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Re: The Lisp Curse

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  Re: The Lisp Curse Mentifex <mentifex@myuw.net> - 2011-06-29 15:41 -0700
    Re: The Lisp Curse "Fuschia, President-Elect of the Bright Purplish-Green Council" <fp-eotbp-gc@ibm.com> - 2011-06-29 19:16 -0400
    Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-06-30 09:47 +0200
      Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-06-30 02:27 -0700
        Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-06-30 14:28 +0200
          Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-06-30 14:06 -0700
            Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-01 23:25 +0200
              Re: The Lisp Curse "Alf P. Steinbach /Usenet" <alf.p.steinbach+usenet@gmail.com> - 2011-07-02 00:32 +0200
                Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 09:49 +0200
                  Re: The Lisp Curse "Alf P. Steinbach /Usenet" <alf.p.steinbach+usenet@gmail.com> - 2011-07-02 12:23 +0200
                    Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 15:30 +0200
                      Re: The Lisp Curse "Alf P. Steinbach /Usenet" <alf.p.steinbach+usenet@gmail.com> - 2011-07-02 17:06 +0200
                        Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 18:09 +0200
                          Re: The Lisp Curse James Waldby <not@valid.invalid> - 2011-07-02 17:23 +0000
                            Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 20:50 +0200
                            Re: The Lisp Curse luser droog <mijoryx@yahoo.com> - 2011-07-17 22:14 -0700
                              Re: The Lisp Curse Ben Bacarisse <ben.usenet@bsb.me.uk> - 2011-07-18 14:10 +0100
                                Re: The Lisp Curse Willem <willem@toad.stack.nl> - 2011-07-18 14:13 +0000
                                  Re: The Lisp Curse Ben Bacarisse <ben.usenet@bsb.me.uk> - 2011-07-18 16:18 +0100
                          Re: The Lisp Curse "Alf P. Steinbach /Usenet" <alf.p.steinbach+usenet@gmail.com> - 2011-07-02 19:47 +0200
                            Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 20:56 +0200
                              Re: The Lisp Curse "Alf P. Steinbach /Usenet" <alf.p.steinbach+usenet@gmail.com> - 2011-07-02 23:01 +0200
                                Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-03 10:45 +0200
                        Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-07-02 10:00 -0700
                      Re: The Lisp Curse luser droog <mijoryx@yahoo.com> - 2011-07-17 04:09 -0700
                  Re: The Lisp Curse "James" <no@spam.invalid> - 2011-07-03 12:06 -0700
              Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-07-01 21:22 -0700
                Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 09:47 +0200
                  Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-07-02 02:10 -0700
                    Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 15:29 +0200
                      Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-07-02 10:03 -0700
                        Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-02 20:47 +0200
                          Re: The Lisp Curse BGB <cr88192@hotmail.com> - 2011-07-02 20:29 -0700
                            Re: The Lisp Curse "Dmitry A. Kazakov" <mailbox@dmitry-kazakov.de> - 2011-07-03 10:53 +0200
                  Re: The Lisp Curse tm <thomas.mertes@gmx.at> - 2011-07-03 23:42 -0700
          Re: The Lisp Curse Fritz Wuehler <fritz@spamexpire-201107.rodent.frell.theremailer.net> - 2011-07-03 14:40 +0200

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#553 — Re: The Lisp Curse

On Jun 26, 1:13 pm, Andrew Haley <andre...@littlepinkcloud.invalid>
wrote:
> This is interesting, although I'm not sure I agree with all of it:
>
> http://www.winestockwebdesign.com/Essays/Lisp_Curse.html
>
> "Imagine adding object orientation to the C and Scheme programming
> languages. Making Scheme object-oriented is a sophomore homework
> assignment. On the other hand, adding object orientation to C requires
> the programming chops of Bjarne Stroustrup.
>
> "The consequences of this divergence in needed talent and effort cause
> The Lisp Curse:
>
> "Lisp is so powerful that problems which are technical issues in other
> programming languages are social issues in Lisp."
>
> Andrew.

Lisp is good for list processing,
but Forth is best for AI.

Mentifex
--
http://cyborg.blogspot.com
http://mind.sourceforge.net/lisp.html
http://www.scn.org/~mentifex/AiMind.html
http://www.tfeb.org/lisp/mad-people.html

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#554

On 29/06/2011 6:41 PM, Mentifex wrote:
> On Jun 26, 1:13 pm, Andrew Haley<andre...@littlepinkcloud.invalid>
> wrote:
>> http://www.winestockwebdesign.com/Essays/Lisp_Curse.html
>
> Lisp is good for list processing,
> but Forth is best for AI.

What does your classic unsubstantiated and erroneous claim have to do 
with web design, Mentifex?

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#556

On Wed, 29 Jun 2011 15:41:01 -0700 (PDT), Mentifex wrote:

> On Jun 26, 1:13 pm, Andrew Haley <andre...@littlepinkcloud.invalid>
> wrote:
>> This is interesting, although I'm not sure I agree with all of it:
>>
>> http://www.winestockwebdesign.com/Essays/Lisp_Curse.html
>>
>> "Imagine adding object orientation to the C and Scheme programming
>> languages. Making Scheme object-oriented is a sophomore homework
>> assignment. On the other hand, adding object orientation to C requires
>> the programming chops of Bjarne Stroustrup.
>>
>> "The consequences of this divergence in needed talent and effort cause
>> The Lisp Curse:
>>
>> "Lisp is so powerful that problems which are technical issues in other
>> programming languages are social issues in Lisp."
> 
> Lisp is good for list processing,
> but Forth is best for AI.

Forth is best for forth processing.

I doubt that any low-level language can be actually useful for AI. Same is 
true for domain-specific languages (e.g. Prolog, MatLab, LabView).

I know that both branches of languages are popular there, but that is 
largely because people doing AI are mostly researchers, who do not care 
about (aware of?) software engineering, not due to the merits of these 
languages. The AI software rarely reaches the level of an industrial 
product. Or putting it otherwise, once it does, it is no more considered 
AI.

Actually for AI strong elaborated typing and early error detection is more 
important than tight change-try cycles and no upfront design. Normally 
there is no way to debug an AI application (inference engine, pattern 
matcher, image processing unit), because of the number of states, the 
amount of computations, real-time constraints. (Considering something 
beyond  one-man experiments of course) And when it comes to performance and 
putting the stuff into a small embedded target, then you bet.

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#559

On 6/30/2011 12:47 AM, Dmitry A. Kazakov wrote:
> On Wed, 29 Jun 2011 15:41:01 -0700 (PDT), Mentifex wrote:
>
>> On Jun 26, 1:13 pm, Andrew Haley<andre...@littlepinkcloud.invalid>
>> wrote:
>>> This is interesting, although I'm not sure I agree with all of it:
>>>
>>> http://www.winestockwebdesign.com/Essays/Lisp_Curse.html
>>>
>>> "Imagine adding object orientation to the C and Scheme programming
>>> languages. Making Scheme object-oriented is a sophomore homework
>>> assignment. On the other hand, adding object orientation to C requires
>>> the programming chops of Bjarne Stroustrup.
>>>
>>> "The consequences of this divergence in needed talent and effort cause
>>> The Lisp Curse:
>>>
>>> "Lisp is so powerful that problems which are technical issues in other
>>> programming languages are social issues in Lisp."
>>
>> Lisp is good for list processing,
>> but Forth is best for AI.
>
> Forth is best for forth processing.
>
> I doubt that any low-level language can be actually useful for AI. Same is
> true for domain-specific languages (e.g. Prolog, MatLab, LabView).
>
> I know that both branches of languages are popular there, but that is
> largely because people doing AI are mostly researchers, who do not care
> about (aware of?) software engineering, not due to the merits of these
> languages. The AI software rarely reaches the level of an industrial
> product. Or putting it otherwise, once it does, it is no more considered
> AI.
>
> Actually for AI strong elaborated typing and early error detection is more
> important than tight change-try cycles and no upfront design. Normally
> there is no way to debug an AI application (inference engine, pattern
> matcher, image processing unit), because of the number of states, the
> amount of computations, real-time constraints. (Considering something
> beyond  one-man experiments of course) And when it comes to performance and
> putting the stuff into a small embedded target, then you bet.
>

and some of us don't believe in strong-AI either...

rather, one can make any number of weak-AIs, which mimic various aspects 
of intelligence, or mimic intelligent agents (for example, game AIs, 
which are usually called AIs, but in effect are typically little more 
than some mass of procedural logic and hard-coded behaviors).

it is very well possible that "intelligence" (in a strong/human-like 
sense) can't exist on what we would currently understand as computers 
(and the best that could be done is to create an elaborate mimicry).

not that I believe the above is necessarily bad, or that weak AIs are 
not useful...

for example, I have messed with both neural nets and genetic 
programming, and although I haven't personally found much use for them 
(mostly for performance reasons), they are still potentially useful ideas.

some of my code also contains algorithms that could be loosely termed as 
AI (generally data-driven heuristics-based algorithms), but really in a 
practical sense is nothing terribly special about them (in any real 
sense more than invoking "Google" or an SQL query is "intelligent"...).


I also don't believe (WRT programming languages) that "good for AI" is 
necessarily different for "good for programming in general". whether or 
not one can effectively write real software in a language is its main 
merit, and a language that isn't very good for writing software, well, 
it has a problem...

hence, it is very well possible that the AI game could be "won" using 
apps consisting of C, C++, and/or Java or C#...


the best mimic one will likely get is likely to be a program that is 
both absurdly complicated, likely horridly kludged together, and has 
managed to manifest basic learning and logical reasoning abilities (say, 
for example, it can adapt is behavior via neural nets and genetic programs).

such a mimic, which is likely to probably have superior abilities in 
some areas, and fall on its face in others (like it can solve puzzles 
quickly, fetch trivia readily, and break-dance in a robot body, but 
can't reason through "common sense" problems, nor likely being truly 
aware of its own existence).

as for "magic" or "silver bullet" algorithms, very likely no such algos 
exist.


or such...

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#560

On Thu, 30 Jun 2011 02:27:42 -0700, BGB wrote:

> On 6/30/2011 12:47 AM, Dmitry A. Kazakov wrote:
>> On Wed, 29 Jun 2011 15:41:01 -0700 (PDT), Mentifex wrote:
>>
>>> On Jun 26, 1:13 pm, Andrew Haley<andre...@littlepinkcloud.invalid>
>>> wrote:
>>>> This is interesting, although I'm not sure I agree with all of it:
>>>>
>>>> http://www.winestockwebdesign.com/Essays/Lisp_Curse.html
>>>>
>>>> "Imagine adding object orientation to the C and Scheme programming
>>>> languages. Making Scheme object-oriented is a sophomore homework
>>>> assignment. On the other hand, adding object orientation to C requires
>>>> the programming chops of Bjarne Stroustrup.
>>>>
>>>> "The consequences of this divergence in needed talent and effort cause
>>>> The Lisp Curse:
>>>>
>>>> "Lisp is so powerful that problems which are technical issues in other
>>>> programming languages are social issues in Lisp."
>>>
>>> Lisp is good for list processing,
>>> but Forth is best for AI.
>>
>> Forth is best for forth processing.
>>
>> I doubt that any low-level language can be actually useful for AI. Same is
>> true for domain-specific languages (e.g. Prolog, MatLab, LabView).
>>
>> I know that both branches of languages are popular there, but that is
>> largely because people doing AI are mostly researchers, who do not care
>> about (aware of?) software engineering, not due to the merits of these
>> languages. The AI software rarely reaches the level of an industrial
>> product. Or putting it otherwise, once it does, it is no more considered
>> AI.
>>
>> Actually for AI strong elaborated typing and early error detection is more
>> important than tight change-try cycles and no upfront design. Normally
>> there is no way to debug an AI application (inference engine, pattern
>> matcher, image processing unit), because of the number of states, the
>> amount of computations, real-time constraints. (Considering something
>> beyond  one-man experiments of course) And when it comes to performance and
>> putting the stuff into a small embedded target, then you bet.
> 
> and some of us don't believe in strong-AI either...

Well, there is an old joke that if someone works on artificial
intelligence, that is because of a lack of the natural one...

> rather, one can make any number of weak-AIs, which mimic various aspects 
> of intelligence, or mimic intelligent agents (for example, game AIs, 
> which are usually called AIs, but in effect are typically little more 
> than some mass of procedural logic and hard-coded behaviors).

...and some consider intelligent agents a hoax...

BTW, talking about general intelligence there no AI comparable with the
intelligence of an ant. So the human level one is not even in question,
yet.

> it is very well possible that "intelligence" (in a strong/human-like 
> sense) can't exist on what we would currently understand as computers 
> (and the best that could be done is to create an elaborate mimicry).

Well, that is possible if the human brain would "sufficiently" rely on some
incomputable elements. Though nobody knows of course.

E.g. a clock (real time source) is an incomputable element, but a clock
widget indicating the time though indeed relies on it, does this in a way
"insufficient" to become itself incomputable.

> not that I believe the above is necessarily bad, or that weak AIs are 
> not useful...
> 
> for example, I have messed with both neural nets and genetic 
> programming, and although I haven't personally found much use for them 
> (mostly for performance reasons), they are still potentially useful ideas.

Because both are hoax, even more than the "swarm intelligence" is.

Neural networks are known since 50s under the name "perceptron". These
represent a class of linear classifiers which evidently cannot classify
even such simple patterns as two concentric circles. All intelligence they
possess is in the kernel, which is to linearize the problem and guess who
is responsible to find a working kernel?

Generic algorithms are also known since 50s (W.R. Ashby, if I correctly
remember). Their problem is that the intelligence is not in the random
mutations, but in the way it is decided if the mutation was good. This
cannot not work for the same reason the Darwin's "natural selection"
cannot. So the intelligence, if any, is hidden in the directed mutations.

> some of my code also contains algorithms that could be loosely termed as 
> AI (generally data-driven heuristics-based algorithms), but really in a 
> practical sense is nothing terribly special about them (in any real 
> sense more than invoking "Google" or an SQL query is "intelligent"...).

Yes, once the problem is solved it is no more considered AI. Presently AI
is a bin to put anything in, we are not sure how to deal with.

> I also don't believe (WRT programming languages) that "good for AI" is 
> necessarily different for "good for programming in general". whether or 
> not one can effectively write real software in a language is its main 
> merit, and a language that isn't very good for writing software, well, 
> it has a problem...

Absolutely.

> as for "magic" or "silver bullet" algorithms, very likely no such algos 
> exist.

Yes. Example: an intelligent human is unable to calculate sine with double
precision which almost any dumb processor easily can.

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#566

On 6/30/2011 5:28 AM, Dmitry A. Kazakov wrote:
> On Thu, 30 Jun 2011 02:27:42 -0700, BGB wrote:
>
>> On 6/30/2011 12:47 AM, Dmitry A. Kazakov wrote:
>>> On Wed, 29 Jun 2011 15:41:01 -0700 (PDT), Mentifex wrote:
>>>
>>>> On Jun 26, 1:13 pm, Andrew Haley<andre...@littlepinkcloud.invalid>
>>>> wrote:
>>>>> This is interesting, although I'm not sure I agree with all of it:
>>>>>
>>>>> http://www.winestockwebdesign.com/Essays/Lisp_Curse.html
>>>>>
>>>>> "Imagine adding object orientation to the C and Scheme programming
>>>>> languages. Making Scheme object-oriented is a sophomore homework
>>>>> assignment. On the other hand, adding object orientation to C requires
>>>>> the programming chops of Bjarne Stroustrup.
>>>>>
>>>>> "The consequences of this divergence in needed talent and effort cause
>>>>> The Lisp Curse:
>>>>>
>>>>> "Lisp is so powerful that problems which are technical issues in other
>>>>> programming languages are social issues in Lisp."
>>>>
>>>> Lisp is good for list processing,
>>>> but Forth is best for AI.
>>>
>>> Forth is best for forth processing.
>>>
>>> I doubt that any low-level language can be actually useful for AI. Same is
>>> true for domain-specific languages (e.g. Prolog, MatLab, LabView).
>>>
>>> I know that both branches of languages are popular there, but that is
>>> largely because people doing AI are mostly researchers, who do not care
>>> about (aware of?) software engineering, not due to the merits of these
>>> languages. The AI software rarely reaches the level of an industrial
>>> product. Or putting it otherwise, once it does, it is no more considered
>>> AI.
>>>
>>> Actually for AI strong elaborated typing and early error detection is more
>>> important than tight change-try cycles and no upfront design. Normally
>>> there is no way to debug an AI application (inference engine, pattern
>>> matcher, image processing unit), because of the number of states, the
>>> amount of computations, real-time constraints. (Considering something
>>> beyond  one-man experiments of course) And when it comes to performance and
>>> putting the stuff into a small embedded target, then you bet.
>>
>> and some of us don't believe in strong-AI either...
>
> Well, there is an old joke that if someone works on artificial
> intelligence, that is because of a lack of the natural one...
>

possibly, but there are uses for "AI" in the weak sense...


>> rather, one can make any number of weak-AIs, which mimic various aspects
>> of intelligence, or mimic intelligent agents (for example, game AIs,
>> which are usually called AIs, but in effect are typically little more
>> than some mass of procedural logic and hard-coded behaviors).
>
> ...and some consider intelligent agents a hoax...
>

well, it is only a "hoax" if one believes they are intended to represent 
true intelligence.

for example, game-AIs mostly serve the purpose of running around, 
getting shot, shooting back at the player, potentially providing limited 
interaction with the player, ...

and, in this sense, they work fairly well...

and, a "good" AI is one with pathfinding and which manages to do things 
like take cover and avoid running off ledges to their death (say, the 
player is across a gap and there is a trench with lava in between, a 
good AI will not run off the ledge and into the lava...).

adding speech-synthesis, and HMM-based dialogue generation (similar to a 
chat-bot or similar), and make them seem a little more natural, ...

some games partly ruin the effect by making the NPCs have very detailed 
scripted events, but as soon as the event ends, the NPCs resort to 
"stand-and-stare" statue-like behavior, which kind of ruins their 
portrayal of intelligence.


> BTW, talking about general intelligence there no AI comparable with the
> intelligence of an ant. So the human level one is not even in question,
> yet.
>

yes. as-noted, I don't personally believe in strong-AI, but I do believe 
in weak AI, namely, in the ability (via algorithms and/or procedural 
logic) to simulate some aspects of "intelligence".


>> it is very well possible that "intelligence" (in a strong/human-like
>> sense) can't exist on what we would currently understand as computers
>> (and the best that could be done is to create an elaborate mimicry).
>
> Well, that is possible if the human brain would "sufficiently" rely on some
> incomputable elements. Though nobody knows of course.
>
> E.g. a clock (real time source) is an incomputable element, but a clock
> widget indicating the time though indeed relies on it, does this in a way
> "insufficient" to become itself incomputable.
>

yep, hardware clocks...

similar goes for random-number generation, where one generally needs to 
rely on external properties of the system to effectively seed ones RNG.


>> not that I believe the above is necessarily bad, or that weak AIs are
>> not useful...
>>
>> for example, I have messed with both neural nets and genetic
>> programming, and although I haven't personally found much use for them
>> (mostly for performance reasons), they are still potentially useful ideas.
>
> Because both are hoax, even more than the "swarm intelligence" is.
>
> Neural networks are known since 50s under the name "perceptron". These
> represent a class of linear classifiers which evidently cannot classify
> even such simple patterns as two concentric circles. All intelligence they
> possess is in the kernel, which is to linearize the problem and guess who
> is responsible to find a working kernel?
>

they work acceptably as adaptive linear filters.
granted, one can have better results at lower overhead IME with matrix 
transforms (big-ass matrix multiplies, ...) and/or the use of direct 
statistical adaptation (say, one counts how many times X is true or 
false and calculates a probability of it being one or the other).


> Generic algorithms are also known since 50s (W.R. Ashby, if I correctly
> remember). Their problem is that the intelligence is not in the random
> mutations, but in the way it is decided if the mutation was good. This
> cannot not work for the same reason the Darwin's "natural selection"
> cannot. So the intelligence, if any, is hidden in the directed mutations.
>

I have had some luck using them for signal-filters, but they are 
generally unacceptably slow to adapt, and pale in comparison to just 
using ones' head to come up with a solution (goes much faster and 
doesn't require large numbers of generations...).

they could be useful in some cases of adaptive algorithms though, where 
the algorithm needs to adapt but for some reason a programmer can't just 
write out a good solution, and it is acceptable for adaptation to be 
really slow... personally I haven't come across any scenario like this 
though.


>> some of my code also contains algorithms that could be loosely termed as
>> AI (generally data-driven heuristics-based algorithms), but really in a
>> practical sense is nothing terribly special about them (in any real
>> sense more than invoking "Google" or an SQL query is "intelligent"...).
>
> Yes, once the problem is solved it is no more considered AI. Presently AI
> is a bin to put anything in, we are not sure how to deal with.
>

well, it depends...

game AIs are still called AIs despite being both a generally solved 
problem, and being fairly obviously not-really-intelligent...

in this case, it may just be AI in the sense of being anthropomorphic 
(say, controlling a human-like character) than it is its resemblance to 
actual intelligence (it is then glossed over that potentially far more 
"intelligent" algorithms are generally responsible for things like 
keeping the framerate up...).

it is like, when people think of "algorithm" they think of things like 
sorting numbers or storing and retrieving data, and when they think of 
"AI" they think of a 3D character wandering around in a scene and 
interacting with objects, despite there being little real fundamental 
difference between them.


>> I also don't believe (WRT programming languages) that "good for AI" is
>> necessarily different for "good for programming in general". whether or
>> not one can effectively write real software in a language is its main
>> merit, and a language that isn't very good for writing software, well,
>> it has a problem...
>
> Absolutely.
>

yep.


>> as for "magic" or "silver bullet" algorithms, very likely no such algos
>> exist.
>
> Yes. Example: an intelligent human is unable to calculate sine with double
> precision which almost any dumb processor easily can.
>

yep, humans suck at calculating things, and computers suck at doing 
human-like stuff...


it is worth noting that many AIs in fiction also inherit human-like 
thinking patterns and cognitive limitations, and many cybernetic races 
(such as the Borg), have behavioral patterns that wouldn't even really 
go over all that well in a 3D game.

next up will they claim that the Borg central plexus (or thinkule or 
whatever) is written in a mix of Fortran and COBOL?...


very possibly, by the time an AI reached human-like intelligences, it 
would also have absurdly huge computational and information-retrieval 
abilities (because at its core it would probably still be a 
computer...), and could likely not be "fooled" in any human-like manner 
(the traditional assumption of fooling AIs through word games or logic 
puzzles or riddles, causing them either to go berserk or freeze up...).

or such...

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#570

On Thu, 30 Jun 2011 14:06:26 -0700, BGB wrote:

> On 6/30/2011 5:28 AM, Dmitry A. Kazakov wrote:
>> On Thu, 30 Jun 2011 02:27:42 -0700, BGB wrote:
>>
>>> rather, one can make any number of weak-AIs, which mimic various aspects
>>> of intelligence, or mimic intelligent agents (for example, game AIs,
>>> which are usually called AIs, but in effect are typically little more
>>> than some mass of procedural logic and hard-coded behaviors).
>>
>> ...and some consider intelligent agents a hoax...
> 
> well, it is only a "hoax" if one believes they are intended to represent 
> true intelligence.

We don't know. If intelligence is computable there is no obvious reason why
computation cannot be distributed among thin agents, unless the algorithm
is violently coupled preventing parallelism. But distribution as such
contributes nothing to the algorithmic complexity.

Some SF authors believed that intelligence arise by itself from
computational power. That is rubbish, a not booted Intel Core i7 is no more
or less intelligent than a not booted Intel 8086. It is the software that
makes the play.

> for example, game-AIs mostly serve the purpose of running around, 
> getting shot, shooting back at the player, potentially providing limited 
> interaction with the player, ...
> 
> and, in this sense, they work fairly well...
> 
> and, a "good" AI is one with pathfinding and which manages to do things 
> like take cover and avoid running off ledges to their death (say, the 
> player is across a gap and there is a trench with lava in between, a 
> good AI will not run off the ledge and into the lava...).
> 
> adding speech-synthesis, and HMM-based dialogue generation (similar to a 
> chat-bot or similar), and make them seem a little more natural, ...
> 
> some games partly ruin the effect by making the NPCs have very detailed 
> scripted events, but as soon as the event ends, the NPCs resort to 
> "stand-and-stare" statue-like behavior, which kind of ruins their 
> portrayal of intelligence.

Huh, but this actually depends on whether we believe in the validness of
the Turing's test approach. Does an inability of the intelligent system
(us) to reveal another system's (AI) stupidity really characterize the
second system as intelligent? If you say, no, Turing was wrong, then I
would probably agree.

> they work acceptably as adaptive linear filters.

But general intelligence should be from a stronger class of methods than
that. This is why I consider NN as a hoax, i.e. an intended attempt to
deceive.

>> Generic algorithms are also known since 50s (W.R. Ashby, if I correctly
>> remember). Their problem is that the intelligence is not in the random
>> mutations, but in the way it is decided if the mutation was good. This
>> cannot not work for the same reason the Darwin's "natural selection"
>> cannot. So the intelligence, if any, is hidden in the directed mutations.
> 
> I have had some luck using them for signal-filters, but they are 
> generally unacceptably slow to adapt, and pale in comparison to just 
> using ones' head to come up with a solution (goes much faster and 
> doesn't require large numbers of generations...).
> 
> they could be useful in some cases of adaptive algorithms though, where 
> the algorithm needs to adapt but for some reason a programmer can't just 
> write out a good solution, and it is acceptable for adaptation to be 
> really slow... personally I haven't come across any scenario like this 
> though.

What about a recent hype: the XP (extreme programming) - a chaotic change
of the source in a hope to adapt to the customer requirements, which
haven't even been formulated.

The same problem here, there is no any guaranty that the process converges
at all. And even if it would, little could be said about the properties at
the convergence point.

>>> some of my code also contains algorithms that could be loosely termed as
>>> AI (generally data-driven heuristics-based algorithms), but really in a
>>> practical sense is nothing terribly special about them (in any real
>>> sense more than invoking "Google" or an SQL query is "intelligent"...).
>>
>> Yes, once the problem is solved it is no more considered AI. Presently AI
>> is a bin to put anything in, we are not sure how to deal with.
> 
> well, it depends...
> 
> game AIs are still called AIs despite being both a generally solved 
> problem, and being fairly obviously not-really-intelligent...

OK

>>> as for "magic" or "silver bullet" algorithms, very likely no such algos
>>> exist.
>>
>> Yes. Example: an intelligent human is unable to calculate sine with double
>> precision which almost any dumb processor easily can.
> 
> yep, humans suck at calculating things, and computers suck at doing 
> human-like stuff...

Actually it all was human-stuff before. Computers came later and shown
themselves better than humans in the areas now considered computer-like.

> very possibly, by the time an AI reached human-like intelligences, it 
> would also have absurdly huge computational and information-retrieval 
> abilities (because at its core it would probably still be a 
> computer...), and could likely not be "fooled" in any human-like manner 
> (the traditional assumption of fooling AIs through word games or logic 
> puzzles or riddles, causing them either to go berserk or freeze up...).

It is also possible that an ability to become fooled is a necessary part of
general intelligence.

Anyway, due to Gödel's incompleteness, there always should be a state of
"perplexity" in any inference system. It does not crash the human brain,
because we have multiple subsystems monitoring each other as
semi-independent agents. An AI system should be necessarily built
similarly.

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#571

* Dmitry A. Kazakov, on 01.07.2011 23:25:
>
> Some SF authors believed that intelligence arise by itself from
> computational power. That is rubbish, a not booted Intel Core i7 is no more
> or less intelligent than a not booted Intel 8086. It is the software that
> makes the play.

This argument is misrepresenting the folks who have proposed that. They have 
been talking about active systems. But like you I don't believe in the idea; 
it's just a far fetched notion that like tales of trolls represent fear.

On the other hand, computing power is necessary for intelligence, because it's 
necessary for quickly performing large associative searches (like set 
intersections) in an extremely large model of the external world.

Just to get an idea of what that means, put down a hypothesis of each neuron 
communicating 100 bytes per second on average. I dunno, perhaps it's just 1, it 
doesn't matter much. Assume, like, 1 trillion neurons in your brain. Then, 
what's going on there, is like 100 trillion bytes, or 10^11 bytes, being sent 
around per second. So for your PC you need a bus with that capacity, but as of 
2011 your PC's bus doesn't shuffle hundreds of trillions of bytes per second; 
it's more like just hundreds of millions... That's the VON NEUMANN BOTTLENECK, 
the result of extreme centralization: currently a factor of 1 million short.

And that translates to at least some years, probably a decade or two.

The programming doesn't matter much until the necessary computing power is 
there. I suspect that the power will be realized in one of two ways. Namely, 
either by massive parallelization of conventional hardware, thus avoiding the 
single super-fast bus, or by interfacing fast conventional computing hardware to 
biological systems and letting the latter do the "model" stuff.


Cheers & hth.,

- Alf

-- 
blog at <url: http://alfps.wordpress.com>

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#574

On Sat, 02 Jul 2011 00:32:56 +0200, Alf P. Steinbach /Usenet wrote:

> On the other hand, computing power is necessary for intelligence, because it's 
> necessary for quickly performing large associative searches (like set 
> intersections) in an extremely large model of the external world.
> 
> Just to get an idea of what that means, put down a hypothesis of each neuron 
> communicating 100 bytes per second on average. I dunno, perhaps it's just 1, it 
> doesn't matter much. Assume, like, 1 trillion neurons in your brain. Then, 
> what's going on there, is like 100 trillion bytes, or 10^11 bytes, being sent 
> around per second. So for your PC you need a bus with that capacity, but as of 
> 2011 your PC's bus doesn't shuffle hundreds of trillions of bytes per second; 
> it's more like just hundreds of millions... That's the VON NEUMANN BOTTLENECK, 
> the result of extreme centralization: currently a factor of 1 million short.
> 
> And that translates to at least some years, probably a decade or two.

I would not be so sure. I think that an average processor is far more
powerful (in the above terms) than a fly. (How many neurons has a fly?) So
far nobody was able to build anything even close to the "intelligence" of
an insect.

> The programming doesn't matter much until the necessary computing power is 
> there. I suspect that the power will be realized in one of two ways. Namely, 
> either by massive parallelization of conventional hardware, thus avoiding the 
> single super-fast bus,

This would not necessary increase the power. What it would do is to make it
more difficult to program and control. Systems distributed functionally
(as opposed to the redundant ones) are more vulnerable an less efficient
than the integrated ones.

> or by interfacing fast conventional computing hardware to 
> biological systems and letting the latter do the "model" stuff.

At least it could allow us to better understand the problem.

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#576

* Dmitry A. Kazakov, on 02.07.2011 09:49:
> On Sat, 02 Jul 2011 00:32:56 +0200, Alf P. Steinbach /Usenet wrote:
>
>> On the other hand, computing power is necessary for intelligence, because it's
>> necessary for quickly performing large associative searches (like set
>> intersections) in an extremely large model of the external world.
>>
>> Just to get an idea of what that means, put down a hypothesis of each neuron
>> communicating 100 bytes per second on average. I dunno, perhaps it's just 1, it
>> doesn't matter much. Assume, like, 1 trillion neurons in your brain. Then,
>> what's going on there, is like 100 trillion bytes, or 10^11 bytes, being sent
>> around per second. So for your PC you need a bus with that capacity, but as of
>> 2011 your PC's bus doesn't shuffle hundreds of trillions of bytes per second;
>> it's more like just hundreds of millions... That's the VON NEUMANN BOTTLENECK,
>> the result of extreme centralization: currently a factor of 1 million short.
>>
>> And that translates to at least some years, probably a decade or two.
>
> I would not be so sure.

As I read this you mean "I would not be so sure that AI will be achieved in a 
decade or two".

If that's what you mean then that's profoundly silly, arguing against an idiot's 
position that nobody's argued for.

But if you mean that you're not so sure that it will take that long, then why?


> I think that an average processor is far more
> powerful (in the above terms) than a fly. (How many neurons has a fly?) So
> far nobody was able to build anything even close to the "intelligence" of
> an insect.

Good point.

It would be a worthwhile goal to emulate the nervous system of a housefly, 
perhaps controlling a robot fly...

The fly's nervous system reportedly has only millions of neurons, but still 
seems to be "smarter and more complicated than any computer built so far", 
according to Ann-Shynn Chiang of the National Tsing Hua University in Taiwan, 
who did some breaktrough work on mapping a fly brain's neural net, published 
this February[1].


Cheers,

- Alf

Notes:
[1] <url: http://www.sciencedaily.com/releases/2010/12/101202124108.htm>

-- 
blog at <url: http://alfps.wordpress.com>

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#579

On Sat, 02 Jul 2011 12:23:35 +0200, Alf P. Steinbach /Usenet wrote:

> * Dmitry A. Kazakov, on 02.07.2011 09:49:
>> On Sat, 02 Jul 2011 00:32:56 +0200, Alf P. Steinbach /Usenet wrote:
>>
>>> On the other hand, computing power is necessary for intelligence, because it's
>>> necessary for quickly performing large associative searches (like set
>>> intersections) in an extremely large model of the external world.
>>>
>>> Just to get an idea of what that means, put down a hypothesis of each neuron
>>> communicating 100 bytes per second on average. I dunno, perhaps it's just 1, it
>>> doesn't matter much. Assume, like, 1 trillion neurons in your brain. Then,
>>> what's going on there, is like 100 trillion bytes, or 10^11 bytes, being sent
>>> around per second. So for your PC you need a bus with that capacity, but as of
>>> 2011 your PC's bus doesn't shuffle hundreds of trillions of bytes per second;
>>> it's more like just hundreds of millions... That's the VON NEUMANN BOTTLENECK,
>>> the result of extreme centralization: currently a factor of 1 million short.
>>>
>>> And that translates to at least some years, probably a decade or two.
>>
>> I would not be so sure.
> 
> As I read this you mean "I would not be so sure that AI will be achieved in a 
> decade or two".
> 
> If that's what you mean then that's profoundly silly, arguing against an idiot's 
> position that nobody's argued for.
> 
> But if you mean that you're not so sure that it will take that long, then why?

I meant that so long nobody knows what the intelligence algorithmically is.
In this context estimations of necessary power are meaningless. It is like
an alchemist guessing how much wood he would need to heat the cauldron in
order to produce one ounce of gold. 

> The fly's nervous system reportedly has only millions of neurons, but still 
> seems to be "smarter and more complicated than any computer built so far", 
> according to Ann-Shynn Chiang of the National Tsing Hua University in Taiwan, 
> who did some breaktrough work on mapping a fly brain's neural net, published 
> this February[1].

[...]

> [1] <url: http://www.sciencedaily.com/releases/2010/12/101202124108.htm>

Yes, I remember the publication of 2006 the page refers to. Stimulating a
fly with 100% controlled input and comparing its behavior with the models
looks a productive approach.

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#580

* Dmitry A. Kazakov, on 02.07.2011 15:30:
> On Sat, 02 Jul 2011 12:23:35 +0200, Alf P. Steinbach /Usenet wrote:
>
>> * Dmitry A. Kazakov, on 02.07.2011 09:49:
>>> On Sat, 02 Jul 2011 00:32:56 +0200, Alf P. Steinbach /Usenet wrote:
>>>
>>>> On the other hand, computing power is necessary for intelligence, because it's
>>>> necessary for quickly performing large associative searches (like set
>>>> intersections) in an extremely large model of the external world.
>>>>
>>>> Just to get an idea of what that means, put down a hypothesis of each neuron
>>>> communicating 100 bytes per second on average. I dunno, perhaps it's just 1, it
>>>> doesn't matter much. Assume, like, 1 trillion neurons in your brain. Then,
>>>> what's going on there, is like 100 trillion bytes, or 10^11 bytes, being sent
>>>> around per second. So for your PC you need a bus with that capacity, but as of
>>>> 2011 your PC's bus doesn't shuffle hundreds of trillions of bytes per second;
>>>> it's more like just hundreds of millions... That's the VON NEUMANN BOTTLENECK,
>>>> the result of extreme centralization: currently a factor of 1 million short.
>>>>
>>>> And that translates to at least some years, probably a decade or two.
>>>
>>> I would not be so sure.
>>
>> As I read this you mean "I would not be so sure that AI will be achieved in a
>> decade or two".
>>
>> If that's what you mean then that's profoundly silly, arguing against an idiot's
>> position that nobody's argued for.
>>
>> But if you mean that you're not so sure that it will take that long, then why?
>
> I meant that so long nobody knows what the intelligence algorithmically is.
> In this context estimations of necessary power are meaningless. It is like
> an alchemist guessing how much wood he would need to heat the cauldron in
> order to produce one ounce of gold.

Oh, I wouldn't have guessed that meaning, it's too meaningless to me, sorry.

Probably, as seen from my perspective, the insight that you're lacking is that 
many aspects of intelligence are well understood, and that one such aspect is 
the need for a large, detailed model of the world (where "world" means whatever 
environment that the intelligence interacts with), a model that supports almost 
instant association actions and (possibly vague) set intersection.

You can compare this to, not alchemist as you mentioned (which has the wrong 
kind of connotations) but  --  scientific or engineering-like chemists. Your 
task as a fumbling beginner engineering chemist is to produce hydrogen from 
water. You have no idea how to do that, but even though you're pretty clueless 
about the process you're able to calculate that you will need *at least* as many 
kilograms of water as the number of kilograms of hydrogen to produce.

This will under-estimate the amount of water that you need, severely.

But it isn't an estimate that tells you how much is sufficient: it only tells 
you that that amount, at the very least, is required, and its valid and it's 
entirely correct, for you do need at least that much water.


>> The fly's nervous system reportedly has only millions of neurons, but still
>> seems to be "smarter and more complicated than any computer built so far",
>> according to Ann-Shynn Chiang of the National Tsing Hua University in Taiwan,
>> who did some breaktrough work on mapping a fly brain's neural net, published
>> this February[1].
>
> [...]
>
>> [1]<url: http://www.sciencedaily.com/releases/2010/12/101202124108.htm>
>
> Yes, I remember the publication of 2006 the page refers to.

I'm impressed, I don't see any reference to 2006.

The journal reference of the original research:
[
Ann-Shyn Chiang, Chih-Yung Lin, Chao-Chun Chuang, Hsiu-Ming Chang, Chang-Huain 
Hsieh, Chang-Wei Yeh, Chi-Tin Shih, Jian-Jheng Wu, Guo-Tzau Wang, Yung-Chang 
Chen et al.
Three-Dimensional Reconstruction of Brain-wide Wiring Networks in Drosophila at 
Single-Cell Resolution.
Current Biology, December 2, 2010 DOI: 10.1016/j.cub.2010.11.056
]

It says "December 2, 2010", but perhaps based on earlier work that you remember?


> Stimulating a
> fly with 100% controlled input and comparing its behavior with the models
> looks a productive approach.

I agree with your idea for one productive approach, I think that would be good 
and necessary. Another approach, that might be also employed, might be to 
computationally evolve the model based on how the model fares in some virtual 
environment (that might ultimately be replaced with robot). This way it could 
possibly be evolved forward much faster, e.g. with many sims in parallel. And 
perhaps equally important, as opposed to the Reality comparision, it might be 
possible to evolve smaller parts of the model independently, at least some part 
of the way. Which might make the difference between publishing in one's own life 
or after. ;-)


Cheers,

- Alf

-- 
blog at <url: http://alfps.wordpress.com>

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#581

On Sat, 02 Jul 2011 17:06:29 +0200, Alf P. Steinbach /Usenet wrote:

> * Dmitry A. Kazakov, on 02.07.2011 15:30:

>> I meant that so long nobody knows what the intelligence algorithmically is.
>> In this context estimations of necessary power are meaningless. It is like
>> an alchemist guessing how much wood he would need to heat the cauldron in
>> order to produce one ounce of gold.
> 
> Oh, I wouldn't have guessed that meaning, it's too meaningless to me, sorry.
> 
> Probably, as seen from my perspective, the insight that you're lacking is that 
> many aspects of intelligence are well understood, and that one such aspect is 
> the need for a large, detailed model of the world (where "world" means whatever 
> environment that the intelligence interacts with), a model that supports almost 
> instant association actions and (possibly vague) set intersection.

I don't think that a model of the world is an essential part:

1. Insects and other primitive species certainly do not have it, yet solve
problems too complex for programmed computers. They also possess very
limited abilities to learn, so even learning is not a key aspect in
achieving the level of intelligence they show.

2. A newly born child does not have any model. The model is constructed
later in the process of learning.

The problem of intelligence is not how to teach children, but how to
construct them (in some less traditional way (:-)).

> You can compare this to, not alchemist as you mentioned (which has the wrong 
> kind of connotations) but  --  scientific or engineering-like chemists. Your 
> task as a fumbling beginner engineering chemist is to produce hydrogen from 
> water. You have no idea how to do that, but even though you're pretty clueless 
> about the process you're able to calculate that you will need *at least* as many 
> kilograms of water as the number of kilograms of hydrogen to produce.

There must be a sound model of intelligence before any estimations could be
made. In your example with a chemist such model exists. We know that water
is H2O. We do know how to produce water from hydrogen and oxygen, and
conversely. An alchemist knew nothing of that. With the problem of
intelligence we are rather in the position of an alchemist operating
alchemical symbols and, I am afraid, our understanding of the problem is
comparably absurd.

>>> The fly's nervous system reportedly has only millions of neurons, but still
>>> seems to be "smarter and more complicated than any computer built so far",
>>> according to Ann-Shynn Chiang of the National Tsing Hua University in Taiwan,
>>> who did some breaktrough work on mapping a fly brain's neural net, published
>>> this February[1].
>>
>> [...]
>>
>>> [1]<url: http://www.sciencedaily.com/releases/2010/12/101202124108.htm>
>>
>> Yes, I remember the publication of 2006 the page refers to.
> 
> I'm impressed, I don't see any reference to 2006.

http://www.sciencedaily.com/releases/2006/09/060920192529.htm

(Though then I read it somewhere else, I guess)

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#584

On Sat, 02 Jul 2011 18:09:48 +0200, Dmitry A. Kazakov wrote:
> On Sat, 02 Jul 2011 17:06:29 +0200, Alf P. Steinbach /Usenet wrote:
...
>> Probably, as seen from my perspective, the insight that you're lacking
>> is that many aspects of intelligence are well understood, and that one
>> such aspect is the need for a large, detailed model of the world (where
>> "world" means whatever environment that the intelligence interacts
>> with), a model that supports almost instant association actions and
>> (possibly vague) set intersection.
> 
> I don't think that a model of the world is an essential part:
> 
> 1. Insects and other primitive species certainly do not have it, yet
> solve problems too complex for programmed computers. They also possess
> very limited abilities to learn, so even learning is not a key aspect in
> achieving the level of intelligence they show.

I doubt that those assertions are correct, but don't have time to
look for contrarywise evidence.  Can you provide evidence for them?

By the way, "I don't think x is y" is, in English, not a useful 
construction.  (It is tantamount, in my estimation, to "I don't 
think".)  One should instead say "I think x is not y".

> 2. A newly born child does not have any model. The model is constructed
> later in the process of learning.
...

Do you have any evidence or sources to support that assertion?  The
state of research re models in newborns appears to me to not provide
a clear cut answer.  For example, the first URL below quotes research
that says "Babies are born with a fairly detailed representation of the 
average human face that helps them recognise familiar faces and also 
helps them learn about the social world" while the abstracted page in
the other URL suggests it is controversial.

<http://www.newscientist.com/article/dn6355-babies-prefer-to-gaze-upon-beautiful-faces.html>
<http://onlinelibrary.wiley.com/doi/10.1002/icd.241/abstract>


Of course, the issues of fact that I mention above might be irrelevant
to the larger picture of whatever it is you are discussing.  This thread
perhaps started out as a discussion of future-of-Lisp, then Lisp-and-AI,
what-is-AI, what-is-intelligence, hardware-for-intelligence, etc, with 
various subthreads less amenable to three-word titles and various unclear
arguments and aims.  If the fact issues aren't relevant, feel free to 
ignore them and instead clarify the point of discussion.

-- 
jiw

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#587

On Sat, 2 Jul 2011 17:23:55 +0000 (UTC), James Waldby wrote:

> On Sat, 02 Jul 2011 18:09:48 +0200, Dmitry A. Kazakov wrote:
>> On Sat, 02 Jul 2011 17:06:29 +0200, Alf P. Steinbach /Usenet wrote:
> ...
>>> Probably, as seen from my perspective, the insight that you're lacking
>>> is that many aspects of intelligence are well understood, and that one
>>> such aspect is the need for a large, detailed model of the world (where
>>> "world" means whatever environment that the intelligence interacts
>>> with), a model that supports almost instant association actions and
>>> (possibly vague) set intersection.
>> 
>> I don't think that a model of the world is an essential part:
>> 
>> 1. Insects and other primitive species certainly do not have it, yet
>> solve problems too complex for programmed computers. They also possess
>> very limited abilities to learn, so even learning is not a key aspect in
>> achieving the level of intelligence they show.
> 
> I doubt that those assertions are correct, but don't have time to
> look for contrarywise evidence.  Can you provide evidence for them?

No, it would be difficult to find a way to prove or disprove that. So if
the argument does not work, I will not insist on it.

>> 2. A newly born child does not have any model. The model is constructed
>> later in the process of learning.
> ...
> 
> Do you have any evidence or sources to support that assertion?  The
> state of research re models in newborns appears to me to not provide
> a clear cut answer.  For example, the first URL below quotes research
> that says "Babies are born with a fairly detailed representation of the 
> average human face that helps them recognise familiar faces and also 
> helps them learn about the social world" while the abstracted page in
> the other URL suggests it is controversial.

An innate facial recognition ability does not imply any model of the world
and conversely. Especially if the claim possibly is that a model is
necessary for this ability (considering facial recognition a part of
intelligence). A vicious circle.

-- 
Regards,
Dmitry A. Kazakov
http://www.dmitry-kazakov.de

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#672

On Jul 2, 12:23 pm, James Waldby <n...@valid.invalid> wrote:
> On Sat, 02 Jul 2011 18:09:48 +0200, Dmitry A. Kazakov wrote:
> > On Sat, 02 Jul 2011 17:06:29 +0200, Alf P. Steinbach /Usenet wrote:
> ...
> >> Probably, as seen from my perspective, the insight that you're lacking
> >> is that many aspects of intelligence are well understood, and that one
> >> such aspect is the need for a large, detailed model of the world (where
> >> "world" means whatever environment that the intelligence interacts
> >> with), a model that supports almost instant association actions and
> >> (possibly vague) set intersection.
>
> > I don't think that a model of the world is an essential part:
>
> > 1. Insects and other primitive species certainly do not have it, yet
> > solve problems too complex for programmed computers. They also possess
> > very limited abilities to learn, so even learning is not a key aspect in
> > achieving the level of intelligence they show.
>
> I doubt that those assertions are correct, but don't have time to
> look for contrarywise evidence.  Can you provide evidence for them?
>
> By the way, "I don't think x is y" is, in English, not a useful
> construction.  (It is tantamount, in my estimation, to "I don't
> think".)  One should instead say "I think x is not y".

I have been holding this same pet opinion for several years now.
One could go still further and claim that in order to say (or type)
the sentence "I don't think x is y", the dependent clause "x is y"
must assume some form in the mind. This assumption of form
(transient though it may be) is indistinguishable from *thought*
properly so called. So the speaker demonstrates the thought to
be, in fact, thinkable; and simultaneously claims that it is
unthinkable.

Therefore the sentence is equivalent to "I speak without thinking."
Or, with more venom, "Nothing I say evinces intellectual activity
of any kind."  Or even, "I am a cretinous Cretan!" It is certainly
*denial* in the popular-psychology sense.

But moving the "not" to the dependent clause creates an assertion
(rhetorically, a much stronger statement) as well as removing a
contraction.

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#675

luser droog <mijoryx@yahoo.com> writes:

> On Jul 2, 12:23 pm, James Waldby <n...@valid.invalid> wrote:
<snip>
>> By the way, "I don't think x is y" is, in English, not a useful
>> construction.  (It is tantamount, in my estimation, to "I don't
>> think".)  One should instead say "I think x is not y".
>
> I have been holding this same pet opinion for several years now.
> One could go still further and claim that in order to say (or type)
> the sentence "I don't think x is y", the dependent clause "x is y"
> must assume some form in the mind. This assumption of form
> (transient though it may be) is indistinguishable from *thought*
> properly so called. So the speaker demonstrates the thought to
> be, in fact, thinkable; and simultaneously claims that it is
> unthinkable.
>
> Therefore the sentence is equivalent to "I speak without thinking."
> Or, with more venom, "Nothing I say evinces intellectual activity
> of any kind."  Or even, "I am a cretinous Cretan!" It is certainly
> *denial* in the popular-psychology sense.
>
> But moving the "not" to the dependent clause creates an assertion
> (rhetorically, a much stronger statement) as well as removing a
> contraction.

(a) I don't think the sky is blue.  I know that it is.

(b) Keats: "Beauty is truth"
    Carritt: "I don't think beauty is truth!"

(c) I don't think all of this discussion is silly.

Example (a) shows that we sometime want to put the emphasis on the
thinking itself rather than on the "thinking not"

(b) shows that we may want to keep the pattern "x is y" either for the
rhetorical effect or simply to avoid a messy re-write.

Finally, example (c) shows that some instantiations of x in "I don't
think x is y" make "I think x is not y" quite a different statement.

Do you want red or white? :-)

-- 
Ben.

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#676

Ben Bacarisse wrote:
) (a) I don't think the sky is blue.  I know that it is.
)
) (b) Keats: "Beauty is truth"
)     Carritt: "I don't think beauty is truth!"
)
) (c) I don't think all of this discussion is silly.
)
) Example (a) shows that we sometime want to put the emphasis on the
) thinking itself rather than on the "thinking not"
)
) (b) shows that we may want to keep the pattern "x is y" either for the
) rhetorical effect or simply to avoid a messy re-write.
)
) Finally, example (c) shows that some instantiations of x in "I don't
) think x is y" make "I think x is not y" quite a different statement.

Example (c) is a bit contrived, as the obvious way of putting it
pedantically is:

(c) I think not all of this discussion is silly.

Which is obviously because it wasn't "I don't think x is y" as is.


However, to put it more simply, "I don't think (proposition)" is a
qolloquially valid form of "I have doubts on (proposition)", even though
purely logically it means something different.  Language is not logic.

Note that it is *not* the same as "I think (not proposition)".
Claiming that it is, is the logical fallacy of the excluded middle.


SaSW, Willem
-- 
Disclaimer: I am in no way responsible for any of the statements
            made in the above text. For all I know I might be
            drugged or something..
            No I'm not paranoid. You all think I'm paranoid, don't you !
#EOT

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#677

Willem <willem@toad.stack.nl> writes:

> Ben Bacarisse wrote:
> ) (a) I don't think the sky is blue.  I know that it is.
> )
> ) (b) Keats: "Beauty is truth"
> )     Carritt: "I don't think beauty is truth!"
> )
> ) (c) I don't think all of this discussion is silly.
> )
> ) Example (a) shows that we sometime want to put the emphasis on the
> ) thinking itself rather than on the "thinking not"
> )
> ) (b) shows that we may want to keep the pattern "x is y" either for the
> ) rhetorical effect or simply to avoid a messy re-write.
> )
> ) Finally, example (c) shows that some instantiations of x in "I don't
> ) think x is y" make "I think x is not y" quite a different statement.
>
> Example (c) is a bit contrived, as the obvious way of putting it
> pedantically is:
>
> (c) I think not all of this discussion is silly.
>
> Which is obviously because it wasn't "I don't think x is y" as is.

Of course it's contrived!  All of the examples were very deliberately
contrived!  But is it a useful example?  I think so.  If I understand
you, you are saying the implied quantifier (for all...) makes it not of
the form "I don't think x is y" but my point was precisely that using x
and y like this does not work unless you take care to exclude all sorts
of forms of x (and possible y) as one would have to do in first-order
logic.

<snip>
>  Language is not logic.

Exactly.

<snip>
-- 
Ben.

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#585

* Dmitry A. Kazakov, on 02.07.2011 18:09:
> On Sat, 02 Jul 2011 17:06:29 +0200, Alf P. Steinbach /Usenet wrote:
>
>> * Dmitry A. Kazakov, on 02.07.2011 15:30:
>
>>> I meant that so long nobody knows what the intelligence algorithmically is.
>>> In this context estimations of necessary power are meaningless. It is like
>>> an alchemist guessing how much wood he would need to heat the cauldron in
>>> order to produce one ounce of gold.
>>
>> Oh, I wouldn't have guessed that meaning, it's too meaningless to me, sorry.
>>
>> Probably, as seen from my perspective, the insight that you're lacking is that
>> many aspects of intelligence are well understood, and that one such aspect is
>> the need for a large, detailed model of the world (where "world" means whatever
>> environment that the intelligence interacts with), a model that supports almost
>> instant association actions and (possibly vague) set intersection.
>
> I don't think that a model of the world is an essential part:
>
> 1. Insects and other primitive species certainly do not have it, yet solve
> problems too complex for programmed computers. They also possess very
> limited abilities to learn, so even learning is not a key aspect in
> achieving the level of intelligence they show.

Regarding "insects ... do not have [a model of the world]". They do relate to 
the world, mostly with hardwired sequences of responses. You can *define* the 
model as the system that provides the responses. Substitute some other model and 
you get responses that won't work very well for the creature -> insect dies. 
Thus the world model that is there is necessarily very finely adapted.

Regarding "yet solve problems too complex for programmed computers", if you're 
talking about control of the body, then that's right, but then it isn't about 
intelligence but rather about feedback and control systems. If you're talking 
about analytical "problems", well, they don't solve such problems. In 
particular, if you're thinking of Traveling Salesman-solving insects (there was 
some misleading media coverage of such a thing some months ago, or perhaps a 
year ago), no, if that's what you're alluding to then please, mark down the 
source that misled you as unreliable, not serious, ungood, bad, silly...

Regarding "even learning is not a key aspect in achieving the level of 
intelligence they show", well, what level intelligence do insects show? Not very 
much intelligence. By any measure of intelligence an individual insect has about 
zero, about the same as a thermostat. Give an insect an IQ test and it won't 
even get the first question right. Zero correct answers => 0 IQ. :-)

Getting an artifical system to emulate an insect brain is still worthwhile.

For if one can't do even that, then it's rather hopeless to aim for AI, and 
secondly, as we have discussed, as opposed to what goes on in a human brain the 
dataflow per second inside an insect brain appears to be somewhat within the 
capabilities of current computers (even a PC).


> 2. A newly born child does not have any model. The model is constructed
> later in the process of learning.

Your idea here is, I believe, one extreme position in the so called "nurture 
versus nature" debate.

The nature versus nurture debate is so old that is has been resolved.

Summary: it's both, both innate capabilities (model) and learning.


> The problem of intelligence is not how to teach children, but how to
> construct them (in some less traditional way (:-)).

Well, that too.


Cheers,

- Alf

-- 
blog at <url: http://alfps.wordpress.com>

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