Watson is a question-answering AI system developed by IBM, famed for winning the Jeopardy! game show. As a major AI system, Watson can understand natural language, generate hypotheses, evaluate these hypotheses for relevance, and quiz answers based on users’ needs.


Imagine you have a super-smart robot friend who reads a lot of books and knows a lot about many things. You can ask this friend any question, and it’ll give you a very good answer. That super-smart friend is like Watson - an AI that’s really good at answering questions in a way people can understand.

In-depth explanation

Watson, developed by IBM, is a flagship example of a sophisticated AI system. Named after IBM’s founder, Thomas J. Watson, it made headlines for its victory in a 2011 episode of Jeopardy!, where it competed against two champion human players and won.

At its core, Watson employs a combination of AI techniques including natural language processing (NLP), information retrieval, automated reasoning, and machine learning (ML) that allow it to understand and respond accurately to natural language queries.

NLP allows Watson to understand questions posed by users in human language, parse them in a way a machine can understand, as well as to generate human-readable responses. Information retrieval aids Watson to search vast databases of structured and unstructured data for possible answers.

Automated reasoning, based on pre-defined rules and heuristics, allows Watson to form logical conclusions from data. Watson uses these conclusions to generate multiple potential answers (hypotheses), each of which is then independently evaluated based on evidence collected from relevant data sources.

Watson also uses its ML capabilities to continually learn and update its knowledge base as it encounters new information and questions. In essence, the more it’s used, the smarter it becomes. Watson’s ML component is primarily used for evidential support analysis, answer scoring, and question analysis.

This combination of technologies sets Watson apart. It enables it to process large volumes of data quickly - much faster than a human could - to produce a range of potential responses to any given query, and then rank them by likelihood to offer the best considered answer.

IBM offers Watson as part of its cloud services, allowing businesses to build and train their own AI applications. Watson’s APIs and SaaS (Software as a Service) offerings allow developers to integrate the power of AI into their own systems - from analyzing texts to detect sentiment and tone, to converting speech to text, language translation, and more.

Natural Language Processing (NLP), Machine Learning (ML), Artificial Intelligence (AI), Information retrieval, Automated reasoning, Cloud services, Knowledge base, Text-to-Speech, Sentiment Analysis, Turing Test