Complexity
June 30th, 2008 by finalchildren
The Google Way of Science
There’s a dawning sense that extremely large databases of information, starting in the petabyte level, could change how we learn things. The traditional way of doing science entails constructing a hypothesis to match observed data or to solicit new data. Here’s a bunch of observations; what theory explains the data sufficiently so that we can predict the next observation?
It may turn out that tremendously large volumes of data are sufficient to skip the theory part in order to make a predicted observation. Google was one of the first to notice this. For instance, take Google’s spell checker. When you misspell a word when googling, Google suggests the proper spelling. How does it know this? How does it predict the correctly spelled word? It is not because it has a theory of good spelling, or has mastered spelling rules. In fact Google knows nothing about spelling rules at all.
Computational complexity theory - Wikipedia, the free encyclopedia
Computational complexity theory, as a branch of the theory of computation in computer science, investigates the problems related to the amounts of resources …
Complexity - Wikipedia, the free encyclopedia
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In general usage, complexity often tends to be used to characterize something with many parts in intricate arrangement. In science there are at this time a …
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Instead Google operates a very large dataset of observations which show that for any given spelling of a word, x number of people say “yes” when asked if they meant to spell word “y.” Google’s spelling engine consists entirely of these datapoints, rather than any notion of what correct English spelling is. That is why the same system can correct spelling in any language.
In fact, Google uses the same philosophy of learning via massive data for their translation programs. They can translate from English to French, or German to Chinese by matching up huge datasets of humanly translated material. For instance, Google trained their French/English translation engine by feeding it Canadian documents which are often released in both English and French versions. The Googlers have no theory of language, especially of French, no AI translator. Instead they have zillions of datapoints which in aggregate link “this to that” from one language to another.
Once you have such a translation system tweaked, it can translate from any language to another. And the translation is pretty good. Not expert level, but enough to give you the gist. You can take a Chinese web page and at least get a sense of what it means in English. Yet, as Peter Norvig, head of research at Google, once boasted to me, “Not one person who worked on the Chinese translator spoke Chinese.” There was no theory of Chinese, no understanding. Just data. (If anyone ever wanted a disproof of Searle’s riddle of the Chinese Room, here it is.)
If you can learn how to spell without knowing anything about the rules or grammar of spelling, and if you can learn how to translate languages without having any theory or concepts about grammar of the languages you are translating, then what else can you learn without having a theory?
In a cover article in Wired this month Chris Anderson explores the idea that perhaps you could do science without having theories.
this is a exceptional where massive amounts of data and applied mathematics replace every other means that might be brought to bear. out with every theory of human behavior, from linguistics to sociology. ignore taxonomy, ontology, and exceptional. who knows why people do what they do? the point is they do it, and we can track and measure it with unprecedented fidelity. with sufficiently observations, the numbers speak for themselves. petabytes allow us to express: “correlation is adequate.” we can stop looking as a replacement for models. we can analyze the data without hypotheses fro what it might reveal b stand out. we can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms acquire patterns where sphere cannot.
There may be something to this observation. Many sciences such as astronomy, physics, genomics, linguistics, and geology are generating extremely huge datasets and constant streams of data in the petabyte level today. They’ll be in the exabyte level in a decade. Using old fashioned “machine learning,” computers can extract patterns in this ocean of data that no human could ever possibly detect. These patterns are correlations. They may or may not be causative, but we can learn new things. Therefore they accomplish what science does, although not in the traditional manner.
Complexity
Contents and abstracts for last five years. Full text to subscribers. Links to associated sites and supplementary material.
Amazon.com: Complexity: The Emerging Science at the Edge of Order …
Amazon.com: Complexity: The Emerging Science at the Edge of Order and Chaos: M. Mitchell Waldrop: Books.
What Anderson is suggesting is that sometimes enough correlations are sufficient. There is a good parallel in health. A lot of doctoring works on the correlative approach. The doctor may not ever find the actual cause of an ailment, or understand it if he/she did, but he/she can correctly predict the course and treat the symptom. But is this really science? You can get things done, but if you don’t have a model, is it something others can build on? We don’t know yet. The technical term for this approach in scie …
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Gates to step down from Microsoft
June 29th, 2008 by finalchildren
The chairman of Microsoft and one of the world’s richest men, Bill Gates, is stepping down from his job running the world’s largest software company.
Mr Gates, who made his fortune through developing software for the personal computer, plans to devote his time to charity work.
As a teenager Bill Gates had a vision of a personal computer on every desk in every home.
He says he caught sight of the future and based his career on what he saw.
Great responsibility
The son of a successful lawyer from Seattle, Mr Gates programmed his first computer at the age of 13.
During his two years at Harvard University, he spent much of his time finessing his programming skills as well as enjoying the occasional all-night poker session.
He eventually dropped out of college and moved to Albuquerque, in New Mexico, where he set up Microsoft with his childhood friend, Paul Allen.
Their big break came in 1980 when Microsoft signed an agreement with IBM to build the operating system that became known as MS-DOS.
Microsoft went public in 1986 and within a year Bill Gates, at 31, had become the youngest self-made billionaire.
In an interview with the BBC, Mr Gates explained that Microsoft benefitted because “most of our competitors were very poorly run”.
“They did not understand how to bring in people with business experience and people with engineering experience and put them together. They did not understand how to go around the world.”
New horizons
HAVE YOUR SAY He has made a machine that could have been a luxury item only for industrial use, accessible to all. M. Morgan, Ireland Send us your comments
Now 52, he still has boyish looks, but he is no longer the world’s richest man. He has been overtaken by the investor Warren Buffett and the Mexican telecom tycoon Carlos Slim.
But Mr Gates’ fortune is at the root of his decision to leave his day job and concentrate on his charitable organisation, the Bill and Melinda Gates Foundation.
He will remain as Microsoft’s chairman and work on special technology projects, but according to Mr Gates, great wealth brings great responsibility and his future work will include finding new vaccines and financing projects in the developing world.
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Ciao darwin
June 28th, 2008 by finalchildren
Flashback!! Ciao Darwin!
i not in any degree posted this!! straight after the birdsville track. maree lake eyre, definitely more water in it now, innit! wilpena pulse wilpena pound is a beautiful part of the flinders ranges national estate. we rode not quite 400km around this place, all on dirt roads. saw some surprising scenery and had a great steak at a minute cafe on the highway. riding …
Current Mood
nervous. luckily, my loving boyfriend keeps me grounded with ms greasepaint illustrations like this: mille grazie, matteo. i’m in truth surprised that i didn’t obtain this picture much earlier on our journey.
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Katie stam
June 23rd, 2008 by finalchildren
New Vampire Weekend Video - “Oxford Comma”
Those Columbia boys’ third and highest-charting single enjoyed its video premiere Friday as part of Pete Wentz’s way-to-save-MTV project, FNMTV - which kind of reminds me of SNICK … remember how cool SNICK was? … Anyway! I never quite got this song - mainly what the oxford comma has to do with butlers, chapstick, Lil Jon or relationships in general. (P.S. I don’t believe in the oxford comma - but I guess they don’t care, right?)
People love Vampire Weekend and will probably dig this one-take farmland-turned-retro movie-set music video, but I really can’t count myself as a fan of theirs. While I liked “A Punk” better than “Oxford,” Vampire’s sound is kind of dull and not compelling for me … just me?
Watch an MTV.com behind-the-scenes of the “Oxford Comma” video - along with the music video for “A Punk” - after the jump…
Ezra Koenig on the movie-inspired video
and the music video for “a punk”
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(Reuters)
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Valpak
June 21st, 2008 by finalchildren
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