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.
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.
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 is IBM Watson important?
What distinguishes IBM Watson from other analytics software is its direct relevance to business problem solving.
Watson has the ability to rapidly analyze huge repositories of data, documents, and other artifacts and 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.
This tool 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.
Also, a robust set of APIs enables developers to incorporate the capabilities of IBM Watson into other business applications.
Check out this video for an easier explanation
Who all can apply IBM Watson?
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
- a data scientist who must develop algorithms and queries and can use Watson technology to derive the answers
- 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
In which sector is IBM’s Watson prevalent?
The medical field is the sector that is likely being impacted the most by Watson. For starters, Watson has taken residence at three of the top cancer hospitals in the US, Memorial Sloan Kettering Cancer Center, University of Texas MD Anderson Cancer Center, and the Mayo Clinic, where it helps with cancer research and patient care.
In terms of cancer research, Watson is speeding up DNA analysis in cancer patients to help make their treatment more effective.
In the financial sector, Watson use is typically geared toward its question and answer capabilities. By not only answering questions, but also analyzing them as well, Watson can help give financial guidance and help manage financial risk.
When it comes to the law, most of us likely have more questions than answers on any topic. However, startups such as ROSS Intelligence Inc. are using Watson to make it easier to get answers to your burning legal questions.
Modern retail experiences are all about personalization. Natural Selection is an app created by Sellpoints that uses Watson’s NLP capabilities to present products to customers at the most appropriate point in the buying cycle.
This can help reduce the overall number of clicks until conversion for an online retailer.
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