IBM Watson is a cognitive system that enables a new partnership between people and computers. It is the AI offering from IBM. Watson combines five core capabilities:
- Interacts with people more naturally, based on the person’s preference.
- Quickly ingests key industry materials, partnering with experts to scale and elevate expertise.
- Enables new products and services to sense, reason and learn about their users and the world around them.
- Uses data to improve business processes and forecasting, increasing operational effectiveness.
- Enhances exploration and discovery, uncovering unique patterns, opportunities and actionable hypotheses.
IBM Watson is at the forefront of a new era of computing: the AI era. In summary, Watson can understand all forms of data, interact naturally with people, and learn and reason, at scale. Data, information, and expertise create the foundation for working with Watson. Watson AI technologies are available as a set of open application programming interfaces (APIs) and software as a service (SaaS) industry solutions.
IBM's Watson is on the forefront of the Cognitive Computing. Cognitive computing enables the users to create a profoundly new kind of value, finding answers and insights locked away in the volumes of data.
Watson (unlike the traditional computing) can understand unstructured data and relies on Natural Language which is governed by the rules of grammar, context and culture. Its implicit, ambiguous, complex and a challenging to process.
Watson doesn't just look for keyword matches and synonyms like a search engine, it actually reads and interprets texts like a person by breaking down the sentence, grammatically, relationally and structurally to extract meaning from the semantics of the written material.
When Watson has to work in a particular field, it learns the language, jargons and the motive thought of that domain. With the gardens of human expertise, Watson collects the knowledge required to have literacy in a particular domain what's called the Corpus of knowledge. Data curation is the process of adding data assets to a project or a catalog, enriching them by assigning classifications, data classes, and business terms, and analyzing and improving the quality of the data.
Next the data is preprocessed by Watson, building indices and other meta data that make working with that content more efficient. This is known as Ingestion. At this point, Watson may create a graph to answer more precise questions.
After Watson has ingested the corpus, it needs to be trained by a human expert to learn how to interpret the information. To learn the best possible responses and acquire the ability to find patterns, Watson partners with experts, who train it using an approach called Machine Learning. An expert loads training data into Watson in the form of question-answer pairs that serves as ground truth. This doesnt give Watson explicit answers for every question it will receive but rather, teaches it the linguistic pattens of meaning in the domain.
Once it has learnt through question answer pairs, it continues to learn through the ongoing interactions between users and Watson that are periodically reviewed by experts and fed back into the system to help Watson better interpret information. Likewise, as new information is published, Watson is updated so that it is constantly adapting to shifts in knowledge and linguistic interpretations in any given field.
Watson is now ready to respond to questions about highly complex situations and quickly provide suggestions.
IBM Watson is available as:
- A set of AI services on IBM Cloud
- Industry solutions for a wide variety of industries
- Tools, documentation, and samples for developers