IBM Watson first garnered worldwide attention in 2011 as the computerized “brain” that won one million dollars on the TV game show Jeopardy! by beating human contestants. Since then, IBM Watson has gained a reputation as a thinking machine that can crunch through mountains of data and turn out answers in fractions of a second. But what exactly is it? This primer on IBM Watson answers that question.
- What it is: IBM Watson is a data analytics processor that uses natural language processing, a technology that analyzes human speech for meaning and syntax. IBM Watson performs analytics on vast repositories of data that it processes to answer human-posed questions, often in a fraction of a second.
- Why it matters: IBM Watson’s cognitive and analytical capabilities enable it to respond to human speech, process vast stores of data, and return answers to questions that companies could never solve before.
- Who this affects: IBM Watson affects companies in various industry sectors. IBM Watson technology most immediately affects the data analytics team, but it can also affect key executive decision makers who act on Watson’s findings and business practitioners who use Watson for their work.
- When this is happening: Companies in a host of industries are already running IBM Watson for predictive analytics and problem solving. IBM Watson gives them a competitive advantage and helps them return more value to their customers and constituents.
- How to get it: Companies that can afford the multiple millions of dollars that a Watson system costs can run the system internally. Fortunately, Watson access is also available through the IBM cloud for a variety of industry verticals, making it a viable option for many small and midsize companies.
What it is
IBM Watson is a data analytics processor that uses natural language processing, a technology that analyzes speech for meaning and syntax and translates this into actionable answers.
IBM Watson was named after IBM’s first CEO, Thomas J. Watson. The technology behind Watson was originally developed in an IBM research project known as DeepQA. The goal of the project was to develop a natural language-responsive system that could interpret questions asked in a human language and then analyze vast amounts of data and return answers that it would take human researchers days, weeks, or even months to derive.
The 2011 Jeopardy! contest against the game show’s champions Ken Jennings and Brad Rutter was IBM Watson’s first public test; in the end, Watson was victorious.
Two years later, IBM announced the first commercial application of Watson was designed for Sloan Kettering Cancer Center and WellPoint insurance. The application performed cost management analysis in the treatment of lung cancer.
Today, IBM Watson is used in a multitude of industry sectors with specialized information needs, including veterinary science, environmental and geotechnical engineering, education, government, food and beverage, legal, and music and entertainment.
Why it matters
What distinguishes IBM Watson from other analytics software is its direct relevance to business problem solving. Watson has the ability to rapidly analyze gargantuan repositories of data, documents, and other artifacts; it also comes with a level of human speech pattern recognition and language understanding that was elusive for many artificial intelligence applications in the past. IBM Watson uses cognitive learning practices that combine the data analytics and statistical reasoning of machines with uniquely human qualities, such as self-directed goals, common sense, and ethical values.
As a top layer to all of this, IBM has packaged various versions of Watson to address the specific business concerns and questions of different industry verticals.
Watson also plays a key role in managing unstructured data, which according to IBM, comprises around 80% of data under management in a majority of companies. Watson processes unstructured text and documentation by “learning” a subject by pairing questions and answers after the user loads all related materials (e.g., Word documents, .pdf files, web pages, etc.). The platform is capable of processing millions of documents, and reading 800 million pages of data per second.
IBM Watson also processes natural language, which can help businesses be more efficient. For example, an insurance company or a healthcare company can use Watson to review medical reports in order to isolate key medical terms; or a physician might use Watson to pore through millions of pages of clinical research in an attempt to isolate a medical condition, and arrive at a diagnosis and treatment plan.
Watson is now offered by IBM in the cloud. This means that companies can start small in their use of Watson and pay for only what they need, without having to invest in expensive on-premises computing.
Who this affects
IBM Watson technology can apply to a broad range of companies, institutions, and public sector entities because it has been customized to many of these industries’ knowledge bases. Within companies, the use of Watson can fall under the purview of, for example:
- a data architect who is tasked with big data and analytics responsibilities; or
- a data scientist who must develop algorithms and queries and can use Watson technology to derive the answers; or
- an end business user, like a doctor in a medical practice who wishes to describe a physical condition to Watson and obtain Watson’s assessments about a probable diagnosis.
When this is happening
IBM Watson is in operation now in many industry verticals, ranging from healthcare predictive analytics and condition diagnosis to smart city infrastructure planning and legal case outcome analysis.
IBM Watson runs on IBM Power servers that are not really supercomputers in the classic sense, but that act that way when they are clustered together in groups of tens and even hundreds of servers, with a price point for an internal system that only a large enterprise or a research institute can afford. The good news for small and midsize companies is that they can use Watson, too; IBM offers a cloud-based version of Watson that companies can pay for by subscription or on demand.
Image: Jason Hiner/TechRepublic
How to get it
Companies that can afford an investment into multiple millions of dollars can purchase an in-house Watson system, which consists of futile servers tethered together into a processing cluster. For companies without these resources, Watson can be accessed through the IBM cloud. For example, IBM offers a software developer’s cloud powered by Watson. It also provides a cloud-based global healthcare analytics cloud.