IBM’s Watson is a cognitive computing system, one that behaves like our brain, learning through experiences, finding correlations, and remembering — and learning from — the outcomes.
First hitting the spotlight when pitted against two of Jeopardy’s biggest all-time winners Ken Jennings and Brad Rutter, IBM’s artificial intelligence machine names Watson threw these two off their throne in quick fashion – showing that artificial intelligence was a real thing and IBM has the technology.
Artificial intelligence is here now. This doesn’t mean that Cylons disguised as humans have infiltrated our societies, or that the processors behind one of the search engines have become sentient and are now making their own plans for world domination. But denying the presence of AI in our society not only takes away from the achievements of science and commerce, but also runs the risk of complacency in a world where more and more of our actions and intentions are being analyzed and influenced by intelligent machines. Not everyone agrees with this way of looking at the issue, though.
First, although Watson includes many forms of text search, it is first and foremost a system capable of responding appropriately in real-time to new inputs. It competed against humans to ring the buzzer first, and Watson couldn’t ring the buzzer until it was confident it had constructed the right sentence. And, in fact, the humans quite often beat Watson to the buzzer even when Watson was on the right track. Watson works by choosing candidate responses, then devoting its processors to several of them at the same time, exploring archived material for further evidence of the quality of the answer. Candidates can be discarded and new ones selected. IBM is currently applying this general question-answering approach to real-world domains like health care and retail.
This is very much how primate brains (like ours) work. Neuroscientists can recognize which brain cells monkeys use to represent different hypotheses about how to solve the current puzzle they are facing. Then, he can watch the different solutions compete for influence in the brain, until the animal finally acts when it is certain enough. If the puzzle has a short time limit, the animals will act for a lower threshold and will be less accurate. Just like us. And it wouldn’t be hard to reprogram Watson to do the same thing—to give its best answer at a fixed time rather than at a fixed level of certainty.
How about understanding? Watson does search text in various Internet sources (like Wikipedia) but didn’t during competition. It had to read the text in advance and remember it in a generalized way so that it could access what it had learned quickly by all different kinds of clues. Jeopardy! questions require understanding jokes and metaphors—what Hofstadter calls “analogical reasoning.” Being able to use the right word in the right context is the definition of understanding language, what linguists call semantics. If someone blind from birth said to you “I’ll look into it” or “See you later,” would you say they didn’t understand what they were saying?
If you’re looking for a thumb in the pie, IBM are now offering up part of Watson – their breakthrough natural language-based cognitive service called Watson Analytics. This analytic service is reported as a powerful predictive and visual analytic tool for businesses and can now be rented through a beta program.
There has already been 22,000 who’ve registered for the beta of this service, with IBM’s official explanation and release reading: “IBM Watson Analytics automates the once time-consuming tasks such as data preparation, predictive analysis, and visual storytelling for business professionals. Offered as a cloud-based freemium service, all business users can now access Watson Analytics from any desktop or mobile device”.
IBM was totally “as been” during the last twenty years (1994 – 2014), going slowly towards the end of the company. But Watson, IBM could revolutionize the management of semantics which is currently lacking treatment ‘Analytics’ and take the lead on a niche again.
For the moment, it is really artificial intelligence but not more, as we can imagine with aware artificial…, for the moment. But it is probably the beginning. Aware artificial will be probably the next disruptive industrial revolution before the end of the 21 century…