What is IBM Watson and what can it do?

Global, Aug 31, 2017

Author: Scott Hodges, Delivery Architect Information Insights at Logicalis UK, 

A cursory glance at the IBM Watson website suggests it’s a tool for building chatbots but, while it can, a deeper dive reveals a lot more. IBM describe it as an AI platform for business that can understand all forms of data, interact naturally with people, and learn and reason, at scale. Wow!

Named after IBM’s founder Thomas J. Watson, it is, essentially, a technology that combines artificial intelligence and sophisticated analytics to provide a supercomputer available as a SaaS and a set of Application Programmable Interfaces (APIs) that developers can use to take advantage of the cognitive elements and power of Watson.

While interesting enough, the real question, to my mind, is this: “What sort of cool stuff can businesses do with IBM Watson?”

I have taken a look at some of the APIs and services available to see some of the possibilities Watson presents.

Think of them collectively rather than individually, as while some use-cases may use one, many will use a variety of them, working together.

  1. Natural Language Understanding
    Extract meta-data from content, including concepts, entities, keywords, categories, sentiment, emotion, relations and semantic roles.
  2. Discovery
    Identify useful patterns and insights in structured or unstructured data.
  3. Conversation
    Add natural language interfaces such as chat bots and virtual agents to your application to automate interactions with end users.
  4. Language Translator
    Automate the translation of documents from one language to another.
  5. Natural Language Classifier
    Classify text according to its intent.
  6. Personality Insights
    Extract personality characteristics from text, based on the writer’s style. 
  7. Text to Speech and Speech to Text
    Process natural language text to generate synthesised audio, or render spoken words as written text.
  8. Tone Analyser
    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.
  9. Trade-off Analytics
    Make better choices when analysing multiple, even conflicting goals.
  10. Visual Recognition
    Analyse images for scenes, objects, faces, colours and other content.

IBM Watson in action

Aerialtronics offers a nice example use-case of visual recognition in particular, they develop, produce and service commercial unmanned aircraft systems. Essentially, the company combines 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.

For a multi-lingual organisation, you could integrate the translation API, adding the resulting service to video conferencing. This could deliver near real-time multiple dialect video conferencing with automatic transcription in the correct language for each delegate.

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. Trade-off Analytics could help optimise the balancing of multiple objectives in decision making.

This isn’t pipe-dreaming: the toolkit is available today.

How can IBM Watson help my business?

And the inevitable questions; what does this all mean for your business? 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?

Those are questions for you to answer, and you might want to consider the following:

  1. Present the concept of AI at your next ‘future strategy’ meeting and brainstorm the implications with your fellow executives.
  2. What could it mean for your products and services?
  3. Are there additional services and products you can create using something like IBM Watson?
  4. Speak with suppliers about how they might add value to the service they provide.
  5. Discuss the idea with your organisation’s technologists, what existing services might contribute to delivering AI services, what decisions are being made that might impede or facilitate delivery and what additional services and infrastructure would be needed to make this happen.
  6. What could the downsides be and how would you deal with them? Use a scenario plan to address them.
  7. Consider a small pilot project that could road test some of the ideas discussed and get that early mover advantage.
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