Whether you realize it or not, you might be interacting with IBM watsonx™ daily, such as when booking a flight, speaking with customer service, working with IT, playing fantasy football, or engaging in numerous other activities. While the growing popularity of consumer AI chatbots have led many companies to recently enter the artificial intelligence (AI) space, IBM’s journey with AI has been decades in the making.
In fact, IBM has been involved with AI for over 70 years and partners with companies across various industries and geographies, from financial services to retail, space, and education. These companies are using watsonx to help unlock new insights, drive productivity, and deliver better customer experiences. But before we discuss what watsonx is doing for enterprises today, let’s take a look back.
Where it all started
During the second half of the 20th century, IBM researchers used popular games such as checkers and backgammon to train some of the earliest neural networks, developing technologies that would become the basis for 21st-century AI. These programs helped the team study strategy and improve a computer’s gameplay through trial and error. One IBM researcher of note, Arthur Samuel, called this process “machine learning,” a term he coined that remains central to AI today.
Just a decade later, IBM made another major contribution to the field of AI with the introduction of a “Shoebox” at the 1962 World’s Fair. Named for its small size, the IBM machine was the world’s first speech-recognition system created to recognize the human voice. An early hint of today’s natural language processing (NLP), Shoebox could calculate a series of numbers and mathematical commands spoken to it, creating a framework used by the smart speakers and automated customer service agents popular today.
In the following two decades, IBM continued to advance AI with research into machine learning, algorithms, NLP and image processing. During this time, IBM also experimented with robots that could automatically assemble typewriter components, created a manufacturing language (AML) used to program robots with the ability to learn from their actions and demonstrated AI applications. IBM invested in the field alongside leading educational institutions, further laying the foundation for today’s AI.
Fast forward to the 1990s
In the last decade of the 20th century, IBM once again used games to help drive the development of AI. In 1992, a program called TD-Gammon, written by IBM researcher Gerald Tesauro, taught itself to play backgammon well enough to compete with professional players. That year, it went 19–19 in 38 games at a World Cup of Backgammon event; a better performance than other backgammon programs up to that point.
Next, IBM set its sights on the complex game of chess. In the late 90s, IBM introduced Deep Blue, aiming to develop a computer powerful enough to beat a grandmaster. The new computer system could evaluate 200 million chess positions per second, achieving a processing speed of 11.38 billion floating-point operations per second. Deep Blue made history in 1997 when it became the first machine to defeat world chess champion Garry Kasparov under standard tournament time controls. Deep Blue has since been retired to the Smithsonian Museum in Washington, D.C., but its legacy extends far beyond the gameboard. The computer demonstrated how computing could be harnessed to solve complex technological and business problems.
IBM AI enters the aughts
Less than a decade after Deep Blue’s victory, IBM reached another milestone when it unveiled IBM Watson® in 2004. The room-sized computer, named after IBM’s first CEO, Thomas J. Watson Sr., consisted of 10 racks holding 90 servers, with a total of 2,880 processor cores.
Watson was part of a new generation of machines that could understand questions posed in natural language and answer them accurately by ingesting vast amounts of information from sources, such as Wikipedia, encyclopedias, dictionaries, religious texts, novels and plays. Equipped to find and understand clues, compare possible answers by ranking their accuracy, and respond—all in under three seconds—Watson was poised for another human-versus-machine challenge.
In a televised Jeopardy! contest viewed by millions in February 2011, Watson competed in two matches against the foremost all-time champions. Tied with one of the contestants at the start of the second match, Watson made history by pulling into the lead and eventually winning USD 77,147, which was donated to various charities, besting Ken Jennings’s USD 24,000 and Brad Rutter’s USD 21,600.
In the years following, IBM continued to push the capabilities of AI, this time with Project Debater, the first AI system designed to meaningfully engage with humans in a debate. In February 2019, IBM pitted Project Debater against Mr. Harish Natarajan, one of the world’s leading professional debaters, in an event broadcast live worldwide. The computer set the stage for how machines could help businesses make decisions at the enterprise level by using capabilities such as Key Point Analysis, designed to examine large bodies of complex documents and produce a ranked list of summarized key points; a concise, data-driven list of information users can quickly act on.
Watson is Gen AI for Gen Z
IBM has applied its more than 70 years of AI research, investment and experimentation to the enterprise with watsonx, its AI and data platform unveiled in May 2023. Watsonx is designed to empower enterprises to train, validate, tune and deploy foundation and machine learning models with ease; scale AI workloads for their data, anywhere; and accelerate responsible, transparent and explainable data and AI workflows.
IBM is now bringing open innovation to AI by open-sourcing a family of its most advanced and performant language and code IBM® Granite™ models. This approach invites partners, clients, developers and global experts to build on the models’ strengths and push the boundaries of what AI can achieve in enterprise environments.
Also, to support the business adoption of AI, IBM is working with partners across industries. These partners are upskilling their employees by securing watsonx proficiency badges, infusing AI into their own solutions, building centers of excellence to support value creation, and selling watsonx-powered solutions through marketplaces.
While many companies have just begun to explore the possibilities of AI for the enterprise, IBM’s decades-long research, investment and experimentation have created a legacy in AI leadership. This enables us to develop AI technology trusted and supported by an ecosystem of partners that help enterprises around the world embed IBM AI into their offerings and operations to modernize their business.
Elevate your AI with IBM watsonx. Train, deploy and scale models effortlessly.
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