One of my experiments was to use the Wikipedia random page feature to
help me come up with good questions. I write a question that is
answered in the first paragraph. Usually it is on some very obscure
topic, so the question is one that very few people could answer
correctly. Then I enter the question into Google. About half of the
time, the top link is the same web page, but there are many cases
where it finds a different page that answers the question. About
10-20% of the time, Google fails to answer the question, but that is a
much lower error rate than a human would make.

Another test is to search for unusual items like "blue banana", "dog
smoking a pipe", or "flying clock". In my quick test, it came up with
relevant images every time.


On Mon, Oct 28, 2013 at 4:07 PM, Jim Bromer <[email protected]> wrote:
> Matt said:
> OK, how about this. Make up a list of 20 questions that you think an
> AGI ought to be able to answer. Next, mark the ones you think that
> Google will be able to answer. Then try it and see which ones it
> actually does. Then post the results of your experiment.
> -------------
>
>
> That is relevant to my plan to create a simple AGI program that would
> be able to learn through text-based IO, but those are not examples of
> an AGI program that is able to learn.  I acknowledge that this idea of
> pushing the goal posts further away for every advancement is nonsense,
> but my whole point is that I believe that it is feasible to write a
> -very simple- AGI program that is able to *genuinely learn* using a
> -simple- context sensitive language (with some typeIV moments).
>
> I just tried a few questions on Google and the best answers just about
> contained the words in my question exactly.  That suggests that a
> context-free association phrase-to-phrase followed by a simple
> context-sensitive decomposition and a slight bias for more
> authoritative links really can do some of the legwork if the database
> is extensive enough.  But that initial collection is not good enough
> for AGI. You would want an AGI program to examine the links to see if
> they are actually relevant and helpful.
>
> But I especially did not notice that Google was learning by having a
> conversation with me.  That has always been one of the goals of AI
> from Turing on.  I am not moving the goal posts, I seem to be
> explaining to people how the game is supposed to be played.  The only
> real question is whether I will actually be able to compete in the
> field. But I am starting to think that competition in this game is 1%
> inspiration and 99% coding.
>
> Jim Bromer
>
> On Mon, Oct 28, 2013 at 2:29 PM, Matt Mahoney <[email protected]> wrote:
>> On Mon, Oct 28, 2013 at 1:22 PM, Jim Bromer <[email protected]> wrote:
>>> How many tablespoons in a cubic parsec is a quite amusing and
>>> unexpected question to have been solved.  But wait a minute... Isn't
>>> that a calculator question?  If you are trying to awe and scare me
>>> with this Halloween factoid, it is not going to work.
>>
>> OK, how about this. Make up a list of 20 questions that you think an
>> AGI ought to be able to answer. Next, mark the ones you think that
>> Google will be able to answer. Then try it and see which ones it
>> actually does. Then post the results of your experiment.
>>
>> --
>> -- Matt Mahoney, [email protected]
>>
>>
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>
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-- 
-- Matt Mahoney, [email protected]


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