IBM Watson
See how IBM Watson has advanced enterprise AI.

Overview

70 years advancing AI

IBM’s research in AI goes back to the 1950s and includes significant milestones like the supercomputer Deep Blue defeating chess grandmaster Garry Kasparov. In 2011, IBM Watson defeated Brad Rutter and Ken Jennings in the Jeopardy! Challenge. To find and understand the clues in the questions, Watson compared possible answers by ranking its confidence in their accuracy, and responded — all in under three seconds.

Watson sparked curiosity around “machines that could think” and opened up the possibilities around how AI could be applied to business. Clients in industries ranging from financial services to retail put Watson to work to unlock new insights, drive productivity and deliver better customer experiences. Now through advancements in core Watson technologies, IBM has developed the next generation of AI products with watsonx.

IBM Watson

IBM Research started working on the grand challenge of building a computer system that could compete with champions at the game of Jeopardy!. Just four years later in 2011, the open-domain question-answering system dubbed Watson beat the two highest ranked players in a nationally televised two-game Jeopardy! match.

IBM Watson Developer Cloud

IBM Watson technology became available as a development platform in the cloud. The move spurred innovation and fueled a new ecosystem of entrepreneurial software application providers–ranging from start-ups and emerging, venture capital-backed businesses to established players.

IBM Watson Discovery Advisor

IBM Watson Discovery Advisor was designed to cut through data quickly and find unexpected connections in raw data.

IBM Watson NLP Library

IBM Watson Natural Language Processing (NLP) teams across the world set out on a reuse journey, bringing IBM's NLP into one unified stack, so that every product and AI application could benefit from the best innovations IBM had to offer.

IBM Watson Assistant

IBM Watson Assistant released a beta version of a new intent detection model. Intent, the frontline of any conversation interface like chatbots, needs to accurately recognize and categorize user intent. By combining traditional machine learning, transfer learning and deep learning techniques, IBM Watson Assistant was faster and more accurate with less training required.

watsonx

In 2023, IBM announced the watsonx AI portfolio, which allows partners to train, tune and distribute models with generative AI and machine learning capabilities. Under development for three years, IBM designed watsonx to manage the life cycle of foundation models that are the basis of generative AI capabilities and for creating and tuning machine learning models.