How did IBM’s Watson get to where it is today? Here are some key events that happened along the way.
May 1997: Deep Blue conquers chess
IBM’s Deep Blue computer beats world chess champion Garry Kasparov in a six-game match that lasts several days and receives massive media coverage around the world. It also inspires researchers at IBM to undertake an even bigger challenge: build a computer that could beat the champions at Jeopardy.
February 2011: Victorious at Jeopardy
Watson competes on Jeopardy and defeats the TV quiz show’s two biggest all-time champions. It wins US$1 million; IBM donates the full amount to charity.
January 2014: A business unit is born
IBM launches the IBM Watson Group, a business unit dedicated to developing and commercializing the technology. Later that year, it opens a global headquarters in New York City’s “Silicon Alley.”
April 2015: Honing in on health
We each generate one million gigabytes of health-related data across our lifetime, IBM says. The Watson Health business unit aims to help patients, physicians, researchers and insurers use that data for better health.
December 2015: A new IoT branch
IBM opens a new Watson internet of things (IoT) global headquarters in Munich, Germany.
February 2016: Watson for U.S. president?
Though it says it’s not affiliated with IBM, the Watson 2016 Foundation launches the “Watson for President” website to help promote the technology’s presidential prospects.
May 2016: Eight languages and counting
Watson begins learning Korean, bringing the total number of its conversational languages to eight. Also part of its repertoire are English, French, Italian, Spanish, Brazilian Portuguese, Japanese, and Arabic.
May 2016: Off to (cybersecurity) school
IBM Security announces a year-long research project through which it is collaborating with eight universities to help train Watson to tackle cybercrime.
June 2016: Learning to drive
Local Motors debuts Olli, the first self-driving vehicle to integrate Watson’s capabilities. The 12-passenger electric vehicle analyzes and learns from transportation data produced by more than 30 sensors embedded throughout the vehicle. It also leverages four Watson developer APIs to enable smooth interactions between passengers and the vehicle.