Stephen Wolfram generously gave me a two-hour demo of Wolfram Alpha last evening, and I was quite positively impressed. As he said, it's not AI, and not aiming to be, so it shouldn't be measured by contrasting it with HAL or Cyc but with Google or Yahoo. At its heart is a formal Mathematica representation. Its inference engine is basically a large number of individually hand-engineered scripts for tapping into data which he and his team have spent the last several years gathering and "curating". For example, he has assembled tables of historical financial information about countries' GDP's and about companies' stock prices. In a small number of cases, he also connects via API to third party information, but mostly for realtime data such as a current stock price or current temperature. Rather than connecting to and relying on the current or future Semantic Web, Alpha computes its answers primarily from his own curated data to the extent possible; he sees Alpha as the home for almost all the information it needs, and will use to answer users' queries.
In an important sense, Alpha is a logical extension of Mathematica: it extends the range of types of information for which significant power can be gained by manually, and exhaustively, enumerating a large set of cases: airplane designs, cities, currencies, etc. I.e., Alpha extends what Mathematica has done previously for things like chemical compounds, geometric surfaces, topological configurations, arithmetic series, trigonometric ratios, and equations. In the new cases, as Mathematica did in those abstract math cases, Alpha excels at not just retrieving the stored data but performing various appropriate numeric calculations on the data, and displaying the results in beautiful graphs and easily comprehended tables for the user.
The resulting mosaic covers a large portion of the space of queries that the average person might genuinely want to ask, in the course of their day. The interface is not exactly natural language, but can be treated by the user as though it were -- just as users of browsers can treat them as though they parsed sentences even though they don't. A better way to think of it is a DWIMM ("do what I might mean"), so if you type in something like "gdp France / Germany", it calculates and returns a graph of the relative fraction of France's annual GDP to Germany's GDP, over the last 30 years or so. If you just type in "gdp", it looks up your local host and (in my case) displays the GDP of the USA over the last 30 years, plus various pieces of information about what gross domestic product is, from a mathematical formula perspective but not from a semantic one. It does not have an ontology, so what it knows about, say, GDP, or population, or stock price, is no more nor less than the equations that involve that term. One vulnerability that this engenders in Alpha is that errors in the data may go unnoticed for a long time; a positive way of saying this is that one could align Alpha's terms to an ontology and knowledge base, and use it to catch some fraction of errors as outright implausible violations of basic knowledge (e.g., Miami's population dropping by exactly a factor a ten during the month of October, 2006.)
Another example of DWIMM occurs if you type in a complicated mathematical formula, sloppily, with run-on variables, parenthesis errors, typos, etc. In those cases, Alpha does a great job of guessing what you could possibly have meant by that, something close to what you typed in which would be a nontrivial graph, and displays that graph. If you type in a string of letters that's parsable only as a chemical compound, it assumes that you want information about that compound. If you type in IL where it expects a state, it will interpret that as Illinois; where it expects a country, it will interpret that as Israel.
For those who are familiar with and enamored by Mathematica's powerful theorem prover, it should be mentioned that that is, for the moment, turned off, for reasons having to do with computational cost -- i.e., response time -
Slashdot Mirror
Stephen Wolfram generously gave me a two-hour demo of Wolfram Alpha last evening, and I was quite positively impressed. As he said, it's not AI, and not aiming to be, so it shouldn't be measured by contrasting it with HAL or Cyc but with Google or Yahoo. At its heart is a formal Mathematica representation. Its inference engine is basically a large number of individually hand-engineered scripts for tapping into data which he and his team have spent the last several years gathering and "curating". For example, he has assembled tables of historical financial information about countries' GDP's and about companies' stock prices. In a small number of cases, he also connects via API to third party information, but mostly for realtime data such as a current stock price or current temperature. Rather than connecting to and relying on the current or future Semantic Web, Alpha computes its answers primarily from his own curated data to the extent possible; he sees Alpha as the home for almost all the information it needs, and will use to answer users' queries. In an important sense, Alpha is a logical extension of Mathematica: it extends the range of types of information for which significant power can be gained by manually, and exhaustively, enumerating a large set of cases: airplane designs, cities, currencies, etc. I.e., Alpha extends what Mathematica has done previously for things like chemical compounds, geometric surfaces, topological configurations, arithmetic series, trigonometric ratios, and equations. In the new cases, as Mathematica did in those abstract math cases, Alpha excels at not just retrieving the stored data but performing various appropriate numeric calculations on the data, and displaying the results in beautiful graphs and easily comprehended tables for the user. The resulting mosaic covers a large portion of the space of queries that the average person might genuinely want to ask, in the course of their day. The interface is not exactly natural language, but can be treated by the user as though it were -- just as users of browsers can treat them as though they parsed sentences even though they don't. A better way to think of it is a DWIMM ("do what I might mean"), so if you type in something like "gdp France / Germany", it calculates and returns a graph of the relative fraction of France's annual GDP to Germany's GDP, over the last 30 years or so. If you just type in "gdp", it looks up your local host and (in my case) displays the GDP of the USA over the last 30 years, plus various pieces of information about what gross domestic product is, from a mathematical formula perspective but not from a semantic one. It does not have an ontology, so what it knows about, say, GDP, or population, or stock price, is no more nor less than the equations that involve that term. One vulnerability that this engenders in Alpha is that errors in the data may go unnoticed for a long time; a positive way of saying this is that one could align Alpha's terms to an ontology and knowledge base, and use it to catch some fraction of errors as outright implausible violations of basic knowledge (e.g., Miami's population dropping by exactly a factor a ten during the month of October, 2006.) Another example of DWIMM occurs if you type in a complicated mathematical formula, sloppily, with run-on variables, parenthesis errors, typos, etc. In those cases, Alpha does a great job of guessing what you could possibly have meant by that, something close to what you typed in which would be a nontrivial graph, and displays that graph. If you type in a string of letters that's parsable only as a chemical compound, it assumes that you want information about that compound. If you type in IL where it expects a state, it will interpret that as Illinois; where it expects a country, it will interpret that as Israel. For those who are familiar with and enamored by Mathematica's powerful theorem prover, it should be mentioned that that is, for the moment, turned off, for reasons having to do with computational cost -- i.e., response time -