Watson then must push a physical buzzer to respond, just like its human competitors. While this would seem to be a task at which computers would have an overwhelming advantage, Welty noted that Rutter was so well-known for his lightning-fast buzzing that the producers weren't even mildly concerned.
But later, on a "Name That Decade" answer, Jennings responded incorrectly with "what is the s? During a commercial after Watson's decade gaffe, Welty noted that the team thought the ability to process other players' wrong responses would be unnecessary.
Watson also tripped up on an "Olympic Oddities" answer, but so imperceptibly that Alex Trebek didn't notice at first, raising an important point of clarification. After Jennings responded incorrectly that Olympian gymnast George Eyser was "missing a hand," Watson responded, "What is a leg?
Welty said Trebek initially accepted Watson's response, but the taping had to be stopped and the sequence reshot because Trebek had forgotten that Watson wasn't aware of the context created by Jenning's response. IBM trumpets Watson, which has been in development for years and has the processing power of 2, "powerful computers," as a major advancement in machines' efforts to understand human language.
The computer receives clues through digital texts and then buzzes in against the two other "Jeopardy! It juggles dozens of lines of reasoning at once and tries to arrive at a smart answer. In one instance, it repeated an answer that another contestant, Ken Jennings, who won 74 "Jeopardy!
On many other clues, however, Watson was spot-on. After losing the first clue to Brad Rutter, another "Jeopardy! At the start of the show, Trebek went to some lengths to explain the origins of Watson -- IBM approached the show about the idea three years ago -- and how the computer actually works. That's partly because what you see on the "Jeopardy! And there are other safety nets too. The doctor and a data scientist are sitting next to each other, correcting Watson.
Spurious material, or conflicted material or something from a pharmaceutical company that the doctor feels may be biased - that is caught during the training cycle," added Saxena. WellPoint and MSKCC used Watson as the basis for systems that could read and understand volumes of medical literature and other information - patients' treatment and family histories, for example, as well as clinical trials and articles in medical journals - to assist oncologists by recommending courses of treatment.
Interactive Care Insights for Oncology provides suggestions for treatment plans for lung cancer patients, while New WellPoint Interactive Care Guide and Interactive Care Reviewer reviews clinicians' suggested treatments against their patients' plans and is expected to be in use at 1, healthcare providers this year.
Watson has bigger ambitions than a clinician's assistant, however. Its medical knowledge is around that of a first year medical student, according to IBM, and the company hopes to have Watson pass the general medical licensing board exams in the not too distant future. We're starting with cancer and we will soon add diabetes, cardiology, mental health, other chronic diseases.
And then our work is on the payment side, where we are streamlining the authorisation and approval process between hospitals, clinics and insurance companies," Saxena said. The ultimate aim for Watson is to be an aid to diagnosis - rather than just suggesting treatments for cancer, as it does today, it could assist doctors in identifying the diseases that bring people to the clinics in the first place.
Before then, there is work to be done. While big data vendors often trumpet the growth of unstructured data and the abandoning of relational databases, for Watson, it's these older sources of data that present more of a problem. Watson does not process structured data directly and it doesn't interpret images.
It can interpret the report attached to an image, but not the image itself. In addition, IBM is working on creating a broader healthcare offering that will take it beyond its oncology roots.
We're using it as a learning process to create algorithms and methodologies that would be readily generalisable to any area of healthcare. They don't have to have to say, right, we have oncology under control, now let's start again with family practice or cardiology," Kohn said. Watson has also already found some interest in banking. Citi is using Watson to improve customer experience with the bank and create new services. It's easy to see how Watson could be put to use, say, deciding whether a borderline-risk business customer is likely to repay the loan they've applied for, or used to pick out cases of fraud or identity theft before customers may be aware they're happening.
Citi is still early in its Watson experiments. A spokeswoman said the company is currently just "exploring use cases". From here on in, rather than being standalone products, the next Watson offerings to hit the market will be embedded into products in the IBM Smarter Planet product line. They're expected to appear in the second half of the year. The idea behind the Engagement Advisor, aimed at contact centres, is that customer service agents can query their employers' databases and other information sources using natural language while they're conducting helpline conversations with their clients.
One of the companies testing out the service is Australia's ANZ bank, where it will be assisting call centre staff with making financial services recommendations to people who ring up. Watson could presumably one day scour available evidence for the best time to find someone able to talk and decide the communication channel most likely to generate a positive response, or pore over social media for disgruntled customers and provide answers to their problems in natural language.
There are also plans to change how Watson's delivered, too. Instead of just interacting with it via a call centre worker, customers will soon be able to get to grips with the Engagement Advisor. Rather than have some call centre agent read out Watson generated information to a customer with, say, a fault with their new washing machine or a stock-trader wanting advice on updating their portfolio, the consumer and trader could just quiz Watson directly from their phone or tablet, by typing their query straight into a business' app.
Apps with Watson under the hood should be out in the latter half of this year, according to Forbes. IBM execs have also previously suggested that Watson could end up a supercharged version of Siri , where people will be able to speak directly into their phone and pose a complex question for Watson to answer - a farmer holding up his smartphone to take video of his fields, and asking Watson when to plant corn, for example.
IBM is keen to spell out the differences between Watson and Siri. Siri, on the other hand, simply looks for keywords to search the web for lists of options that it chooses one from," the company says.
But, the comparison holds: Watson could certainly have a future as your infinitely knowledgeable personal assistant. While adding voice-recognition capabilities to Watson should be no great shakes for IBM given its existing partnerships, such a move would require Watson to be able to recognise images something IBM's already working on that would require Watson to query all sorts of sources of information including newspapers, books, photos, repositories of data that have been made publicly available, social media and the internet at large.
That Watson should take on such a role in the coming years, especially if the processing goes on in an IBM datacentre and not on the mobile itself, as you would expect, is certainly within the realms of the possible. As IBM seeks to embed Watson's capabilities into more and more products, how far does the company think Watson will spread in the coming years? It will only say gnomically, "as we continue to scale our capabilities, we intend to make Watson available as a set of services in many industries.
Better ask Watson. Jo Best has been covering IT for the best part of a decade for publications including silicon. IBM Watson wowed the tech industry and a corner of U. Here's how IBM pulled it off and a look at what Watson's real career is going to be. Watson has moved on to solutions that can power searches from smartphones. Image: IBM. This chart, done a year after Watson's Jeopardy win, shows some of its rapid progress.
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