Man vs. Machine: Computable Knowledge and Language Processing

Computers have come a long way since Charles Babbage's time. Babbage was the inventor of the concept of the programmable computer. He designed and attempted to build several machines including the Analytical Engine which was a programmable mechanical computer. It would have been the first Turing-complete (roughly implying it can simulate any other computer or proper program) machine ever. People at the time were confused by the entire concept of a computer.

"Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?" I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.

People thought that if a computer could do calculations it must be smart in the same way a person is smart, that is make deductions, inferences, and synthesize information to make conclusions. In the 1960's computers showed great promise and some researchers thought the age of truly intelligent machines was just a few years away. It turned out that the human mind is formidable opponent. Machines which think exactly like humans may not ever exist, but machines that 'think' are already here.

The final question, "William Wilkenson’s 'An Account of the Principalities of Wallachia and Moldavia' inspired this author's most famous novel." All contestants got the question right, but Jenning's knew he was not catching up.

Humans and machines were doing a lot of thinking this week when humans faced off against computers in a three day exhibition Jeopardy! match. The computer in the match was called Watson which was able to defeat Ken Jennings, the winngest ever Jeopardy player, and Brian Rutter, the all-time Jeopardy money winner. Watson is a purpose built technology demonstrating computer built by IBM which uses language processing and machine learning to play Jeopardy. A very good documentary produced by NOVA is available online which discuss the research and development that went into Watson, The Smartest Machine on Earth, which is a good watch even if you have been following the news on Watson. In the three day match things began slowly as Watson held is own, but occasionally stumbled. However, in the end Watson was light years ahead. Here is the recap:

This isn't the first time a human vs. machine battle has been played. In 1997 a highly publicized battle occurred between world chess champion Gary Kasparov and IBM's Deep Blue. Kasparov fell hard in the battle and even accused IBM of cheating. In retrospect his protests were in compete futility, as is proven by the fact that in 2006 world chess champion Vladimir Kramnik was beaten by a computer, Deep Fritz, running on a standard personal computer (running two Intel Core 2 Duo). Chess playing computers are not too 'smart'; they basically use their computing power to play out likely board configurations and so the techniques employed by chess playing programs have been excluded from some definitions of artificial intelligence. And of course maybe Watson isn't that smart either you could say. Watson uses knowledge humans have gathered, finds patterns, finds the relative strength of each answer, and returns the answer. It is hard to exactly define what intelligence is so I won't even try. Instead I will make two observations about the implications of machines besting humans. First, what takes a super computer at one point, will take a microchip in the future as indicated by the evolution of chess playing computers. Second, while the argument about what intelligence is goes on the pace and ability of computers also goes on.

How does Watson think? Watson uses machine learning. Basically Watson is fed a bunch of text documents like Wikipedia and IMDB (note that Watson was not online during the Jeopardy competition, but had access to these documents pre archived). Then programmers feed Watson questions and correct answer pairs which Watson can use to look through its database to find patterns. A complex architecture of rules and statistics allow Watson to choose the right answer, but amazingly programmers on the project don't explicitly tell Watson how or what the right answer is. Modern computer programs are big and complicated so it is best to let the computer take care of writing their own programs.

Watson's success means there is a bright future for language processing computers (at least IBM wants us to think so and buy their products). I have been contemplating the merger of Wolfram|Alpha and IBM's Watson as the ultimate language processing computational engine. Alpha if you have never used it is a live web program that anyone can use. The creator, Stephen Wolfram, calls Alpha a computational knowledge engine. This means that Alpha doesn't parse language in the most human receptive manner, but it has powerful database and computational algorithm resources such that if you want to know the error function of the GDP of Italy divided by the GDP of the US all divided by the 144th prime, well you can do that. Also, Alpha can do math, and how. IBM's Watson on the other hand could tell you the name of the country with its boot dipped in the Mediterranean. These smart computers are different for obvious reasons, they have access to different information databases and they are programed differently. An explanation of the difference recently came up on Stephen Wolfram's blog in pictorial form.

It would be a powerful combination to have Alpha's database and analytical skills paired with Watson's language processing. Perhaps we will have a Watson|Alpha soon. I remarked to a colleague in jest the other day that if they made such a machine I would be out of a job, but he replied that I would still have job as long as computers only have answers and not questions. True enough. I am reminded of the Hitchhikers Guide to the Galaxy where an immense computer calculates the answer to the universe, however, with the answer in hand it is realized a bigger more powerful computer must be constructed to determine the question.