To compute whatever can be computed about the world: Wolfram Alpha

Wolfram Alpha WA is a new search engine starting in May 2009 and which could be important for statistics.

Not really a search engine

But, in fact: ‘ Wolfram Alpha isn’t really a search engine, because we compute the answers, and we discover new truths. If anything, you might call it a platonic search engine, unearthing eternal truths that may never have been written down before.
Despite his disclaimer, Wolfram Alpha looks like a search engine, in that there’s a one-line box where you type in a question. The output appears a second or two later, as a page of text and graphics below the box. What’s happening behind the scenes? Rather than looking up the answer to your question, Wolfram Alpha figures out what your question means, looks up the necessary data to answer your question, computes an answer, designs a page to present the answer in a pleasing way, and sends the page back to your computer.’ And Wolfram Alpha is about how we might build the edifice of human knowledge from simple primitive computational rules. In a general way, the NKS (A New Kind of Science NKS is a book from Stephen Wolfram, full text here: notion that everything is computable gave me the confidence to go ahead with Wolfram Alpha at all. It’s because of NKS that I’m willing to believe that we can find a computational model for every branch of science.’

These are the words of Stephen Wolfram. He has been talking with Rudy Rucker, the podcast is published in h+ Magazine .

Rudy Ruckers who wrote himself a book in the line of NKS adds some more remarks in h+ Magazine:

….  ‘As Wolfram Alpha comes into widespread use, Stephen believes “It will raise the level of scientific things that the average person can do. People will find that the world is more predictable than they might have expected. Just as running Google is like having a reference librarian to help you, running Wolfram Alpha will be like having a house scientist to consult for you.” ‘
‘I wondered how Wolfram Alpha compares to the so-called Semantic Web – an intelligent web project that’s been kicking around for several years now. “The problem with the Semantic Web is that the people who post the content are expected to apply the tags,” remarks Wolfram. “And the tagging system involves a complicated categorization of all the things that might exist – what philosophers call an ontology. Like any comprehensive world-system, the Semantic Web ontology is subject to endless revision, with many gray areas. For instance if there’s a cell phone antenna on a bridge girder, is the structure a bridge or a cell phone tower? It’s proved easier for us to hand-curate the existing data that we find in books and on the web. This is feasible because a lot of the data we’re interested in is purely scientific – things like the chemical formula of some compound. As this kind of data isn’t being constantly revised, it’s possible to stay ahead of the curve.”

Some pictures of WA

The namics blog shows some pictures of WA searches (comment in German)

Query „life expectancy age 45 ireland“

WA search result
WA search result

Stephen Wolfram talks at Harvard Law School, 28th of April 2009

‘WA is a ‘tremendously ambitious project. … Its goal is to find a way to make the systematic knowledge that we’ve accumulated in our civilization computable, to find a way to take a sort of all the data out there …. combine them … and make them computable … ‘

Stephen Wolfram at Harvard Law School April 2009
Stephen Wolfram at Harvard Law School April 2009

Some facts Stephen Wolfram was serching for in the talk at Harvard Law School:
GDP of France compared to Italy, internet users in europe, data about a certain location like Lexington Massachusets, materials like gold, medicine, stock performance, GDP versus railway length, president of Brazil in 1920, tide in New York at a particular time.

The ambition is to ‘reach a expert level knowledge with WA, making accessible expert level knowledge for everybody.

The 4 elements of WA are:

  1. Data curation: get data from everywhere, clean it up, make it computable in a automatic and partially human process. WA is keen to work with people from different areas to get data. The metadata, the ontology will be published, perhaps in RDF.
  2. Implementation of actual algorithms, methods and models, and put these Mathematica, the software under the hood. WA is based on Mathematica an earlier and very successful software from Stephen Wolfram.
  3. Lnguistic analysis to understand the questions. WA doesn’t use natural language processing, but the opposite: map the questions to the symbolic representations of the data in WA.
  4. Automate presentation of things like i.e. graphical data

See the video or listen to the podcast only.

Some links

Wolfram Alpha is coming by Stephen Wolfram on


It would be very interesting to see which statistical data this machine will compute and if the source will – as a matter of quality – be clearly stated.
The possibility to upload data and get them processed (API) is planned and can be used by everyone.

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