or, for not-for-profit organisations, how they can help you make the world a better place.
I’ve taken a look at some of the APIs and services available to see some of the possibilities with Watson. It’s important to think of them collectively rather than individually, as while some use-cases may use one, many will use a variety of them, working together. We’ll jump into some use-cases later on to spark some thoughts on the possibilities.
Natural Language Understanding
Extract meta-data from content, including concepts, entities, keywords, categories, sentiment, emotion, relations and semantic roles.
Identify useful patterns and insights in structured or unstructured data.
Add natural language interfaces such as chat bots and virtual agents to your application to automate interactions with end users.
Automate the translation of documents from one language to another.
Natural Language Classifier
Classify text according to its intent.
Extract personality characteristics from text, based on the writer’s style.
Text to Speech and Speech to Text
Process natural language text to generate synthesised audio, or render spoken words as written text.
Use linguistic analysis to detect the emotional (joy, sadness etc) linguistic (analytical, confident etc) and social (openness, extraversion etc) tone of a piece of text.
Make better choices when analysing multiple, even conflicting goals.
Analyse images for scenes, objects, faces, colours and other content.
All this is pretty cool stuff, but how can it be applied to work in your world? You could use the APIs to “train” your model to be more specific to your industry and business, and to help automate and add intelligence to various tasks.
Aerialtronics offers a nice example use-case of visual recognition in particular, they develop, produce and service commercial unmanned aircraft systems. Essentially, the company teams drones, an IoT platform and Watson’s Visual recognition service, to help identify corrosion, serial numbers, loose cables and misaligned antennas on wind turbines, oil rigs and mobile phone towers. This helps them automate the process of identifying faults and defects.
Further examples showing how Watson APIs can be combined to drive powerful, innovative services can be found on the IBM Watson website’s starter-kit page.
At this IBM event, a sample service was created, live in the workshop. This application would stream a video, convert the speech in the video to text, and then categorise that text, producing an overview of the content being discussed. The application used the speech-to-text and natural language classifier services.
Taking this example further with a spot of blue sky thinking, for a multi-lingual organisation, we could integrate the translation API, adding the resulting service to video conferencing. This could deliver near real-time multiple dialect video conferencing, complete with automatic transcription in the correct language for each delegate.
Customer and support service chat bots could use the Conversation service to analyse tone. Processes such as flight booking could be fulfilled by a virtual agent using the ‘Natural Language Classifier’ to derive the intent in the conversation. Visual recognition could be used to identify production line issues, spoiled products in inventory or product types in retail environments.
Identification of faded colours or specific patterns within scenes or on objects could trigger remedial services. Detection of human faces, their gender and approximate age could help enhance customer analysis. Language translation could support better communication with customers and others in their preferred languages. Trade-off Analytics could help optimise the balancing of multiple objectives in decision making.
This isn’t pipe-dreaming: the toolkit is available today. What extra dimensions and capabilities could you add to your organisation, and the way you operate? How might you refine your approach to difficult tasks, and the ways you interact with customers? Get in contact today to discuss the possibilities.