The Science Behind Watson

Watson understanding natural language, breaking down the barrier between people and machines. See how Watson "learns," tracking feedback - learning from
success and failure - to improve future responses.

The history of Watson

IBM has a historical commitment to research - investing USD6 billion per year. Watson was a product of this commitment. The project began in 2006 with a team of IBM researchers collaborating with leading universities on a project called "Deep QA."

Jeopardy! was selected as the ultimate test of the machine's capabilities because it relied on many human cognitive abilities traditionally seen beyond the capability of computers, such as:

  • The ability to discern double meanings of words, puns, rhymes, and inferred hints.
  • Extremely rapid responses
  • The ability to process vast amounts of information to make complex and subtle logical connections
  • In a human, these capabilities come from a a lifetime of participation in human interaction and decision-making along with an immersion in pop culture.

For the Watson team, replicating these capabilities was an enormous challenge, moving beyond keyword searches and queries of structured data to asking questions and accessing and assessing a vast amount of unstructured data to find the best answer. But IBM that knew the solution to this challenge had the potential to change the way businesses use information and make decisions.

To meet this grand challenge, the Watson team focused on three key capabilities:

  • Natural language processing
  • Hypothesis generation
  • Evidence-based learning

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