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Wolfram Promises Computing That Answers Questions
An anonymous reader writes "Computer scientist Stephen Wolfram feels that he has put together at least the initial version of a computer that actually answers factual questions, a la Star Trek's ship computers. His version will be found on their Web-based application, Wolfram Alpha. What does this mean? Well, instead of returning links to pages that may (or may not) contain the answer to your questions, Wolfram will respond with the actual answer. Just imagine typing in 'How many bones are in the human body?' and getting the answer." Right now, though the search entry field is in place, Alpha is not yet generally available -- only "to a few select individuals."
...they only give you answers.
is the answer to this question "no"?
If you want to answer a question without understanding the question then how do you know when the question can be answered?
Some drink at the fountain of knowledge. Others just gargle.
Good points, but this is still just a different (better perhaps?) implementation of the same concept. The big issue with the implementation is that it will only "know" what you tell it, the same as any other computer. Further it will only be able to tell you about what you want to know based on the system's ability to parse your question and return what it "thinks" you want to know.
Look, I'm not saying it isn't a cool idea, I'm just saying that it isn't as shiny and new as the creator would lead you to believe. I'm also not inclined to be impressed considering that it isn't even available to try yet. It hasn't even been released yet.
God, schmod. I want my monkey man!
As long as they are not showing the tool to the public, I do not believe they build a system which promises that. However, there have been lots of research in this area and there are methods to convert queries into horn-clauses so you can query knowledge bases. I designed a method in my master thesis which does similar things, however it was laid out to be performed by humans.
As ingredients for such a system you need
- a knowledge base filled with facts (you can use OWL for it if you want or a rule based approach)
- a reasoner (e.g. something like pellet)
- a rule engine (e.g. something like Jess)
- a method which understands simple English query sentences.
The really hard part is the knowledge base, because it is lots of work. And an automated approach which can understand written documents and classify them correctly would be great, but I doubt that they found a solution for this problem.
This problem includes:
- How to handle uncertainty?
- What to do with contradicting knowledge?
- What to do with temporal aspects in that knowledge?
However, if they built a tool which can answer question of one single domain of knowledge, this is nothing new. Such machines exist now for a long time. They can be helpful, but there is nothing exciting about them.
Atomic mass of plutonium?
Circumference of the earth?
Number of horns on a unicorn?
Google already does this. It's giving you the answer and linking to the page that has it. All Google needs is to be able to use these things in the calculator ("circumference of the earth in furlongs").
Oh and related to your "rupees in a dollar". "1 dollar in indian rupees" will tell you.
Don't sweat it ... these are the same people who believe that a computer can "think" about chess, instead of just searching through N number of plies in T time, then offering the best solution it has found in those constraints, without ever having to "understand" chess on any level.
This can be applied to ANY problem, provided you want to invest the design and testing time.
This whole question was answered decades ago (1970s) with the "foreigner in a sealed room" turing thought experiment. It showed that the person in the sealed room doesn't have to understand english, or even know the answer to questions, provided they are given some simple rules to link words together in a response depending on what words are in the original statement.
Who says that this is insufficient for "thinking"?
I think understanding the Chinese room paradox as having provided a solution to this question is a misinterpretation. The best thing to take away is that "thinking" is not well defined.