Joe Shirk's List: Semantic Web

• a "computational knowledge engine" for the Web
• 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
• it also knows about technology, geography, weather, cooking, business, travel, people, music
• Stephen showed me many interesting examples -- for example, Wolfram Alpha was able to solve novel numeric sequencing problems, calculus problems, and could answer questions about the human genome too. It was also able to compute answers to questions about many other kinds of topics (cooking, people, economics
• it computes them using at least some level of domain understanding and reasoning, plus vast amounts of data about the topic being asked about
• Where Google is a system for FINDING things that we as a civilization collectively publish, Wolfram Alpha is for COMPUTING answers to questions about what we as a civilization collectively know
• The services that are probably going to be most threatened by a service like Wolfram Alpha are the Wikipedia, Cyc, Metaweb's Freebase, True Knowledge, the START Project, and natural language search engines
• Twine.com, is NOT trying to do what Wolfram Alpha is trying to do, fortunately. Instead, Twine uses the Semantic Web to help people filter the Web, organize knowledge, and track their interests
• it would be far too difficult to try to explicitly represent everything Wolfram Alpha knows and can compute using OWL ontologies and the reasoning that they enable
• OpenCyc (which has taken decades to build up a very broad knowledge base of common sense knowledge and reasoning heuristics), Wolfram Alpha is also a centrally hand-curated system
• The scientific and philosophical underpinnings of Wolfram Alpha are similar to those of the cellular automata systems he describes in his book, "A New Kind of Science" (NKS)
• One of the observations of NKS is that incredibly rich, even unpredictable patterns, can be generated from tiny sets of simple rules and data, when they are applied to their own output over and over again
• cellular automata, by using just a few simple repetitive rules, can compute anything any computer or computer program can compute
• The simplicity and elegance of cellular automata proves that anything that may be computed -- and potentially anything that may exist in nature -- can be generated from very simple building blocks and rules that interact locally with one another
• cellular automata is not a reductionist approach to science -- in fact, it is much more focused on synthesizing complex emergent behaviors from simple elements than in reducing complexity back to simple units
• Wolfram has created a set of building blocks for working with formal knowledge to generate useful computations, and in turn, by putting these computations together you can answer even more sophisticated questions and so on. It's a system for synthesizing sophisticated computations from simple computations
• TrueKnowledge, based in the UK. A summary of their technology is here: http://www.trueknowledge.com/technology/
• a list of tricky questions to ask Wolfram Alpha when it goes public (such as How many krill do whales eat per hour? Why did Apollo XIII fail to land on the moon?) but I thought I would try some easier ones on True Knowledge. I am disappointed to say that it failed with all of them.
  • Who was pope in 1066? (understood the question perfectly. didn't know the answer though)
  • How many times has Madonna wed? (thought "has madonna wed" was an intransitive verb)
  • How many goals did Pele score in his career? (couldn't parse the question)
  • How many people died in the Black Death? (couldn't parse the question)
  • How many cannons were on the Mary Rose when she sank? (couldn't parse the question)

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• Wolfram explains that the engine is built on two fundamental stepping stones: his works Mathematica and A New Kind of Science:

   

  With Mathematica, I had a symbolic language to represent anything—as well as the algorithmic power to do any kind of computation. And with NKS, I had a paradigm for understanding how all sorts of complexity could arise from simple rules. But what about all the actual knowledge that we as humans have accumulated?

   

  But if one’s already made knowledge computable, one doesn’t need to do that kind of natural language understanding. 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…I wasn’t at all sure it was going to work. But 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.
• the engine is not built using standard semantic web languages such as RDF, OWL and Sparql

• Alpha is a computational engine able to draw on terabytes of curated data and synthesize it into entirely new combinations and presentations. The stock of systematic, structured data in the world is vast, but finite, and the efficient processes developed for Wolfram|Alpha have allowed us to make real progress towards the goal of incorporating all of it
• the “higher purpose” of this project, is to make all computable, factual knowledge available to everyone. What Wolfram|Alpha does is compute on top of those facts—answering questions, solving equations, providing insights, projecting future behaviors, and more

• the goal of Alpha is to give everyone access to expert knowledge and the data that a specialist would be able to compute from this information
• Alpha is built around a vast repository of curated data from public and licensed sources. Alpha then organizes and computes this knowledge with the help of sophisticated Natural Language Processing algorithms. Users can ask Alpha any kind of question
• Where Alpha exceeds, is in the presentation of its "search" results. When asked for how many internet users there are in Europe, for example, Alpha returned not just the total number, but also various plots and data for every country (apparently Vatican City only has 93 Internet users)
• Another query with a very sophisticated result was "uncle's uncle's brother's son." Now if you type that into Google, the result will be a useless list of sites that don't even answer this specific question, but Alpha actually returns an interactive genealogic tree with additional information, including data about the 'blood relationship fraction,' for example (3.125% in this case)
• Alpha is built on top of 5 million lines of Mathematica code which currently run on top of about 10,000 CPUs
• Mathematica, however, will also be one of the first programs to make use of the Alpha API, so that Mathematica users will be able to access Alpha's repository of data.
• Alpha also has a sophisticated knowledge of physics and chemistry data
• nutritional information, weather, and census data
• eal-time financial data or weather information

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• Wolfram Alpha blends natural language, a new search model and an algorithm that takes all the data on the Web and makes it “computable.
• Wolfram and his team have built what he calls a “computational knowledge engine” for the Web. OK, so what does that really mean? Basically it means that you can ask it factual questions and it computes answers for you.
• Wolfram Alpha actually computes the answers to a wide range of questions — like questions that have factual answers such as “What country is Timbuktu in?” or “How many protons are in a hydrogen atom?” or “What is the average rainfall in Seattle this month?,” “What is the 300th digit of Pi?,” “where is the ISS?” or “When was GOOG worth more than $300?”

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