Wolfram Alpha: Next major search breakthrough?
(Credit:
Wolfram Research)
Stephen Wolfram has a track record of scientific breakthroughs and some controversy. He received his Ph.D. in theoretical physics from Caltech in 1979 when he was 20 and has focused most of his career on probing complex systems. In 1988 he launched Mathematica, powerful computational software that has become the gold standard in its field. In 2002, Wolfram produced a 1,280-page tome, A New Kind of Science, based on a decade of exploration in cellular automata and complex systems. The book stirred up a lot of debate in scientific circles. Legendary physicist Freeman Dyson described the tome as "a case of style over substance." (See Steven Levy's Wired profile of Wolfram).
In May, Wolfram will unveil his latest creation, now called Wolfram Alpha. It applies his work with Mathematica and NKS (A New Kind of Science) to Web search. "All one needs to be able to do is to take questions people ask in natural language, and represent them in a precise form that fits into the computations one can do," Wolfram said in a recent blog post. "I'm happy to say that with a mixture of many clever algorithms and heuristics, lots of linguistic discovery and linguistic curation, and what probably amount to some serious theoretical breakthroughs, we're actually managing to make it work...It's going to be a website: www.wolframalpha.com. With one simple input field that gives access to a huge system, with trillions of pieces of curated data and millions of lines of algorithms," he added.
It follows the Google principle, with a simple input box, but takes a different approach to rendering search results. Nova Spivack, CEO of Radar Networks, which developed Twine, an ambitious "interest network" Web application based on semantic Web technologies, said that Wolfram Alpha may be as "important for the Web (and the world) as Google, but for a different purpose."
Spivack shared his initial impressions of Wolfram Alpha based on a two-hour conversation with Wolfram.
"Wolfram Alpha is like plugging into a vast electronic brain. It provides extremely impressive and thorough answers to a wide range of questions asked in many different ways, and it computes answers, it doesn't merely look them up in a big database."
"In this respect it is vastly smarter than (and different from) Google. Google simply retrieves documents based on keyword searches. Google doesn't understand the question or the answer, and doesn't compute answers based on models of various fields of human knowledge."
Spivack gave some insight as to how the Wolfram's search engine works:
Wolfram Alpha is a system for computing the answers to questions. To accomplish this it uses built-in models of fields of knowledge, complete with data and algorithms, that represent real-world knowledge.
For example, it contains formal models of much of what we know about science -- massive amounts of data about various physical laws and properties, as well as data about the physical world.
Based on this you can ask it scientific questions and it can compute the answers for you. Even if it has not been programmed explicity to answer each question you might ask it.
But science is just one of the domains it knows about--it also knows about technology, geography, weather, cooking, business, travel, people, music, and more.
It also has a natural language interface for asking it questions. This interface allows you to ask questions in plain language, or even in various forms of abbreviated notation, and then provides detailed answers.
The vision seems to be to create a system which can do for formal knowledge (all the formally definable systems, heuristics, algorithms, rules, methods, theorems, and facts in the world) what search engines have done for informal knowledge (all the text and documents in various forms of media).
Wolfram's engine isn't going to replace Google, according to Spivack, although he suggests Google would like to own it.
"You would probably not use Wolfram Alpha to shop for a new car, find blog posts about a topic, or to choose a resort for your honeymoon. It is not a system that will understand the nuances of what you consider to be the perfect romantic getaway, for example--there is still no substitute for manual human-guided search for that. Where it appears to excel is when you want facts about something, or when you need to compute a factual answer to some set of questions about factual data."
For now, we'll have to wait until May to see whether the Web and scientific worlds embrace Wolfram's Alpha as a major mathematical and engineering breakthrough.
Read Nova Spivack's "Wolfram Alpha is Coming -- and It Could be as Important as Google"
See also: VentureBeat: Wolfram Alpha -- it's like plugging into an electronic brain
Dan Farber is editor in chief of CBS Interactive News, which includes CBSNews.com and CNET News. He has more than 25 years of experience as an editor and journalist covering technology. E-mail Dan. 





Google has fought tooth-and-nail AGAINST natural language input, usually citing "unnecessary noise words!" Instead, we have the tail wagging the dog, actually changing the way we use language today. More and more, people are speaking in indecipherable keywords, instead of in real sentences and paragraphs. I believe this is a direct result of our dependence on Google, and so we have the Googlization of language. It is a sad development, and perhaps we can start to reverse the trend..
You lost me with the whole "people talking in keywords" thing, though. I am a software developer with kids... I've seen txt msg speak, but I've never heard people verbalize google interrogatives like, "Angelina Jolie kids" or "tainted peanuts products"... What did you mean, exactly?
Surely Mr Spivack has got it wrong. Google has an implicit model of human knowledge - links represent human judgements about semantic relationships.
There really does need to be a better way to get a useful answer.
Hope this one helps.
remember gopher?
worked well when most people on the 'net were computer science professionals.
Didn't need an AltaVista or a Google until the brainless masses found the net through AOL and the WWW.
The valid_info to noise ratio is ever widening.
Just coming up with an answer by analyzing the question instead of searching for one seems like a good idea to me.
So what are the medium/long term possibilities? How will it affect the way people start to think? Is it another brick in the wall of artificial intelligence? Are these thingds good?
It's an interesting world
But this could be really amazing. If I were a VC, I'd be on the phone.
I just asked it a question "what is 4 x 5?" and it answered straight away "20" but it choked on "what is 3 plus 9 x 2" but only because it lacks the semantic equivalence of "plus" to the "+" which I can provide (but it is a pain to do so)
I asked trueknowledge another question just now "where was barak obama born?" and the result, "honolulu, hawaii" straight away. More impressive "What is the closest planet to Earth?" , return "Venus". It has gotten smarter since the last time I used it a few months ago, I signed up for the private beta over a year ago and it couldn't answer the "planet" question then. Note how that question requires the system to know what "closest" means in the context of this sentence! very impressive. I switched the question to "what planet is closest to Earth?" and again "Venus" and then finally I asked "Is Venus bigger than Mars?" to which it returned "I don't know" at which point after telling it the answer was "yes" It was then able to answer the question correctly as "yes". Again the learning process (which spanned several pages) is the hump that these systems must get over to become really efficient. TN has been in beta for over a year! I will be interested to see how Wolfram's service compares in its initial beta.
Lets say you want to know how strong the TV signal is in a valley. First you figure out the domain which in this case is radio waves and transmission. Youget the relevant input like radio tower locations and terrain but then you dont use Maxwells Equations you use the fact that space is 3 dimensional and that something must spread from here to there. You include the terrain in the model and calculate and calculate and drop lower order terms.
So we can think of the stack the normal way we deal with stuff as:
1)Ideas
2)Language
3)Physics and Empirically Observed Results (Theory)
4)Math
5)Cellular Automata of the Universe
Wolfram Alfa seems to cutout the middle and deal with it this way:
1)Ideas
2)Language
3)Cellular Automata of the Universe
I've summarized some of this at: <a href="http://isontech.blogspot.com/2009/03/wolfram-alfa-search-engine.html"> http://isontech.blogspot.com/2009/03/wolfram-alfa-search-engine.html</a>
- by gabrielweinberg March 21, 2009 9:57 AM PDT
- Hey, also be sure to check out our new search engine, Duck Duck Go: http://www.duckduckgo.com/. We also have some semantic properties, e.g. ambigious keyword detection: http://www.duckduckgo.com/?q=apple, as well as have zero-click info, e.g. http://duckduckgo.com/?q=Futurama.
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Showing 1 of 2 pages (30 Comments)Take care,
Gabriel Weinberg
Founder & CEO, Duck Duck Go