See how IBM Watson has advanced enterprise 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.
How Watson has evolved AI over time
2007
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.
2013
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.
2020
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.
2023
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.
Discover watsonx
Train, validate, tune, and deploy foundation and machine learning models with ease.
Scale AI workloads, for all your data, anywhere.
Accelerate responsible, transparent and explainable data and AI workflows.
Empower everyone in the organization to build and deploy AI-powered virtual agents without writing a line of code.
Enable employees to quickly offload time-consuming work to tackle more of the work only they can do.
Empower developers of all experience levels to write code with AI-generated recommendations.