OK Ben is then one step ahead of Forex. Point is time series analysis,
although it is narrow AI can be extremely powerful. The situation about "*
sentiment*" is different from that of Poker where there is a single
adversary bluffing. A time series analysis encompasses the *ensemble* of
different opinions. Statistical programs can model this accurately.

Ben presumably has techniques for mining the data about companies. The
difficulty, as I see it, of translating this into a stock exchange
prediction is the weighting of different factors. What in fact you will need
to complete the task is something like conjoint analysis.

We need, for example, to get an index for innovation. We can see
how important this is and how important other factors are by doing something
like conjoint analysis. Management will affect long term stock values. Forex
is concerned with day to day fluctuations where management performance
(except in terms of the manipulation of shares) is not important.

Conjoint analysis has been used by managements to indicate how they should
be managing. Ben should be able to tell managements how they can optimise
the value of their company based on historical data.

This is real AGI and there is a close tie up between prediction and how a
company should be managed. We know as a matter of historical record, for
example, that where you have to reduce a budget deficit you do it with 2
parts reduction in public expenditure and 1 part rise in taxation. The
Con/Lib Dem coalition is going for a 3:1 ratio. There will no double be
other things that will come out of data-mining.

Sorry no disrespect intended.

On 8 August 2010 18:09, Abram Demski <abramdem...@gmail.com> wrote:

> Ian,
>
> Be courteous-- Ben asked specifically that any arguments about which things
> are narrow-ai should start a separate topic.
>
> Yea, I did not intend to rule out any possible sources of information for
> the stock market prediction task. Ben has worked on a system which looked on
> the web for chatter about specific companies, for example.
>
> Even if it was just stock data being used, it wouldn't be just time-series
> analysis. It would at least be planning as well. Really, though, it includes
> acting with the behavior of potential adversaries in mind (like
> game-playing).
>
> Even if it *were* just time-series analysis, though, I think it would be a
> decent AGI application. That is because I think AGI technology should be
> good at time-series analysis! In my opinion, a good AGI learning algorithm
> should be useful for such tasks.
>
> So, yes, many of my examples could be attacked via narrow AI; but I think
> they would be handled *better* by AGI. That's why they are low-hanging
> fruit-- they are (hopefully) on the border.
>
> --Abram
>
> On Sun, Aug 8, 2010 at 11:58 AM, Ian Parker <ianpark...@gmail.com> wrote:
>
>> Just one point about Forex, your first entry. This is purely a time series
>> analysis as I understand it. It is narrow AI in fact. With AGI you would
>> expect interviews with the executives of listed companies, just as the big
>> investment houses do.
>>
>> AGI would be data mining of everything about a company as well as time
>> series analysis.
>>
>>
>>   - Ian Parker
>>
>> On 8 August 2010 02:35, Abram Demski <abramdem...@gmail.com> wrote:
>>
>>> Ben,
>>>
>>> -The oft-mentioned stock-market prediction;
>>> -data mining, especially for corporate data such as customer behavior,
>>> sales prediction, etc;
>>> -decision support systems;
>>> -personal assistants;
>>> -chatbots (think, an ipod that talks to you when you are lonely);
>>> -educational uses including human-like artificial teachers, but also
>>> including smart presentation-of-material software which decides what
>>> practice problem to ask you next, when to give tips, etc;
>>> -industrial design (engineering);
>>> ...
>>>
>>> Good luck to him!
>>>
>>> --Abram
>>>
>>> On Sat, Aug 7, 2010 at 9:10 PM, Ben Goertzel <b...@goertzel.org> wrote:
>>>
>>>> Hi,
>>>>
>>>> A fellow AGI researcher sent me this request, so I figured I'd throw it
>>>> out to you guys....
>>>>
>>>> ****
>>>> I'm putting together an AGI pitch for investors and thinking of low
>>>> hanging fruit applications to argue for. I'm intentionally not
>>>> involving any mechanics (robots, moving parts, etc.). I'm focusing on
>>>> voice (i.e. conversational agents) and perhaps vision-based systems.
>>>> Hellen Keller AGI, if you will :)
>>>>
>>>> Along those lines, I'd like any ideas you may have that would fall
>>>> under this description. I need to substantiate the case for such AGI
>>>> technology by making an argument for high-value apps. All ideas are
>>>> welcome.
>>>> ****
>>>>
>>>> All serious responses will be appreciated!!
>>>>
>>>> Also, I would be grateful if we
>>>> could keep this thread closely focused on direct answers to this
>>>> question, rather than
>>>> digressive discussions on Helen Keller, the nature of AGI, the
>>>> definition of AGI
>>>> versus narrow AI, the achievability or unachievability of AGI, etc.
>>>> etc.  If you think
>>>> the question is bad or meaningless or unclear or whatever, that's
>>>> fine, but please
>>>> start a new thread with a different subject line to make your point.
>>>>
>>>> If the discussion is useful, my intention is to mine the answers into a
>>>> compact
>>>> list to convey to him
>>>>
>>>> Thanks!
>>>> Ben G
>>>>
>>>>
>>>> -------------------------------------------
>>>> agi
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>>>
>>>
>>>
>>> --
>>> Abram Demski
>>> http://lo-tho.blogspot.com/
>>> http://groups.google.com/group/one-logic
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>
>
> --
> Abram Demski
> http://lo-tho.blogspot.com/
> http://groups.google.com/group/one-logic
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