Re: [FRIAM] Future of humans and artificial intelligence

[Steven A Smith]

thanks for the reference, I was not aware of the Renesan 
 Institute 
before this, though I had heard somewhere about the first listed 
lecture/course/seminar on "the Trickster".   I don't see your course in 
the lineup?  I will be out of town on the 7th so I wouldn't try to 
attend anyway, but as always "good on ya" for your efforts to continue 
to spread the enlightenment.


I've a friend who introduced me to Jack... he was in middle school in 
Portales when someone introduced him to "that old professor who writes 
Science Fiction" (then in his 50s?).  They became fast friends despite 
the many decades between them, and my friend Joe even influenced several 
of Jack's titles, if not characters and narratives.  He claims he helped 
Jack come up with the title "Terraforming Earth", although Joe's 
throwdown was "Terraforming Terra" which apparently Jack loved but his 
editor said "not enough people know what 'Terra' is".  Oh well.


In Jack's life story, his parents moved him from their hardscrabble farm 
near Bisbee AZ where he was born to a relative's more productive ranches 
in Mexico/TX but eventually eventually they migrated to NM in 1915 in a 
covered wagon.  He has(d) stories!


I have a copy of Jack's 2005 autobiography, "Wonder's Child" if 
perchance you would like to borrow it.   The duality of Science/Fiction 
( or more generally the interplay between the literal/actualized and the 
imagined is a fascinating study to me).   This second wave of Scientific 
Romancing (after Verne, Swift, Burroughs, even London/Twain) was so 
smack-dab in the middle of the golden age of transportation and 
communication, into information processing that it deeply 
informs/reflects our contemporary psyche, even for those who think they 
don't like or care about Science Fiction.   The more modern adoption of 
Science Fiction into mainstream cinema/TV has put titles/tropes like 
"the Matrix" and "BladeRunner", "Avatar" and "Dr. Who" squarely in the 
face (most literally) of the masses.


I believe this is for the better and the worse.  Like everything I 
suppose!  Nothing Aristotelian about MY logic!?


- Steve

   /"The best thing about being on the fence is that the view is better
   from up there"/ - R. Edward Lowe

Steve, it is a Renesan course on Tue, September 7 and 14. I have read 
Jack Williamson, not all 90, and he would have been included in 
another course I proposed to Renesan on science fiction themes. Maybe 
in the future.


davew



On Wed, Aug 9, 2017, at 09:57 AM, Steven A Smith wrote:


Dave -

Most excellent of you to do this, and what will be your venue for 
this class?


Are you familiar with our own Jack Williamson 
's vague parallel work 
in his "Humanoids" which began in 1947 with the Novelette: "With 
Folded Hands". I do not know if he ever acknowledged an influence in 
this work from Asimov's introduction to the "three laws" in 1941? He 
investigates the (unintended/unexpected catastrophic consequences of 
something like the three laws on humanity, having the human spirit 
"quelled" by being "niced" or "safed" near-to-death)


He claims  to have written this as a cathartic project to shake off 
the existential angst/depression he felt from the (ab)use of atomic 
weapons at the end of WWII.  Jack was too old to serve in the 
military when the war broke out (he was 36?), but instead volunteered 
to work in the South Pacific as a civilian meteorologist.  He had 
started his career in Science Fiction before the term was fully 
adopted (Scientific Romance and Scientifiction being precursors 
according to Jack) with the publication of a short story "Metal Man" 
In Hugo Gernsbach's /Amazing Stories /in 1928.  Up until the end of 
WWII he claims to have been somewhat of a techno-utopianist, 
believing that advancing technology would (continue to ) simply 
advance the quality of life of human beings (somewhat?) monotonically.


I hosted Jack at an evening talk at LANL/Bradbury Science Museum in 
1998 during the Nebula Awards on the theme of how Science and Science 
Fiction inform one another.   Jack was 90 that year and had over 90 
published works at that time.  His work was always somewhat in the 
vein of Space Opera and his characters were generally quite two 
dimensional and his gender politics typical of his generation of 
science fictioneers, yet he was still loved by his community.  His 
use of this pulpy/pop medium as a way to investigate and discuss 
fundamental aspects of human nature and many of the social or even 
spiritual implications of the advance of technology was nevertheless 
quite inspired (IMO).


He died in 2007 at the ripe young age of 98 and was still producing 
work nearly up to the day of his death.  In 1998 when I first met 
him, the OED was creating an appendix/section of "neologisms from 
science fiction" and he was credited (informally?) with having the 
most 

Re: [FRIAM] Future of humans and artificial intelligence

[Prof David West]

Steve, it is a Renesan course on Tue, September 7 and 14. I have read
Jack Williamson, not all 90, and he would have been included in
another course I proposed to Renesan on science fiction themes. Maybe
in the future.
davew



On Wed, Aug 9, 2017, at 09:57 AM, Steven A Smith wrote:
> Dave -


> Most excellent of you to do this, and what will be your venue for
> this class?> Are you familiar with our own Jack Williamson[1]'s vague 
> parallel work
> in his "Humanoids" which began in 1947 with the Novelette: "With
> Folded Hands".  I do not know if he ever acknowledged an influence in
> this work from Asimov's introduction to the "three laws" in 1941?  He
> investigates the (unintended/unexpected catastrophic consequences of
> something like the three laws on humanity, having the human spirit
> "quelled" by being "niced" or "safed" near-to-death)> He claims  to have 
> written this as a cathartic project to shake off
> the existential angst/depression he felt from the (ab)use of atomic
> weapons at the end of WWII.  Jack was too old to serve in the military
> when the war broke out (he was 36?), but instead volunteered to work
> in the South Pacific as a civilian meteorologist.  He had started his
> career in Science Fiction before the term was fully adopted
> (Scientific Romance and Scientifiction being precursors according to
> Jack) with the publication of a short story "Metal Man" In Hugo
> Gernsbach's *Amazing Stories *in 1928.  Up until the end of WWII he
> claims to have been somewhat of a techno-utopianist, believing that
> advancing technology would (continue to ) simply advance the quality
> of life of human beings (somewhat?) monotonically.> I hosted Jack at an 
> evening talk at LANL/Bradbury Science Museum in
> 1998 during the Nebula Awards on the theme of how Science and Science
> Fiction inform one another.   Jack was 90  that year and had over 90
> published works at that time.  His work was always somewhat in the
> vein of Space Opera and his characters were generally quite two
> dimensional and his gender politics typical of his generation of
> science fictioneers, yet he was still loved by his community.  His use
> of this pulpy/pop medium as a way to investigate and discuss
> fundamental aspects of human nature and many of the social or even
> spiritual implications of the advance of technology was nevertheless
> quite inspired (IMO).> He died in 2007 at the ripe young age of 98 and was 
> still producing
> work nearly up to the day of his death.  In 1998 when I first met him,
> the OED was creating an appendix/section of "neologisms from science
> fiction" and he was credited (informally?) with having the most
> entries in the not-yet-published project.   His most famous throwdown
> in this category at the time was his "invention" of anti-matter, which
> he called "contra-terrene" or more colloquially "seetee" (a
> phoneticization of the contraction "CT")!   He was also quite proud of
> being interrogated by the FBI during the Manhattan project for having
> written a story about Atomic Weapons... they wanted to assume he had
> access to a security leak until he showed them a 1932(?) short story
> on the same theme, making it clear that the ideas of nuclear fission
> (fusion even?) as a weapon were not new (to him anyway)...  that
> apparently satisfied them and of course, he didn't appreciate the full
> import of their interrogation until after the war.> Carry On!


>  - Steve


> 
> On 8/9/17 9:05 AM, Prof David West wrote:
>> For what its worth - I will be teaching a short class next month in
>> Santa Fe, "Isaac Asimov and the Robots." Two points of coverage: 1)
>> the robots themselves invent and follow a "Zeroth Law" that allows
>> them to eliminate individual human beings with a result the exact
>> opposite of Hawking et. al.'s fears that our  creations will not love
>> us; 2) how the actual evolution of robotics and AI (see Daniel
>> Suarez'* Kill Decision* - autonomous swarming drones as tools of war
>> and death to humans) diverged from the rosy naive 1950s view of the
>> future that Asimov advanced.>> 
>> davew
>> 
>> 
>> On Mon, Aug 7, 2017, at 09:54 PM, Carl Tollander wrote:
>>> It seems to me that there are many here in the US who are not
>>> entirely on board with Asimov's First Law of Robotics, at least
>>> insofar as it may apply to themselves, so I suspect notions of
>>> "reining it in" are probably not going to fly.>>> 
>>> 
>>> 
>>> 
>>> On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez
>>>  wrote: Future will be quite interesting. How will 
>>> be the human being of
 the future? For sure not a human being in the way we know. 
 http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158
  
 
 FRIAM Applied Complexity Group listserv
 Meets Fridays 9a-11:30 at cafe at St. John's 

Re: [FRIAM] Future of humans and artificial intelligence

[Steven A Smith]

Dave -

Most excellent of you to do this, and what will be your venue for this 
class?


Are you familiar with our own Jack Williamson 
's vague parallel work in 
his "Humanoids" which began in 1947 with the Novelette: "With Folded 
Hands".  I do not know if he ever acknowledged an influence in this work 
from Asimov's introduction to the "three laws" in 1941?  He investigates 
the (unintended/unexpected catastrophic consequences of something like 
the three laws on humanity, having the human spirit "quelled" by being 
"niced" or "safed" near-to-death)


He claims  to have written this as a cathartic project to shake off the 
existential angst/depression he felt from the (ab)use of atomic weapons 
at the end of WWII.  Jack was too old to serve in the military when the 
war broke out (he was 36?), but instead volunteered to work in the South 
Pacific as a civilian meteorologist.  He had started his career in 
Science Fiction before the term was fully adopted (Scientific Romance 
and Scientifiction being precursors according to Jack) with the 
publication of a short story "Metal Man" In Hugo Gernsbach's /Amazing 
Stories /in 1928.  Up until the end of WWII he claims to have been 
somewhat of a techno-utopianist, believing that advancing technology 
would (continue to ) simply advance the quality of life of human beings 
(somewhat?) monotonically.


I hosted Jack at an evening talk at LANL/Bradbury Science Museum in 1998 
during the Nebula Awards on the theme of how Science and Science Fiction 
inform one another.   Jack was 90  that year and had over 90 published 
works at that time.  His work was always somewhat in the vein of Space 
Opera and his characters were generally quite two dimensional and his 
gender politics typical of his generation of science fictioneers, yet he 
was still loved by his community.  His use of this pulpy/pop medium as a 
way to investigate and discuss fundamental aspects of human nature and 
many of the social or even spiritual implications of the advance of 
technology was nevertheless quite inspired (IMO).


He died in 2007 at the ripe young age of 98 and was still producing work 
nearly up to the day of his death.  In 1998 when I first met him, the 
OED was creating an appendix/section of "neologisms from science 
fiction" and he was credited (informally?) with having the most entries 
in the not-yet-published project.   His most famous throwdown in this 
category at the time was his "invention" of anti-matter, which he called 
"contra-terrene" or more colloquially "seetee" (a phoneticization of the 
contraction "CT")!   He was also quite proud of being interrogated by 
the FBI during the Manhattan project for having written a story about 
Atomic Weapons... they wanted to assume he had access to a security leak 
until he showed them a 1932(?) short story on the same theme, making it 
clear that the ideas of nuclear fission (fusion even?) as a weapon were 
not new (to him anyway)...  that apparently satisfied them and of 
course, he didn't appreciate the full import of their interrogation 
until after the war.


Carry On!

 - Steve


On 8/9/17 9:05 AM, Prof David West wrote:
For what its worth - I will be teaching a short class next month in 
Santa Fe, "Isaac Asimov and the Robots." Two points of coverage: 1) 
the robots themselves invent and follow a "Zeroth Law" that allows 
them to eliminate individual human beings with a result the exact 
opposite of Hawking et. al.'s fears that our  creations will not love 
us; 2) how the actual evolution of robotics and AI (see Daniel 
Suarez'/Kill Decision/ - autonomous swarming drones as tools of war 
and death to humans) diverged from the rosy naive 1950s view of the 
future that Asimov advanced.


davew


On Mon, Aug 7, 2017, at 09:54 PM, Carl Tollander wrote:
It seems to me that there are many here in the US who are not 
entirely on board with Asimov's First Law of Robotics, at least 
insofar as it may apply to themselves, so I suspect notions of 
"reining it in" are probably not going to fly.





On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez 
> wrote:


Future will be quite interesting. How will be the human being of
the future? For sure not a human being in the way we know.


http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158




FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[Prof David West]

For what its worth - I will be teaching a short class next month in
Santa Fe, "Isaac Asimov and the Robots." Two points of coverage: 1) the
robots themselves invent and follow a "Zeroth Law" that allows them to
eliminate individual human beings with a result the exact opposite of
Hawking et. al.'s fears that our  creations will not love us; 2) how
the actual evolution of robotics and AI (see Daniel Suarez'* Kill
Decision* - autonomous swarming drones as tools of war and death to
humans) diverged from the rosy naive 1950s view of the future that
Asimov advanced.
davew


On Mon, Aug 7, 2017, at 09:54 PM, Carl Tollander wrote:
> It seems to me that there are many here in the US who are not entirely
> on board with Asimov's First Law of Robotics, at least insofar as it
> may apply to themselves, so I suspect notions of "reining it in" are
> probably not going to fly.> 
> 
> 
> 
> On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez
>  wrote:>> Future will be quite interesting. How will be 
> the human being of the
>> future? For sure not a human being in the way we know.>> 
>> http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158>>
>>  
>> 
>>  FRIAM Applied Complexity Group listserv
>>  Meets Fridays 9a-11:30 at cafe at St. John's College
>>  to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com>>  
>> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove


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Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[gepr ⛧]

FWIW, I tend to use stochastic to mean a process with a collection of 
variables, some of which are (pseudo) randomly set and some of which are not. A 
"random process" would imply a process where either all the variables are 
random OR where the randomly set variables are dominant. A process can be 
stochastic even if the randomness has little effect.

My use of indeterminate is ambiguous. In processes where we're ignorant of how 
a variable is set, those variables are indeterminate​. But I also use it to 
mean unset variables. E.g. a semaphore that's being polled for a value or state 
change. But as with stochasticity, a "don't care" variable can be indeterminate 
without making the whole process indeterminate.

On August 8, 2017 11:23:29 PM PDT, Grant Holland  
wrote:
>Nick,
>
>In science, these three terms are generally interchangeable. Their 
>common usage is that they all describe activities, or "events", that
>are 
>"subject to chance". Such activities, events or processes that are 
>described by these terms are governed by the laws of probability. They 
>all describe activities, events, or "happenings" whose repetitions do 
>not always produce the same outcomes even when given the same inputs 
>every time (initial conditions). In other words, uncertainty is
>involved.
>
>However, like most words, these enjoy other usage, meanings, as well. 
>For example "random" is sometimes used to mean "disorganized" or 
>"lacking in specific pattern". This is a very different meaning than 
>"activities that don't always produce the same outcome given the same 
>inputs". Consider what a math formula for each of these tow meanings 
>wold consist of. One of them would be based on probabilities; but the 
>other would involve stationary relationships.
>
>On 8/8/17 5:31 PM, Nick Thompson wrote:
>>
>> Grant,
>>
>> I think I know the answer to this question, but want to make sure:
>>
>> What is the difference beween calling a process “stochastic”, 
>> “indeterminate”, or “random”?
-- 
⛧glen⛧


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

"Right.  Then you use gradient ascent.  But what if you are scheduling a job 
shop for throughput when there are thousands of variables most of which have 
discrete values?"


I'd try to code it up for a SMT solver like Z3, or look for a SMT solver that 
had theories that closely matched the domain of the job shop.  Or try something 
like this<https://arxiv.org/abs/1609.02200> on a D-Wave.

<https://arxiv.org/abs/1609.02200>

Marcus



From: Friam <friam-boun...@redfish.com> on behalf of Frank Wimberly 
<wimber...@gmail.com>
Sent: Wednesday, August 9, 2017 7:35 AM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Future of humans and artificial intelligence

Right.  Then you use gradient ascent.  But what if you are scheduling a job 
shop for throughput when there are thousands of variables most of which have 
discrete values?

Frank

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 10:41 PM, "Marcus Daniels" 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

Frank writes:


"My point was that depth-first and breadth-first can probably serve only as a 
straw-man (straw-men?)."


Unless there is a robust meta-rule (not heuristic) or single deterministic 
search algorithm to rule them all, then wouldn't those other suggestions also 
be straw-men too?   If I knew that there were no noise and the domain was 
continuous and convex, then I wouldn't use a stochastic approach.


Marcus


From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Frank Wimberly <wimber...@gmail.com<mailto:wimber...@gmail.com>>
Sent: Tuesday, August 8, 2017 10:15:05 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Future of humans and artificial intelligence

My point was that depth-first and breadth-first can probably serve only as a 
straw-man (straw-men?).

Frank Wimberly
Phone (505) 670-9918<tel:(505)%20670-9918>

On Aug 8, 2017 10:11 PM, "Marcus Daniels" 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

Frank writes:


"Then there's best-first search, B*, C*, constraint-directed search, etc.  And 
these are just classical search methods."


Connecting this back to evolutionary / stochastic techniques, genetic 
programming is one way to get the best of both approaches, at least in 
principle.   One can expose these human-designed algorithms as predefined 
library functions.  Typically in genetic programming the vocabulary consists of 
simple routines (e.g. arithmetic), conditionals, and recursion.


In practice, this kind of seeding of the solution space can collapse diversity. 
  It is a drag to see tons of compute time spent on a million little 
refinements around an already good solution.  (Yes, I know that solution!)  
More fun to see a set of clumsy solutions turn into to decent-performing but 
weird solutions.  I find my attention is drawn to properties of sub-populations 
and how I can keep the historically good performers _out_.  Not a pure GA, but 
a GA where communities also have fitness functions matching my heavy hand of 
justice..  (If I prove that conservatism just doesn't work, I'll be sure to 
pass it along.)


Marcus



From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Frank Wimberly <wimber...@gmail.com<mailto:wimber...@gmail.com>>
Sent: Tuesday, August 8, 2017 7:57:06 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Future of humans and artificial intelligence

Then there's best-first search, B*, C*, constraint-directed search, etc.  And 
these are just classical search methods.

Feank

Frank Wimberly
Phone (505) 670-9918<tel:(505)%20670-9918>

On Aug 8, 2017 7:20 PM, "Marcus Daniels" 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

"But one problem is that breadth-first and depth-first search are just fast 
ways to find answers."


Just _not_ -- general but not efficient.   [My dog was demanding attention! ]


From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Marcus Daniels <mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>>
Sent: Tuesday, August 8, 2017 6:43:40 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Grant writes:


"On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) "


I think of logic programming systems as a traditional tool of AI research (e.g. 
Prolog, now Curry, similar capabilities implemented in Lisp) from the age 
before the AI winter

Re: [FRIAM] Future of humans and artificial intelligence

[Frank Wimberly]

Right.  Then you use gradient ascent.  But what if you are scheduling a job
shop for throughput when there are thousands of variables most of which
have discrete values?

Frank

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 10:41 PM, "Marcus Daniels" <mar...@snoutfarm.com> wrote:

> Frank writes:
>
>
> "My point was that depth-first and breadth-first can probably serve only
> as a straw-man (straw-men?)."
>
>
> Unless there is a robust meta-rule (not heuristic) or single deterministic
> search algorithm to rule them all, then wouldn't those other suggestions
> also be straw-men too?   If I knew that there were no noise and the domain
> was continuous and convex, then I wouldn't use a stochastic approach.
>
>
> Marcus
> --
> *From:* Friam <friam-boun...@redfish.com> on behalf of Frank Wimberly <
> wimber...@gmail.com>
> *Sent:* Tuesday, August 8, 2017 10:15:05 PM
> *To:* The Friday Morning Applied Complexity Coffee Group
> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>
> My point was that depth-first and breadth-first can probably serve only as
> a straw-man (straw-men?).
>
> Frank Wimberly
> Phone (505) 670-9918
>
> On Aug 8, 2017 10:11 PM, "Marcus Daniels" <mar...@snoutfarm.com> wrote:
>
>> Frank writes:
>>
>>
>> "Then there's best-first search, B*, C*, constraint-directed search,
>> etc.  And these are just classical search methods."
>>
>>
>> Connecting this back to evolutionary / stochastic techniques, genetic
>> programming is one way to get the best of both approaches, at least in
>> principle.   One can expose these human-designed algorithms as predefined
>> library functions.  Typically in genetic programming the vocabulary
>> consists of simple routines (e.g. arithmetic), conditionals, and recursion.
>>
>>
>> In practice, this kind of seeding of the solution space can collapse
>> diversity.   It is a drag to see tons of compute time spent on a million
>> little refinements around an already good solution.  (Yes, I know that
>> solution!)  More fun to see a set of clumsy solutions turn into to
>> decent-performing but weird solutions.  I find my attention is drawn to
>> properties of sub-populations and how I can keep the historically good
>> performers _out_.  Not a pure GA, but a GA where communities also have
>> fitness functions matching my heavy hand of justice..  (If I prove that
>> conservatism just doesn't work, I'll be sure to pass it along.)
>>
>>
>> Marcus
>>
>>
>> --
>> *From:* Friam <friam-boun...@redfish.com> on behalf of Frank Wimberly <
>> wimber...@gmail.com>
>> *Sent:* Tuesday, August 8, 2017 7:57:06 PM
>> *To:* The Friday Morning Applied Complexity Coffee Group
>> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>>
>> Then there's best-first search, B*, C*, constraint-directed search, etc.
>> And these are just classical search methods.
>>
>> Feank
>>
>> Frank Wimberly
>> Phone (505) 670-9918
>>
>> On Aug 8, 2017 7:20 PM, "Marcus Daniels" <mar...@snoutfarm.com> wrote:
>>
>>> "But one problem is that breadth-first and depth-first search are just
>>> fast ways to find answers."
>>>
>>>
>>> Just _not_ -- general but not efficient.   [My dog was demanding
>>> attention! ]
>>> --
>>> *From:* Friam <friam-boun...@redfish.com> on behalf of Marcus Daniels <
>>> mar...@snoutfarm.com>
>>> *Sent:* Tuesday, August 8, 2017 6:43:40 PM
>>> *To:* The Friday Morning Applied Complexity Coffee Group; glen ☣
>>> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>>>
>>>
>>> Grant writes:
>>>
>>>
>>> "On the other hand... evolution *is* stochastic. (You actually did not
>>> disagree with me on that. You only said that the reason I was right was
>>> another one.) "
>>>
>>>
>>> I think of logic programming systems as a traditional tool of AI
>>> research (e.g. Prolog, now Curry, similar capabilities implemented in Lisp)
>>> from the age before the AI winter.  These systems provide a very flexible
>>> way to pose constraint problems.  But one problem is that breadth-first and
>>> depth-first search are just fast ways to find answers.  Recent work seems
>>> to have shifted to SMT solvers and specialized constraint solving
>>> 

Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

"Genetic algorithms need not be, but can be, stochastic. Genetic algorithms are 
adaptive; but they need not be stochastically adaptive"

[..]

"Without this particular stochasticicty, there would only ever have been one 
species on earth, if that, and that species would now be long extinct because 
of its inability to adapt."


If an algorithm can result in there being one species it is not adaptive.   I 
meant to imply a GA has a non-zero mutation rate (not just selection) and that 
mutation is random, without specifying particular distributional properties or 
distinguishing between pseudo-random and `truly' random.


Marcus


From: Grant Holland <grant.holland...@gmail.com>
Sent: Wednesday, August 9, 2017 12:40:48 AM
To: The Friday Morning Applied Complexity Coffee Group; Marcus Daniels; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Marcus,

Let me clarify what I meant by saying that evolution is stochastic

By "evolution", I do not mean genetic algorithms. Genetic algorithms need not 
be, but can be, stochastic. Genetic algorithms are adaptive; but they need not 
be stochastically adaptive. On the other hand, biological evolution of life on 
earth is necessarily stochastically adaptive - due to chance mutations.

As Jacques Monod points out in his book "Chance and Necessity", chance 
mutations are the only natural mechanism by which new species are created. And 
it is completely subject to chance. Without this particular stochasticicty, 
there would only ever have been one species on earth, if that, and that species 
would now be long extinct because of its inability to adapt.

On 8/8/17 6:43 PM, Marcus Daniels wrote:

Grant writes:


"On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) "


I think of logic programming systems as a traditional tool of AI research (e.g. 
Prolog, now Curry, similar capabilities implemented in Lisp) from the age 
before the AI winter.  These systems provide a very flexible way to pose 
constraint problems.  But one problem is that breadth-first and depth-first 
search are just fast ways to find answers.  Recent work seems to have shifted 
to SMT solvers and specialized constraint solving algorithms, but these have 
somewhat less expressiveness as programming languages.  Meanwhile, machine 
learning has come on the scene in a big way and tasks traditionally associated 
with old-school AI, like natural language processing, are now matched or even 
dominated using neural nets (LSTM).  I find the range of capabilities provided 
by groups like nlp.stanford.edu really impressive -- there examples of both 
approaches (logic programming and machine learning) and then don't need to be 
mutually exclusive.


Quantum annealing is one area where the two may increasingly come together by 
using physical phenomena to accelerate the rate at which high dimensional 
discrete systems can be solved, without relying on fragile or domain-specific 
heuristics.


I often use evolutionary algorithms for hard optimization problems.  Genetic 
algorithms, for example, are robust to  noise (or if you like ambiguity) in 
fitness functions, and they are trivial to parallelize.


Marcus


From: Friam <friam-boun...@redfish.com><mailto:friam-boun...@redfish.com> on 
behalf of Grant Holland 
<grant.holland...@gmail.com><mailto:grant.holland...@gmail.com>
Sent: Tuesday, August 8, 2017 4:51:18 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Thanks for throwing in on this one, Glen. Your thoughts are ever-insightful. 
And ever-entertaining!

For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) A 
good book on the stochasticity of evolution is "Chance and Necessity" by 
Jacques Monod. (I just finished rereading it for the second time. And that 
proved quite fruitful.)

G.

On 8/8/17 12:44 PM, glen ☣ wrote:

I'm not sure how Asimov intended them.  But the three laws is a trope that 
clearly shows the inadequacy of deontological ethics.  Rules are fine as far as 
they go.  But they don't go very far.  We can see this even in the foundations 
of mathematics, the unification of physics, and polyphenism/robustness in 
biology.  Von Neumann (Burks) said it best when he said: "But in the 
complicated parts of formal logic it is always one order of magnitude harder to 
tell what an object can do than to produce the object."  Or, if you don't like 
that, you can see the same perspective in his iterative construction of sets as 
an alternative to the classical conc

Re: [FRIAM] Future of humans and artificial intelligence

[Grant Holland]

Marcus,

Let me clarify what I meant by saying that evolution is stochastic

By "evolution", I do not mean genetic algorithms. Genetic algorithms 
need not be, but can be, stochastic. Genetic algorithms are/adaptive; 
/but they need not be/stochastically /adaptive. On the other hand, 
biological evolution of life on earth is necessarily stochastically 
adaptive - due to chance mutations.


As Jacques Monod points out in his book "Chance and Necessity", chance 
mutations are the /only/ natural mechanism by which new species are 
created. And it is completely subject to chance. Without this particular 
stochasticicty, there would only ever have been one species on earth, if 
that, and that species would now be long extinct because of its 
inability to adapt.



On 8/8/17 6:43 PM, Marcus Daniels wrote:


Grant writes:


"On the other hand... evolution /is/ stochastic. (You actually did not 
disagree with me on that. You only said that the reason I was right 
was another one.) "



I think of logic programming systems as a traditional tool of AI 
research (e.g. Prolog, now Curry, similar capabilities implemented in 
Lisp) from the age before the AI winter.  These systems provide a very 
flexible way to pose constraint problems.  But one problem is that 
breadth-first and depth-first search are just fast ways to find 
answers.  Recent work seems to have shifted to SMT solvers and 
specialized constraint solving algorithms, but these have somewhat 
less expressiveness as programming languages.  Meanwhile, machine 
learning has come on the scene in a big way and tasks traditionally 
associated with old-school AI, like natural language processing, are 
now matched or even dominated using neural nets (LSTM).  I find the 
range of capabilities provided by groups like nlp.stanford.edu really 
impressive -- there examples of both approaches (logic programming and 
machine learning) and then don't need to be mutually exclusive.



Quantum annealing is one area where the two may increasingly come 
together by using physical phenomena to accelerate the rate at which 
high dimensional discrete systems can be solved, without relying on 
fragile or domain-specific heuristics.



I often use evolutionary algorithms for hard optimization problems.  
Genetic algorithms, for example, are robust to noise (or if you like 
ambiguity) in fitness functions, and they are trivial to parallelize.



Marcus


*From:* Friam <friam-boun...@redfish.com> on behalf of Grant Holland 
<grant.holland...@gmail.com>

*Sent:* Tuesday, August 8, 2017 4:51:18 PM
*To:* The Friday Morning Applied Complexity Coffee Group; glen ☣
*Subject:* Re: [FRIAM] Future of humans and artificial intelligence

Thanks for throwing in on this one, Glen. Your thoughts are 
ever-insightful. And ever-entertaining!


For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution /is/ stochastic. (You actually did not 
disagree with me on that. You only said that the reason I was right 
was another one.) A good book on the stochasticity of evolution is 
"Chance and Necessity" by Jacques Monod. (I just finished rereading it 
for the second time. And that proved quite fruitful.)


G.


On 8/8/17 12:44 PM, glen ☣ wrote:

I'm not sure how Asimov intended them.  But the three laws is a trope that clearly shows 
the inadequacy of deontological ethics.  Rules are fine as far as they go.  But they 
don't go very far.  We can see this even in the foundations of mathematics, the 
unification of physics, and polyphenism/robustness in biology.  Von Neumann (Burks) said 
it best when he said: "But in the complicated parts of formal logic it is always one 
order of magnitude harder to tell what an object can do than to produce the object." 
 Or, if you don't like that, you can see the same perspective in his iterative 
construction of sets as an alternative to the classical conception.

The point being that reality, traditionally, has shown more expressiveness than 
any of our rule sets.

There are ways to handle the mismatch in expressivity between reality versus 
our rule sets.  Stochasticity is the measure of the extent to which a rule set 
matches a set of patterns.  But Grant's right to qualify that with evolution, 
not because of the way evolution is stochastic, but because evolution requires 
a unit to regularly (or sporadically) sync with its environment.

An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head will 
*always* fail.  It's guaranteed to fail because syncing with the environment 
isn't *built in*.  The sync isn't part of the AI's onto- or phylo-geny.






FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_

Re: [FRIAM] Future of humans and artificial intelligence

[Grant Holland]

Nick,

In science, these three terms are generally interchangeable. Their 
common usage is that they all describe activities, or "events", that are 
"subject to chance". Such activities, events or processes that are 
described by these terms are governed by the laws of probability. They 
all describe activities, events, or "happenings" whose repetitions do 
not always produce the same outcomes even when given the same inputs 
every time (initial conditions). In other words, uncertainty is involved.


However, like most words, these enjoy other usage, meanings, as well. 
For example "random" is sometimes used to mean "disorganized" or 
"lacking in specific pattern". This is a very different meaning than 
"activities that don't always produce the same outcome given the same 
inputs". Consider what a math formula for each of these tow meanings 
wold consist of. One of them would be based on probabilities; but the 
other would involve stationary relationships.


On 8/8/17 5:31 PM, Nick Thompson wrote:


Grant,

I think I know the answer to this question, but want to make sure:

What is the difference beween calling a process “stochastic”, 
“indeterminate”, or “random”?


Nick

Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

http://home.earthlink.net/~nickthompson/naturaldesigns/ 
<http://home.earthlink.net/%7Enickthompson/naturaldesigns/>


*From:*Friam [mailto:friam-boun...@redfish.com] *On Behalf Of *Grant 
Holland

*Sent:* Tuesday, August 08, 2017 6:51 PM
*To:* The Friday Morning Applied Complexity Coffee Group 
<friam@redfish.com>; glen ☣<geprope...@gmail.com>

*Subject:* Re: [FRIAM] Future of humans and artificial intelligence

Thanks for throwing in on this one, Glen. Your thoughts are 
ever-insightful. And ever-entertaining!


For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution /is/ stochastic. (You actually did not 
disagree with me on that. You only said that the reason I was right 
was another one.) A good book on the stochasticity of evolution is 
"Chance and Necessity" by Jacques Monod. (I just finished rereading it 
for the second time. And that proved quite fruitful.)


G.

On 8/8/17 12:44 PM, glen ☣ wrote:

I'm not sure how Asimov intended them.  But the three laws is a trope that clearly 
shows the inadequacy of deontological ethics.  Rules are fine as far as they go.  But 
they don't go very far.  We can see this even in the foundations of mathematics, the 
unification of physics, and polyphenism/robustness in biology.  Von Neumann (Burks) said 
it best when he said: "But in the complicated parts of formal logic it is always one 
order of magnitude harder to tell what an object can do than to produce the object." 
 Or, if you don't like that, you can see the same perspective in his iterative 
construction of sets as an alternative to the classical conception.

The point being that reality, traditionally, has shown more expressiveness 
than any of our rule sets.

There are ways to handle the mismatch in expressivity between reality 
versus our rule sets.  Stochasticity is the measure of the extent to which a 
rule set matches a set of patterns.  But Grant's right to qualify that with 
evolution, not because of the way evolution is stochastic, but because 
evolution requires a unit to regularly (or sporadically) sync with its 
environment.

An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head 
will *always* fail.  It's guaranteed to fail because syncing with the 
environment isn't *built in*.  The sync isn't part of the AI's onto- or 
phylo-geny.




FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove



FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

Frank writes:


"My point was that depth-first and breadth-first can probably serve only as a 
straw-man (straw-men?)."


Unless there is a robust meta-rule (not heuristic) or single deterministic 
search algorithm to rule them all, then wouldn't those other suggestions also 
be straw-men too?   If I knew that there were no noise and the domain was 
continuous and convex, then I wouldn't use a stochastic approach.


Marcus


From: Friam <friam-boun...@redfish.com> on behalf of Frank Wimberly 
<wimber...@gmail.com>
Sent: Tuesday, August 8, 2017 10:15:05 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Future of humans and artificial intelligence

My point was that depth-first and breadth-first can probably serve only as a 
straw-man (straw-men?).

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 10:11 PM, "Marcus Daniels" 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

Frank writes:


"Then there's best-first search, B*, C*, constraint-directed search, etc.  And 
these are just classical search methods."


Connecting this back to evolutionary / stochastic techniques, genetic 
programming is one way to get the best of both approaches, at least in 
principle.   One can expose these human-designed algorithms as predefined 
library functions.  Typically in genetic programming the vocabulary consists of 
simple routines (e.g. arithmetic), conditionals, and recursion.


In practice, this kind of seeding of the solution space can collapse diversity. 
  It is a drag to see tons of compute time spent on a million little 
refinements around an already good solution.  (Yes, I know that solution!)  
More fun to see a set of clumsy solutions turn into to decent-performing but 
weird solutions.  I find my attention is drawn to properties of sub-populations 
and how I can keep the historically good performers _out_.  Not a pure GA, but 
a GA where communities also have fitness functions matching my heavy hand of 
justice..  (If I prove that conservatism just doesn't work, I'll be sure to 
pass it along.)


Marcus



From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Frank Wimberly <wimber...@gmail.com<mailto:wimber...@gmail.com>>
Sent: Tuesday, August 8, 2017 7:57:06 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Future of humans and artificial intelligence

Then there's best-first search, B*, C*, constraint-directed search, etc.  And 
these are just classical search methods.

Feank

Frank Wimberly
Phone (505) 670-9918<tel:(505)%20670-9918>

On Aug 8, 2017 7:20 PM, "Marcus Daniels" 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

"But one problem is that breadth-first and depth-first search are just fast 
ways to find answers."


Just _not_ -- general but not efficient.   [My dog was demanding attention! ]


From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Marcus Daniels <mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>>
Sent: Tuesday, August 8, 2017 6:43:40 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Grant writes:


"On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) "


I think of logic programming systems as a traditional tool of AI research (e.g. 
Prolog, now Curry, similar capabilities implemented in Lisp) from the age 
before the AI winter.  These systems provide a very flexible way to pose 
constraint problems.  But one problem is that breadth-first and depth-first 
search are just fast ways to find answers.  Recent work seems to have shifted 
to SMT solvers and specialized constraint solving algorithms, but these have 
somewhat less expressiveness as programming languages.  Meanwhile, machine 
learning has come on the scene in a big way and tasks traditionally associated 
with old-school AI, like natural language processing, are now matched or even 
dominated using neural nets (LSTM).  I find the range of capabilities provided 
by groups like nlp.stanford.edu<http://nlp.stanford.edu> really impressive -- 
there examples of both approaches (logic programming and machine learning) and 
then don't need to be mutually exclusive.


Quantum annealing is one area where the two may increasingly come together by 
using physical phenomena to accelerate the rate at which high dimensional 
discrete systems can be solved, without relying on fragile or domain-specific 
heuristics.


I often use evolutionary algorithms for hard optimization problems.  Genetic 
algorithms, for example, are robust to  noise (or if you l

Re: [FRIAM] Future of humans and artificial intelligence

[Frank Wimberly]

My point was that depth-first and breadth-first can probably serve only as
a straw-man (straw-men?).

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 10:11 PM, "Marcus Daniels" <mar...@snoutfarm.com> wrote:

> Frank writes:
>
>
> "Then there's best-first search, B*, C*, constraint-directed search,
> etc.  And these are just classical search methods."
>
>
> Connecting this back to evolutionary / stochastic techniques, genetic
> programming is one way to get the best of both approaches, at least in
> principle.   One can expose these human-designed algorithms as predefined
> library functions.  Typically in genetic programming the vocabulary
> consists of simple routines (e.g. arithmetic), conditionals, and recursion.
>
>
> In practice, this kind of seeding of the solution space can collapse
> diversity.   It is a drag to see tons of compute time spent on a million
> little refinements around an already good solution.  (Yes, I know that
> solution!)  More fun to see a set of clumsy solutions turn into to
> decent-performing but weird solutions.  I find my attention is drawn to
> properties of sub-populations and how I can keep the historically good
> performers _out_.  Not a pure GA, but a GA where communities also have
> fitness functions matching my heavy hand of justice..  (If I prove that
> conservatism just doesn't work, I'll be sure to pass it along.)
>
>
> Marcus
>
>
> --
> *From:* Friam <friam-boun...@redfish.com> on behalf of Frank Wimberly <
> wimber...@gmail.com>
> *Sent:* Tuesday, August 8, 2017 7:57:06 PM
> *To:* The Friday Morning Applied Complexity Coffee Group
> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>
> Then there's best-first search, B*, C*, constraint-directed search, etc.
> And these are just classical search methods.
>
> Feank
>
> Frank Wimberly
> Phone (505) 670-9918
>
> On Aug 8, 2017 7:20 PM, "Marcus Daniels" <mar...@snoutfarm.com> wrote:
>
>> "But one problem is that breadth-first and depth-first search are just
>> fast ways to find answers."
>>
>>
>> Just _not_ -- general but not efficient.   [My dog was demanding
>> attention! ]
>> ------
>> *From:* Friam <friam-boun...@redfish.com> on behalf of Marcus Daniels <
>> mar...@snoutfarm.com>
>> *Sent:* Tuesday, August 8, 2017 6:43:40 PM
>> *To:* The Friday Morning Applied Complexity Coffee Group; glen ☣
>> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>>
>>
>> Grant writes:
>>
>>
>> "On the other hand... evolution *is* stochastic. (You actually did not
>> disagree with me on that. You only said that the reason I was right was
>> another one.) "
>>
>>
>> I think of logic programming systems as a traditional tool of AI research
>> (e.g. Prolog, now Curry, similar capabilities implemented in Lisp) from the
>> age before the AI winter.  These systems provide a very flexible way to
>> pose constraint problems.  But one problem is that breadth-first and
>> depth-first search are just fast ways to find answers.  Recent work seems
>> to have shifted to SMT solvers and specialized constraint solving
>> algorithms, but these have somewhat less expressiveness as programming
>> languages.  Meanwhile, machine learning has come on the scene in a big way
>> and tasks traditionally associated with old-school AI, like natural
>> language processing, are now matched or even dominated using neural nets
>> (LSTM).  I find the range of capabilities provided by groups like
>> nlp.stanford.edu really impressive -- there examples of both approaches
>> (logic programming and machine learning) and then don't need to be mutually
>> exclusive.
>>
>>
>> Quantum annealing is one area where the two may increasingly come
>> together by using physical phenomena to accelerate the rate at which high
>> dimensional discrete systems can be solved, without relying on fragile or
>> domain-specific heuristics.
>>
>>
>> I often use evolutionary algorithms for hard optimization problems.
>> Genetic algorithms, for example, are robust to  noise (or if you like
>> ambiguity) in fitness functions, and they are trivial to parallelize.
>>
>>
>> Marcus
>> --
>> *From:* Friam <friam-boun...@redfish.com> on behalf of Grant Holland <
>> grant.holland...@gmail.com>
>> *Sent:* Tuesday, August 8, 2017 4:51:18 PM
>> *To:* The Friday Morning Applied Complexity Coffee Group; glen ☣
>> *Subject:* Re: [

Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

Frank writes:


"Then there's best-first search, B*, C*, constraint-directed search, etc.  And 
these are just classical search methods."


Connecting this back to evolutionary / stochastic techniques, genetic 
programming is one way to get the best of both approaches, at least in 
principle.   One can expose these human-designed algorithms as predefined 
library functions.  Typically in genetic programming the vocabulary consists of 
simple routines (e.g. arithmetic), conditionals, and recursion.


In practice, this kind of seeding of the solution space can collapse diversity. 
  It is a drag to see tons of compute time spent on a million little 
refinements around an already good solution.  (Yes, I know that solution!)  
More fun to see a set of clumsy solutions turn into to decent-performing but 
weird solutions.  I find my attention is drawn to properties of sub-populations 
and how I can keep the historically good performers _out_.  Not a pure GA, but 
a GA where communities also have fitness functions matching my heavy hand of 
justice..  (If I prove that conservatism just doesn't work, I'll be sure to 
pass it along.)


Marcus



From: Friam <friam-boun...@redfish.com> on behalf of Frank Wimberly 
<wimber...@gmail.com>
Sent: Tuesday, August 8, 2017 7:57:06 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] Future of humans and artificial intelligence

Then there's best-first search, B*, C*, constraint-directed search, etc.  And 
these are just classical search methods.

Feank

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 7:20 PM, "Marcus Daniels" 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>> wrote:

"But one problem is that breadth-first and depth-first search are just fast 
ways to find answers."


Just _not_ -- general but not efficient.   [My dog was demanding attention! ]


From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Marcus Daniels <mar...@snoutfarm.com<mailto:mar...@snoutfarm.com>>
Sent: Tuesday, August 8, 2017 6:43:40 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Grant writes:


"On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) "


I think of logic programming systems as a traditional tool of AI research (e.g. 
Prolog, now Curry, similar capabilities implemented in Lisp) from the age 
before the AI winter.  These systems provide a very flexible way to pose 
constraint problems.  But one problem is that breadth-first and depth-first 
search are just fast ways to find answers.  Recent work seems to have shifted 
to SMT solvers and specialized constraint solving algorithms, but these have 
somewhat less expressiveness as programming languages.  Meanwhile, machine 
learning has come on the scene in a big way and tasks traditionally associated 
with old-school AI, like natural language processing, are now matched or even 
dominated using neural nets (LSTM).  I find the range of capabilities provided 
by groups like nlp.stanford.edu<http://nlp.stanford.edu> really impressive -- 
there examples of both approaches (logic programming and machine learning) and 
then don't need to be mutually exclusive.


Quantum annealing is one area where the two may increasingly come together by 
using physical phenomena to accelerate the rate at which high dimensional 
discrete systems can be solved, without relying on fragile or domain-specific 
heuristics.


I often use evolutionary algorithms for hard optimization problems.  Genetic 
algorithms, for example, are robust to  noise (or if you like ambiguity) in 
fitness functions, and they are trivial to parallelize.


Marcus


From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Grant Holland 
<grant.holland...@gmail.com<mailto:grant.holland...@gmail.com>>
Sent: Tuesday, August 8, 2017 4:51:18 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Thanks for throwing in on this one, Glen. Your thoughts are ever-insightful. 
And ever-entertaining!

For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) A 
good book on the stochasticity of evolution is "Chance and Necessity" by 
Jacques Monod. (I just finished rereading it for the second time. And that 
proved quite fruitful.)

G.

On 8/8/17 12:44 PM, glen ☣ wrote:


I'm not sure how Asimov intended them.  But the three laws is a trope that 
cl

Re: [FRIAM] Future of humans and artificial intelligence

[Frank Wimberly]

Then there's best-first search, B*, C*, constraint-directed search, etc.
And these are just classical search methods.

Feank

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 7:20 PM, "Marcus Daniels" <mar...@snoutfarm.com> wrote:

> "But one problem is that breadth-first and depth-first search are just
> fast ways to find answers."
>
>
> Just _not_ -- general but not efficient.   [My dog was demanding
> attention! ]
> --
> *From:* Friam <friam-boun...@redfish.com> on behalf of Marcus Daniels <
> mar...@snoutfarm.com>
> *Sent:* Tuesday, August 8, 2017 6:43:40 PM
> *To:* The Friday Morning Applied Complexity Coffee Group; glen ☣
> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>
>
> Grant writes:
>
>
> "On the other hand... evolution *is* stochastic. (You actually did not
> disagree with me on that. You only said that the reason I was right was
> another one.) "
>
>
> I think of logic programming systems as a traditional tool of AI research
> (e.g. Prolog, now Curry, similar capabilities implemented in Lisp) from the
> age before the AI winter.  These systems provide a very flexible way to
> pose constraint problems.  But one problem is that breadth-first and
> depth-first search are just fast ways to find answers.  Recent work seems
> to have shifted to SMT solvers and specialized constraint solving
> algorithms, but these have somewhat less expressiveness as programming
> languages.  Meanwhile, machine learning has come on the scene in a big way
> and tasks traditionally associated with old-school AI, like natural
> language processing, are now matched or even dominated using neural nets
> (LSTM).  I find the range of capabilities provided by groups like
> nlp.stanford.edu really impressive -- there examples of both approaches
> (logic programming and machine learning) and then don't need to be mutually
> exclusive.
>
>
> Quantum annealing is one area where the two may increasingly come together
> by using physical phenomena to accelerate the rate at which high
> dimensional discrete systems can be solved, without relying on fragile or
> domain-specific heuristics.
>
>
> I often use evolutionary algorithms for hard optimization problems.
> Genetic algorithms, for example, are robust to  noise (or if you like
> ambiguity) in fitness functions, and they are trivial to parallelize.
>
>
> Marcus
> --
> *From:* Friam <friam-boun...@redfish.com> on behalf of Grant Holland <
> grant.holland...@gmail.com>
> *Sent:* Tuesday, August 8, 2017 4:51:18 PM
> *To:* The Friday Morning Applied Complexity Coffee Group; glen ☣
> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>
>
> Thanks for throwing in on this one, Glen. Your thoughts are
> ever-insightful. And ever-entertaining!
>
> For example, I did not know that von Neumann put forth a set theory.
>
> On the other hand... evolution *is* stochastic. (You actually did not
> disagree with me on that. You only said that the reason I was right was
> another one.) A good book on the stochasticity of evolution is "Chance and
> Necessity" by Jacques Monod. (I just finished rereading it for the second
> time. And that proved quite fruitful.)
>
> G.
>
> On 8/8/17 12:44 PM, glen ☣ wrote:
>
>
> I'm not sure how Asimov intended them.  But the three laws is a trope that 
> clearly shows the inadequacy of deontological ethics.  Rules are fine as far 
> as they go.  But they don't go very far.  We can see this even in the 
> foundations of mathematics, the unification of physics, and 
> polyphenism/robustness in biology.  Von Neumann (Burks) said it best when he 
> said: "But in the complicated parts of formal logic it is always one order of 
> magnitude harder to tell what an object can do than to produce the object."  
> Or, if you don't like that, you can see the same perspective in his iterative 
> construction of sets as an alternative to the classical conception.
>
> The point being that reality, traditionally, has shown more expressiveness 
> than any of our rule sets.
>
> There are ways to handle the mismatch in expressivity between reality versus 
> our rule sets.  Stochasticity is the measure of the extent to which a rule 
> set matches a set of patterns.  But Grant's right to qualify that with 
> evolution, not because of the way evolution is stochastic, but because 
> evolution requires a unit to regularly (or sporadically) sync with its 
> environment.
>
> An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head 
> will *always* fail.  It's guaranteed to fail because syncing with the 
> 

Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

"But one problem is that breadth-first and depth-first search are just fast 
ways to find answers."


Just _not_ -- general but not efficient.   [My dog was demanding attention! ]


From: Friam <friam-boun...@redfish.com> on behalf of Marcus Daniels 
<mar...@snoutfarm.com>
Sent: Tuesday, August 8, 2017 6:43:40 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Grant writes:


"On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) "


I think of logic programming systems as a traditional tool of AI research (e.g. 
Prolog, now Curry, similar capabilities implemented in Lisp) from the age 
before the AI winter.  These systems provide a very flexible way to pose 
constraint problems.  But one problem is that breadth-first and depth-first 
search are just fast ways to find answers.  Recent work seems to have shifted 
to SMT solvers and specialized constraint solving algorithms, but these have 
somewhat less expressiveness as programming languages.  Meanwhile, machine 
learning has come on the scene in a big way and tasks traditionally associated 
with old-school AI, like natural language processing, are now matched or even 
dominated using neural nets (LSTM).  I find the range of capabilities provided 
by groups like nlp.stanford.edu really impressive -- there examples of both 
approaches (logic programming and machine learning) and then don't need to be 
mutually exclusive.


Quantum annealing is one area where the two may increasingly come together by 
using physical phenomena to accelerate the rate at which high dimensional 
discrete systems can be solved, without relying on fragile or domain-specific 
heuristics.


I often use evolutionary algorithms for hard optimization problems.  Genetic 
algorithms, for example, are robust to  noise (or if you like ambiguity) in 
fitness functions, and they are trivial to parallelize.


Marcus


From: Friam <friam-boun...@redfish.com> on behalf of Grant Holland 
<grant.holland...@gmail.com>
Sent: Tuesday, August 8, 2017 4:51:18 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Thanks for throwing in on this one, Glen. Your thoughts are ever-insightful. 
And ever-entertaining!

For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) A 
good book on the stochasticity of evolution is "Chance and Necessity" by 
Jacques Monod. (I just finished rereading it for the second time. And that 
proved quite fruitful.)

G.

On 8/8/17 12:44 PM, glen ☣ wrote:


I'm not sure how Asimov intended them.  But the three laws is a trope that 
clearly shows the inadequacy of deontological ethics.  Rules are fine as far as 
they go.  But they don't go very far.  We can see this even in the foundations 
of mathematics, the unification of physics, and polyphenism/robustness in 
biology.  Von Neumann (Burks) said it best when he said: "But in the 
complicated parts of formal logic it is always one order of magnitude harder to 
tell what an object can do than to produce the object."  Or, if you don't like 
that, you can see the same perspective in his iterative construction of sets as 
an alternative to the classical conception.

The point being that reality, traditionally, has shown more expressiveness than 
any of our rule sets.

There are ways to handle the mismatch in expressivity between reality versus 
our rule sets.  Stochasticity is the measure of the extent to which a rule set 
matches a set of patterns.  But Grant's right to qualify that with evolution, 
not because of the way evolution is stochastic, but because evolution requires 
a unit to regularly (or sporadically) sync with its environment.

An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head will 
*always* fail.  It's guaranteed to fail because syncing with the environment 
isn't *built in*.  The sync isn't part of the AI's onto- or phylo-geny.




FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

Grant writes:


"On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) "


I think of logic programming systems as a traditional tool of AI research (e.g. 
Prolog, now Curry, similar capabilities implemented in Lisp) from the age 
before the AI winter.  These systems provide a very flexible way to pose 
constraint problems.  But one problem is that breadth-first and depth-first 
search are just fast ways to find answers.  Recent work seems to have shifted 
to SMT solvers and specialized constraint solving algorithms, but these have 
somewhat less expressiveness as programming languages.  Meanwhile, machine 
learning has come on the scene in a big way and tasks traditionally associated 
with old-school AI, like natural language processing, are now matched or even 
dominated using neural nets (LSTM).  I find the range of capabilities provided 
by groups like nlp.stanford.edu really impressive -- there examples of both 
approaches (logic programming and machine learning) and then don't need to be 
mutually exclusive.


Quantum annealing is one area where the two may increasingly come together by 
using physical phenomena to accelerate the rate at which high dimensional 
discrete systems can be solved, without relying on fragile or domain-specific 
heuristics.


I often use evolutionary algorithms for hard optimization problems.  Genetic 
algorithms, for example, are robust to  noise (or if you like ambiguity) in 
fitness functions, and they are trivial to parallelize.


Marcus


From: Friam <friam-boun...@redfish.com> on behalf of Grant Holland 
<grant.holland...@gmail.com>
Sent: Tuesday, August 8, 2017 4:51:18 PM
To: The Friday Morning Applied Complexity Coffee Group; glen ☣
Subject: Re: [FRIAM] Future of humans and artificial intelligence


Thanks for throwing in on this one, Glen. Your thoughts are ever-insightful. 
And ever-entertaining!

For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) A 
good book on the stochasticity of evolution is "Chance and Necessity" by 
Jacques Monod. (I just finished rereading it for the second time. And that 
proved quite fruitful.)

G.

On 8/8/17 12:44 PM, glen ☣ wrote:


I'm not sure how Asimov intended them.  But the three laws is a trope that 
clearly shows the inadequacy of deontological ethics.  Rules are fine as far as 
they go.  But they don't go very far.  We can see this even in the foundations 
of mathematics, the unification of physics, and polyphenism/robustness in 
biology.  Von Neumann (Burks) said it best when he said: "But in the 
complicated parts of formal logic it is always one order of magnitude harder to 
tell what an object can do than to produce the object."  Or, if you don't like 
that, you can see the same perspective in his iterative construction of sets as 
an alternative to the classical conception.

The point being that reality, traditionally, has shown more expressiveness than 
any of our rule sets.

There are ways to handle the mismatch in expressivity between reality versus 
our rule sets.  Stochasticity is the measure of the extent to which a rule set 
matches a set of patterns.  But Grant's right to qualify that with evolution, 
not because of the way evolution is stochastic, but because evolution requires 
a unit to regularly (or sporadically) sync with its environment.

An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head will 
*always* fail.  It's guaranteed to fail because syncing with the environment 
isn't *built in*.  The sync isn't part of the AI's onto- or phylo-geny.




FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Future of humans and artificial intelligence

[Frank Wimberly]

The latter.  I'm  about to turn off autocorrect. Ironic in the context of a
discussion about the benefits and dangers out AI.

Frank

Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 5:28 PM, "Nick Thompson" <nickthomp...@earthlink.net> wrote:

f.

“space”?



Or was that a correction error arising from trying to write “apace”.

n



Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

http://home.earthlink.net/~nickthompson/naturaldesigns/



*From:* Friam [mailto:friam-boun...@redfish.com] *On Behalf Of *Frank
Wimberly
*Sent:* Tuesday, August 08, 2017 5:32 PM

*To:* The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
*Subject:* Re: [FRIAM] Future of humans and artificial intelligence



Nick,



It's actually more like six thousand pages. However many pages thousands of
rabbis can write in 600 years, more or less.  Deborah found it and posted
it on our refrigerator.



I understand you are recovering space.



Frank

Frank Wimberly
Phone (505) 670-9918



On Aug 8, 2017 3:24 PM, "Nick Thompson" <nickthomp...@earthlink.net> wrote:

I LOVE this, Frank.  How ever did you find it amongst the ten thousand
pages



*Do not be daunted by the enormity of the world's grief.  Do justly, now.
Love mercy, now. Walk humbly, now.  You are not obligated to complete the
work, but neither are you free to abandon it.*



By the way.  Now in my 80th year, I am officially against technology.  I
was OK with everything up through the word processor.  (I hated carbons.)
Everything after that, I could do without.



Really!  What has AI done for me lately?



What  was it Flaubert said about trains?  Something like, they just made it
possible for people to run around faster and faster and be stupid in more
places.



Nick



Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

http://home.earthlink.net/~nickthompson/naturaldesigns/



*From:* Friam [mailto:friam-boun...@redfish.com] *On Behalf Of *Frank
Wimberly
*Sent:* Tuesday, August 08, 2017 1:56 PM
*To:* The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
*Subject:* Re: [FRIAM] Future of humans and artificial intelligence



Talmud:



Do not be daunted by the enormity of the world's grief.  Do justly, now.
Love mercy, now. Walk humbly, now.  You are not obligated to complete the
work, but neither are you free to abandon it.



Plus 10,000 other pages.



Frank Wimberly
Phone (505) 670-9918



On Aug 8, 2017 11:18 AM, "Pamela McCorduck" <pam...@well.com> wrote:

Grant, does it really seem plausible to you that the thousands of crack
researchers at Stanford, Carnegie Mellon, Google, MIT, Cal Berkeley, and
other places have not seen this? And found remedies?



Just for FRIAM’s information, John McCarthy used to call Asimov’s Three
Laws Talmudic. Sorry I don’t know enough about the Talmud to agree or
disagree.









On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com> wrote:



Grant writes:



"Fortunately, the AI folks don't seem to see - yet - that they are
stumbling all over the missing piece: stochastic adaptation. You know, like
in evolution: chance mutations. AI is still down with a bad case of causal
determinism. But I expect they will fairly shortly get over that. Watch out.
"



What is probability, physically?   It could be an illusion and that there
is no such thing as an independent observer.   Even if that is true,
sampling techniques are used in many machine learning algorithms -- it is
not a question of if they work, it is an academic question of why they work.



Marcus
--

*From:* Friam <friam-boun...@redfish.com> on behalf of Grant Holland <
grant.holland...@gmail.com>
*Sent:* Monday, August 7, 2017 11:38:03 PM
*To:* The Friday Morning Applied Complexity Coffee Group; Carl Tollander
*Subject:* Re: [FRIAM] Future of humans and artificial intelligence



That sounds right, Carl. Asimov's three "laws" of robotics are more like
Asimov's three "wishes" for robotics. AI entities are already no longer
servants. They have become machine learners. They have actually learned to
project conditional probability. The cat is out of the barn. Or is it that
the horse is out of the bag?

Whatever. Fortunately, the AI folks don't seem to see - yet - that they are
stumbling all over the missing piece: stochastic adaptation. You know, like
in evolution: chance mutations. AI is still down with a bad case of causal
determinism. But I expect they will fairly shortly get over that. Watch out.

And we still must answer Stephen Hawking's burning question: Is
intelligence a survivable trait?



On 8/7/17 9:54 PM, Carl Tollander wrote:

It seems to me that there are many here in the US who are not entirely on
board with Asimov's First Law of Robotics, at least insofar as it may apply
to themselves, so I suspect notions

Re: [FRIAM] Future of humans and artificial intelligence

[Gillian Densmore]

@Nick that's a fair question. On a pragmatic side not much...yet. However
as I understand it (some) amount of AI was invaluable for making pretty gud
guesses about frustrating issues: Like what the heck is going on with the
weather.
Robots and androids (so far) are better then humans at somethingsand
pretty bad at others. Androids the R2-D2 kind. Basically computers speek
computer better than people
Computers can talk to computers reely reely fast and possibly understand
each other better than humans do. For some (I think) reely awsome things
they've done (so far): Dictation software basically asks your computer to
guess what you're saying (AI) . Mine litterally tries to learn how make
small improvements as I uses it and has gotten a lot better over time.
Their's a video on youtube of some MIT guys that have a robot band playing
disney inspired music. Those robots have tastes and stuff they like playing
more than others. Some better than others.
FWIW what I thought was too cool was some of stuff sounded reely good.
Robots driving cars or helping people could rock.  Or robots exploring
awsome  stuff that humans can't(yet)

Though I haven't a clue how close any of that is yet.  And you are right to
be concerned ^_^

On Tue, Aug 8, 2017 at 4:51 PM, Grant Holland 
wrote:

> Thanks for throwing in on this one, Glen. Your thoughts are
> ever-insightful. And ever-entertaining!
>
> For example, I did not know that von Neumann put forth a set theory.
>
> On the other hand... evolution *is* stochastic. (You actually did not
> disagree with me on that. You only said that the reason I was right was
> another one.) A good book on the stochasticity of evolution is "Chance and
> Necessity" by Jacques Monod. (I just finished rereading it for the second
> time. And that proved quite fruitful.)
>
> G.
>
> On 8/8/17 12:44 PM, glen ☣ wrote:
>
> I'm not sure how Asimov intended them.  But the three laws is a trope that 
> clearly shows the inadequacy of deontological ethics.  Rules are fine as far 
> as they go.  But they don't go very far.  We can see this even in the 
> foundations of mathematics, the unification of physics, and 
> polyphenism/robustness in biology.  Von Neumann (Burks) said it best when he 
> said: "But in the complicated parts of formal logic it is always one order of 
> magnitude harder to tell what an object can do than to produce the object."  
> Or, if you don't like that, you can see the same perspective in his iterative 
> construction of sets as an alternative to the classical conception.
>
> The point being that reality, traditionally, has shown more expressiveness 
> than any of our rule sets.
>
> There are ways to handle the mismatch in expressivity between reality versus 
> our rule sets.  Stochasticity is the measure of the extent to which a rule 
> set matches a set of patterns.  But Grant's right to qualify that with 
> evolution, not because of the way evolution is stochastic, but because 
> evolution requires a unit to regularly (or sporadically) sync with its 
> environment.
>
> An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head 
> will *always* fail.  It's guaranteed to fail because syncing with the 
> environment isn't *built in*.  The sync isn't part of the AI's onto- or 
> phylo-geny.
>
>
>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>

FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Future of humans and artificial intelligence

[Nick Thompson]

Grant, 

 

I think I know the answer to this question, but want to make sure:  

 

What is the difference beween calling a process “stochastic”, “indeterminate”, 
or “random”?  

 

Nick

 

Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

http://home.earthlink.net/~nickthompson/naturaldesigns/

 

From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of Grant Holland
Sent: Tuesday, August 08, 2017 6:51 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>; 
glen ☣ <geprope...@gmail.com>
Subject: Re: [FRIAM] Future of humans and artificial intelligence

 

Thanks for throwing in on this one, Glen. Your thoughts are ever-insightful. 
And ever-entertaining!

For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution is stochastic. (You actually did not disagree 
with me on that. You only said that the reason I was right was another one.) A 
good book on the stochasticity of evolution is "Chance and Necessity" by 
Jacques Monod. (I just finished rereading it for the second time. And that 
proved quite fruitful.)

G.

 

On 8/8/17 12:44 PM, glen ☣ wrote:

 
I'm not sure how Asimov intended them.  But the three laws is a trope that 
clearly shows the inadequacy of deontological ethics.  Rules are fine as far as 
they go.  But they don't go very far.  We can see this even in the foundations 
of mathematics, the unification of physics, and polyphenism/robustness in 
biology.  Von Neumann (Burks) said it best when he said: "But in the 
complicated parts of formal logic it is always one order of magnitude harder to 
tell what an object can do than to produce the object."  Or, if you don't like 
that, you can see the same perspective in his iterative construction of sets as 
an alternative to the classical conception.
 
The point being that reality, traditionally, has shown more expressiveness than 
any of our rule sets.
 
There are ways to handle the mismatch in expressivity between reality versus 
our rule sets.  Stochasticity is the measure of the extent to which a rule set 
matches a set of patterns.  But Grant's right to qualify that with evolution, 
not because of the way evolution is stochastic, but because evolution requires 
a unit to regularly (or sporadically) sync with its environment.
 
An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head will 
*always* fail.  It's guaranteed to fail because syncing with the environment 
isn't *built in*.  The sync isn't part of the AI's onto- or phylo-geny.
 

 


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Future of humans and artificial intelligence

[Nick Thompson]

f.

“space”?

 

Or was that a correction error arising from trying to write “apace”.  

n

 

Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

 <http://home.earthlink.net/~nickthompson/naturaldesigns/> 
http://home.earthlink.net/~nickthompson/naturaldesigns/

 

From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of Frank Wimberly
Sent: Tuesday, August 08, 2017 5:32 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Subject: Re: [FRIAM] Future of humans and artificial intelligence

 

Nick,

 

It's actually more like six thousand pages. However many pages thousands of 
rabbis can write in 600 years, more or less.  Deborah found it and posted it on 
our refrigerator.

 

I understand you are recovering space.

 

Frank

Frank Wimberly
Phone (505) 670-9918

 

On Aug 8, 2017 3:24 PM, "Nick Thompson" <nickthomp...@earthlink.net 
<mailto:nickthomp...@earthlink.net> > wrote:

I LOVE this, Frank.  How ever did you find it amongst the ten thousand 
pages

 

Do not be daunted by the enormity of the world's grief.  Do justly, now.  Love 
mercy, now. Walk humbly, now.  You are not obligated to complete the work, but 
neither are you free to abandon it.

 

By the way.  Now in my 80th year, I am officially against technology.  I was OK 
with everything up through the word processor.  (I hated carbons.) Everything 
after that, I could do without.  

 

Really!  What has AI done for me lately? 

 

What  was it Flaubert said about trains?  Something like, they just made it 
possible for people to run around faster and faster and be stupid in more 
places.  

 

Nick 

 

Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

 <http://home.earthlink.net/~nickthompson/naturaldesigns/> 
http://home.earthlink.net/~nickthompson/naturaldesigns/

 

From: Friam [mailto:friam-boun...@redfish.com 
<mailto:friam-boun...@redfish.com> ] On Behalf Of Frank Wimberly
Sent: Tuesday, August 08, 2017 1:56 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com 
<mailto:friam@redfish.com> >
Subject: Re: [FRIAM] Future of humans and artificial intelligence

 

Talmud:

 

Do not be daunted by the enormity of the world's grief.  Do justly, now.  Love 
mercy, now. Walk humbly, now.  You are not obligated to complete the work, but 
neither are you free to abandon it.

 

Plus 10,000 other pages.

 

Frank Wimberly
Phone (505) 670-9918 <tel:(505)%20670-9918> 

 

On Aug 8, 2017 11:18 AM, "Pamela McCorduck" <pam...@well.com 
<mailto:pam...@well.com> > wrote:

Grant, does it really seem plausible to you that the thousands of crack 
researchers at Stanford, Carnegie Mellon, Google, MIT, Cal Berkeley, and other 
places have not seen this? And found remedies?

 

Just for FRIAM’s information, John McCarthy used to call Asimov’s Three Laws 
Talmudic. Sorry I don’t know enough about the Talmud to agree or disagree.

 

 

 

 

On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com 
<mailto:mar...@snoutfarm.com> > wrote:

 

Grant writes:

 

"Fortunately, the AI folks don't seem to see - yet - that they are stumbling 
all over the missing piece: stochastic adaptation. You know, like in evolution: 
chance mutations. AI is still down with a bad case of causal determinism. But I 
expect they will fairly shortly get over that. Watch out."

 

What is probability, physically?   It could be an illusion and that there is no 
such thing as an independent observer.   Even if that is true, sampling 
techniques are used in many machine learning algorithms -- it is not a question 
of if they work, it is an academic question of why they work.

 

Marcus

  _  

From: Friam <friam-boun...@redfish.com <mailto:friam-boun...@redfish.com> > on 
behalf of Grant Holland <grant.holland...@gmail.com 
<mailto:grant.holland...@gmail.com> >
Sent: Monday, August 7, 2017 11:38:03 PM
To: The Friday Morning Applied Complexity Coffee Group; Carl Tollander
Subject: Re: [FRIAM] Future of humans and artificial intelligence

 

That sounds right, Carl. Asimov's three "laws" of robotics are more like 
Asimov's three "wishes" for robotics. AI entities are already no longer 
servants. They have become machine learners. They have actually learned to 
project conditional probability. The cat is out of the barn. Or is it that the 
horse is out of the bag?  

Whatever. Fortunately, the AI folks don't seem to see - yet - that they are 
stumbling all over the missing piece: stochastic adaptation. You know, like in 
evolution: chance mutations. AI is still down with a bad case of causal 
determinism. But I expect they will fairly shortly get over that. Watch out.

And we still must answer Stephen Hawking's burning question: Is intelligence a 
survivable trait?

 

On 8/7/17 9:54 PM, Carl Tollander 

Re: [FRIAM] Future of humans and artificial intelligence

[Grant Holland]

Thanks for throwing in on this one, Glen. Your thoughts are 
ever-insightful. And ever-entertaining!


For example, I did not know that von Neumann put forth a set theory.

On the other hand... evolution /is/ stochastic. (You actually did not 
disagree with me on that. You only said that the reason I was right was 
another one.) A good book on the stochasticity of evolution is "Chance 
and Necessity" by Jacques Monod. (I just finished rereading it for the 
second time. And that proved quite fruitful.)


G.


On 8/8/17 12:44 PM, glen ☣ wrote:

I'm not sure how Asimov intended them.  But the three laws is a trope that clearly shows 
the inadequacy of deontological ethics.  Rules are fine as far as they go.  But they 
don't go very far.  We can see this even in the foundations of mathematics, the 
unification of physics, and polyphenism/robustness in biology.  Von Neumann (Burks) said 
it best when he said: "But in the complicated parts of formal logic it is always one 
order of magnitude harder to tell what an object can do than to produce the object." 
 Or, if you don't like that, you can see the same perspective in his iterative 
construction of sets as an alternative to the classical conception.

The point being that reality, traditionally, has shown more expressiveness than 
any of our rule sets.

There are ways to handle the mismatch in expressivity between reality versus 
our rule sets.  Stochasticity is the measure of the extent to which a rule set 
matches a set of patterns.  But Grant's right to qualify that with evolution, 
not because of the way evolution is stochastic, but because evolution requires 
a unit to regularly (or sporadically) sync with its environment.

An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head will 
*always* fail.  It's guaranteed to fail because syncing with the environment 
isn't *built in*.  The sync isn't part of the AI's onto- or phylo-geny.




FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

Re: [FRIAM] Future of humans and artificial intelligence

[Nick Thompson]

I LOVE this, Frank.  How ever did you find it amongst the ten thousand 
pages

 

Do not be daunted by the enormity of the world's grief.  Do justly, now.  Love 
mercy, now. Walk humbly, now.  You are not obligated to complete the work, but 
neither are you free to abandon it.

 

By the way.  Now in my 80th year, I am officially against technology.  I was OK 
with everything up through the word processor.  (I hated carbons.) Everything 
after that, I could do without.  

 

Really!  What has AI done for me lately? 

 

What  was it Flaubert said about trains?  Something like, they just made it 
possible for people to run around faster and faster and be stupid in more 
places.  

 

Nick 

 

Nicholas S. Thompson

Emeritus Professor of Psychology and Biology

Clark University

 <http://home.earthlink.net/~nickthompson/naturaldesigns/> 
http://home.earthlink.net/~nickthompson/naturaldesigns/

 

From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of Frank Wimberly
Sent: Tuesday, August 08, 2017 1:56 PM
To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Subject: Re: [FRIAM] Future of humans and artificial intelligence

 

Talmud:

 

Do not be daunted by the enormity of the world's grief.  Do justly, now.  Love 
mercy, now. Walk humbly, now.  You are not obligated to complete the work, but 
neither are you free to abandon it.

 

Plus 10,000 other pages.

 

Frank Wimberly
Phone (505) 670-9918

 

On Aug 8, 2017 11:18 AM, "Pamela McCorduck" <pam...@well.com 
<mailto:pam...@well.com> > wrote:

Grant, does it really seem plausible to you that the thousands of crack 
researchers at Stanford, Carnegie Mellon, Google, MIT, Cal Berkeley, and other 
places have not seen this? And found remedies?

 

Just for FRIAM’s information, John McCarthy used to call Asimov’s Three Laws 
Talmudic. Sorry I don’t know enough about the Talmud to agree or disagree.

 

 

 

 

On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com 
<mailto:mar...@snoutfarm.com> > wrote:

 

Grant writes:

 

"Fortunately, the AI folks don't seem to see - yet - that they are stumbling 
all over the missing piece: stochastic adaptation. You know, like in evolution: 
chance mutations. AI is still down with a bad case of causal determinism. But I 
expect they will fairly shortly get over that. Watch out."

 

What is probability, physically?   It could be an illusion and that there is no 
such thing as an independent observer.   Even if that is true, sampling 
techniques are used in many machine learning algorithms -- it is not a question 
of if they work, it is an academic question of why they work.

 

Marcus

  _  

From: Friam <friam-boun...@redfish.com <mailto:friam-boun...@redfish.com> > on 
behalf of Grant Holland <grant.holland...@gmail.com 
<mailto:grant.holland...@gmail.com> >
Sent: Monday, August 7, 2017 11:38:03 PM
To: The Friday Morning Applied Complexity Coffee Group; Carl Tollander
Subject: Re: [FRIAM] Future of humans and artificial intelligence

 

That sounds right, Carl. Asimov's three "laws" of robotics are more like 
Asimov's three "wishes" for robotics. AI entities are already no longer 
servants. They have become machine learners. They have actually learned to 
project conditional probability. The cat is out of the barn. Or is it that the 
horse is out of the bag?  

Whatever. Fortunately, the AI folks don't seem to see - yet - that they are 
stumbling all over the missing piece: stochastic adaptation. You know, like in 
evolution: chance mutations. AI is still down with a bad case of causal 
determinism. But I expect they will fairly shortly get over that. Watch out.

And we still must answer Stephen Hawking's burning question: Is intelligence a 
survivable trait?

 

On 8/7/17 9:54 PM, Carl Tollander wrote:

It seems to me that there are many here in the US who are not entirely on board 
with Asimov's First Law of Robotics, at least insofar as it may apply to 
themselves, so I suspect notions of "reining it in" are probably not going to 
fly.

 

 

 

 

On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez <alfr...@covaleda.co 
<mailto:alfr...@covaleda.co> > wrote:

Future will be quite interesting. How will be the human being of the future? 
For sure not a human being in the way we know.

 

http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158



FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove

 

 


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John'

Re: [FRIAM] Future of humans and artificial intelligence

[glen ☣]

I'm not sure how Asimov intended them.  But the three laws is a trope that 
clearly shows the inadequacy of deontological ethics.  Rules are fine as far as 
they go.  But they don't go very far.  We can see this even in the foundations 
of mathematics, the unification of physics, and polyphenism/robustness in 
biology.  Von Neumann (Burks) said it best when he said: "But in the 
complicated parts of formal logic it is always one order of magnitude harder to 
tell what an object can do than to produce the object."  Or, if you don't like 
that, you can see the same perspective in his iterative construction of sets as 
an alternative to the classical conception.

The point being that reality, traditionally, has shown more expressiveness than 
any of our rule sets.

There are ways to handle the mismatch in expressivity between reality versus 
our rule sets.  Stochasticity is the measure of the extent to which a rule set 
matches a set of patterns.  But Grant's right to qualify that with evolution, 
not because of the way evolution is stochastic, but because evolution requires 
a unit to regularly (or sporadically) sync with its environment.

An AI (or a rule-obsessed human) that sprouts fully formed from Zeus' head will 
*always* fail.  It's guaranteed to fail because syncing with the environment 
isn't *built in*.  The sync isn't part of the AI's onto- or phylo-geny.

-- 
☣ glen


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[Grant Holland]

Pamela,

I expect that they have! And I certainly hope so. I simply have not 
found them yet after some earnest looking. Can you please send me some 
references?? Right now I suspect that the heart of machine learning has 
the pearl, and I'm just now turning there.


And I'm optimistically suspicious that those entropic functionals that 
you find in information theory and that are built on top of conditional 
probability (relative entropy, mutual information, conditional entropy, 
entropy rate, etc.) hold promise...and that at the heart of machine 
learning they lay lurking - or could.


Anyway, thx for the note; and /please/ send me any related referernces!

Grant


On 8/8/17 11:20 AM, Pamela McCorduck wrote:
Grant, does it really seem plausible to you that the thousands of 
crack researchers at Stanford, Carnegie Mellon, Google, MIT, Cal 
Berkeley, and other places have not seen this? And found remedies?


Just for FRIAM’s information, John McCarthy used to call Asimov’s 
Three Laws Talmudic. Sorry I don’t know enough about the Talmud to 
agree or disagree.





On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com 
<mailto:mar...@snoutfarm.com>> wrote:


Grant writes:

"Fortunately, the AI folks don't seem to see - yet - that they are 
stumbling all over the missing piece: stochastic adaptation. You 
know, like in evolution: chance mutations. AI is still down with a 
bad case of causal determinism. But I expect they will fairly shortly 
get over that. Watch out."


What is probability, physically?   It could be an illusion and that 
there is no such thing as an independent observer.   Even if that is 
true, sampling techniques are used in many machine learning 
algorithms -- it is not a question of if they work, it is an academic 
question of why they work.


Marcus

*From:*Friam <friam-boun...@redfish.com 
<mailto:friam-boun...@redfish.com>> on behalf of Grant Holland 
<grant.holland...@gmail.com <mailto:grant.holland...@gmail.com>>

*Sent:*Monday, August 7, 2017 11:38:03 PM
*To:*The Friday Morning Applied Complexity Coffee Group; Carl Tollander
*Subject:*Re: [FRIAM] Future of humans and artificial intelligence
That sounds right, Carl. Asimov's three "laws" of robotics are more 
like Asimov's three "wishes" for robotics. AI entities are already no 
longer servants. They have become machine learners. They have 
actually learned to project conditional probability. The cat is out 
of the barn. Or is it that the horse is out of the bag?
Whatever. Fortunately, the AI folks don't seem to see - yet - that 
they are stumbling all over the missing piece: stochastic adaptation. 
You know, like in evolution: chance mutations. AI is still down with 
a bad case of causal determinism. But I expect they will fairly 
shortly get over that. Watch out.
And we still must answer Stephen Hawking's burning question: Is 
intelligence a survivable trait?


On 8/7/17 9:54 PM, Carl Tollander wrote:
It seems to me that there are many here in the US who are not 
entirely on board with Asimov's First Law of Robotics, at least 
insofar as it may apply to themselves, so I suspect notions of 
"reining it in" are probably not going to fly.





On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda 
Vélez<alfr...@covaleda.co <mailto:alfr...@covaleda.co>>wrote:


Future will be quite interesting. How will be the human being of
the future? For sure not a human being in the way we know.


http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158

<http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158>


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Meets Fridays 9a-11:30 at cafe at St. John's College
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FRIAM Applied Complexity Group listserv
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Re: [FRIAM] Future of humans and artificial intelligence

[Frank Wimberly]

Talmud:

Do not be daunted by the enormity of the world's grief.  Do justly, now.
Love mercy, now. Walk humbly, now.  You are not obligated to complete the
work, but neither are you free to abandon it.

Plus 10,000 other pages.


Frank Wimberly
Phone (505) 670-9918

On Aug 8, 2017 11:18 AM, "Pamela McCorduck" <pam...@well.com> wrote:

> Grant, does it really seem plausible to you that the thousands of crack
> researchers at Stanford, Carnegie Mellon, Google, MIT, Cal Berkeley, and
> other places have not seen this? And found remedies?
>
> Just for FRIAM’s information, John McCarthy used to call Asimov’s Three
> Laws Talmudic. Sorry I don’t know enough about the Talmud to agree or
> disagree.
>
>
>
>
> On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com> wrote:
>
> Grant writes:
>
> "Fortunately, the AI folks don't seem to see - yet - that they are
> stumbling all over the missing piece: stochastic adaptation. You know, like
> in evolution: chance mutations. AI is still down with a bad case of causal
> determinism. But I expect they will fairly shortly get over that. Watch out.
> "
>
> What is probability, physically?   It could be an illusion and that there
> is no such thing as an independent observer.   Even if that is true,
> sampling techniques are used in many machine learning algorithms -- it is
> not a question of if they work, it is an academic question of why they work.
>
> Marcus
> --
> *From:* Friam <friam-boun...@redfish.com> on behalf of Grant Holland <
> grant.holland...@gmail.com>
> *Sent:* Monday, August 7, 2017 11:38:03 PM
> *To:* The Friday Morning Applied Complexity Coffee Group; Carl Tollander
> *Subject:* Re: [FRIAM] Future of humans and artificial intelligence
>
> That sounds right, Carl. Asimov's three "laws" of robotics are more like
> Asimov's three "wishes" for robotics. AI entities are already no longer
> servants. They have become machine learners. They have actually learned to
> project conditional probability. The cat is out of the barn. Or is it that
> the horse is out of the bag?
> Whatever. Fortunately, the AI folks don't seem to see - yet - that they
> are stumbling all over the missing piece: stochastic adaptation. You know,
> like in evolution: chance mutations. AI is still down with a bad case of
> causal determinism. But I expect they will fairly shortly get over that.
> Watch out.
> And we still must answer Stephen Hawking's burning question: Is
> intelligence a survivable trait?
>
> On 8/7/17 9:54 PM, Carl Tollander wrote:
>
> It seems to me that there are many here in the US who are not entirely on
> board with Asimov's First Law of Robotics, at least insofar as it may apply
> to themselves, so I suspect notions of "reining it in" are probably not
> going to fly.
>
>
>
>
> On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez <
> alfr...@covaleda.co> wrote:
>
>> Future will be quite interesting. How will be the human being of the
>> future? For sure not a human being in the way we know.
>>
>> http://m.eltiempo.com/tecnosfera/novedades-tecnologia/
>> peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158
>>
>> 
>> FRIAM Applied Complexity Group listserv
>> Meets Fridays 9a-11:30 at cafe at St. John's College
>> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
>> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>>
>
>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>
>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
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>

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Re: [FRIAM] Future of humans and artificial intelligence

[Pamela McCorduck]

Grant, does it really seem plausible to you that the thousands of crack 
researchers at Stanford, Carnegie Mellon, Google, MIT, Cal Berkeley, and other 
places have not seen this? And found remedies?

Just for FRIAM’s information, John McCarthy used to call Asimov’s Three Laws 
Talmudic. Sorry I don’t know enough about the Talmud to agree or disagree.




> On Aug 8, 2017, at 1:42 AM, Marcus Daniels <mar...@snoutfarm.com> wrote:
> 
> Grant writes:
> 
> "Fortunately, the AI folks don't seem to see - yet - that they are stumbling 
> all over the missing piece: stochastic adaptation. You know, like in 
> evolution: chance mutations. AI is still down with a bad case of causal 
> determinism. But I expect they will fairly shortly get over that. Watch out."
> 
> What is probability, physically?   It could be an illusion and that there is 
> no such thing as an independent observer.   Even if that is true, sampling 
> techniques are used in many machine learning algorithms -- it is not a 
> question of if they work, it is an academic question of why they work.
> 
> Marcus
> From: Friam <friam-boun...@redfish.com <mailto:friam-boun...@redfish.com>> on 
> behalf of Grant Holland <grant.holland...@gmail.com 
> <mailto:grant.holland...@gmail.com>>
> Sent: Monday, August 7, 2017 11:38:03 PM
> To: The Friday Morning Applied Complexity Coffee Group; Carl Tollander
> Subject: Re: [FRIAM] Future of humans and artificial intelligence
>  
> That sounds right, Carl. Asimov's three "laws" of robotics are more like 
> Asimov's three "wishes" for robotics. AI entities are already no longer 
> servants. They have become machine learners. They have actually learned to 
> project conditional probability. The cat is out of the barn. Or is it that 
> the horse is out of the bag?  
> Whatever. Fortunately, the AI folks don't seem to see - yet - that they are 
> stumbling all over the missing piece: stochastic adaptation. You know, like 
> in evolution: chance mutations. AI is still down with a bad case of causal 
> determinism. But I expect they will fairly shortly get over that. Watch out.
> And we still must answer Stephen Hawking's burning question: Is intelligence 
> a survivable trait?
> 
> On 8/7/17 9:54 PM, Carl Tollander wrote:
>> It seems to me that there are many here in the US who are not entirely on 
>> board with Asimov's First Law of Robotics, at least insofar as it may apply 
>> to themselves, so I suspect notions of "reining it in" are probably not 
>> going to fly.
>> 
>> 
>> 
>> 
>> On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez <alfr...@covaleda.co 
>> <mailto:alfr...@covaleda.co>> wrote:
>> Future will be quite interesting. How will be the human being of the future? 
>> For sure not a human being in the way we know.
>> 
>> http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158
>>  
>> <http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158>
>> 
>> 
>> FRIAM Applied Complexity Group listserv
>> Meets Fridays 9a-11:30 at cafe at St. John's College
>> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com 
>> <http://redfish.com/mailman/listinfo/friam_redfish.com>
>> FRIAM-COMIC http://friam-comic.blogspot.com/ 
>> <http://friam-comic.blogspot.com/> by Dr. Strangelove
>> 
>> 
>> 
>> 
>> FRIAM Applied Complexity Group listserv
>> Meets Fridays 9a-11:30 at cafe at St. John's College
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>> <http://friam-comic.blogspot.com/> by Dr. Strangelove
> 
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com 
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> <http://friam-comic.blogspot.com/> by Dr. Strangelove


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Re: [FRIAM] Future of humans and artificial intelligence

[Grant Holland]

Marcus,
Good points, all. I suggest you turn to the Copenhagen interpretation of 
Quantum Mechanics (the "usual interpretation") for musings on your very 
pertinent question about "Why probabilities in the physical world".

Although, I'm sure you have already looked there.
Of course, the Copenhagen guys (Heisenberg, Born, etc.) don't really try 
to answer your question either - opting instead to say that theirs is 
merely a theory, a model. And, of course, they are right.
On the other hand, other physicists (i.e. de Broglie, Bohm, Einstein and 
others) have spent a century trying to defend causal determinism against 
the Copenhagen interpretation. These days the defenders of the faith 
have resorted to philosophy over this issue and are considering the 
"ontic" versus the "epistemic". And yet, Copenhagen is still referred to 
as "the usual interpretation", and when QM is taught today, I think, it 
is essentially Copenhagen or some derivative of it. Perhaps Bell's 
theorem has contributed to the longevity of the Copenhagen perspective.



On 8/8/17 2:42 AM, Marcus Daniels wrote:


Grant writes:


"Fortunately, the AI folks don't seem to see - yet - that they are 
stumbling all over the missing piece: stochastic adaptation. You know, 
like in evolution: chance mutations. AI is still down with a bad case 
of causal determinism. But I expect they will fairly shortly get over 
that. Watch out."



What is probability, physically?   It could be an illusion and that 
there is no such thing as an independent observer. Even if that is 
true, sampling techniques are used in many machine learning algorithms 
-- it is not a question of if they work, it is an academic question of 
why they work.



Marcus


*From:* Friam <friam-boun...@redfish.com> on behalf of Grant Holland 
<grant.holland...@gmail.com>

*Sent:* Monday, August 7, 2017 11:38:03 PM
*To:* The Friday Morning Applied Complexity Coffee Group; Carl Tollander
*Subject:* Re: [FRIAM] Future of humans and artificial intelligence

That sounds right, Carl. Asimov's three "laws" of robotics are more 
like Asimov's three "wishes" for robotics. AI entities are already no 
longer servants. They have become machine learners. They have actually 
learned to project conditional probability. The cat is out of the 
barn. Or is it that the horse is out of the bag?


Whatever. Fortunately, the AI folks don't seem to see - yet - that 
they are stumbling all over the missing piece: stochastic adaptation. 
You know, like in evolution: chance mutations. AI is still down with a 
bad case of causal determinism. But I expect they will fairly shortly 
get over that. Watch out.


And we still must answer Stephen Hawking's burning question: Is 
intelligence a survivable trait?



On 8/7/17 9:54 PM, Carl Tollander wrote:
It seems to me that there are many here in the US who are not 
entirely on board with Asimov's First Law of Robotics, at least 
insofar as it may apply to themselves, so I suspect notions of 
"reining it in" are probably not going to fly.





On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez 
<alfr...@covaleda.co <mailto:alfr...@covaleda.co>> wrote:


Future will be quite interesting. How will be the human being of
the future? For sure not a human being in the way we know.


http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158

<http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158>


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Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

Grant writes:


"Fortunately, the AI folks don't seem to see - yet - that they are stumbling 
all over the missing piece: stochastic adaptation. You know, like in evolution: 
chance mutations. AI is still down with a bad case of causal determinism. But I 
expect they will fairly shortly get over that. Watch out."


What is probability, physically?   It could be an illusion and that there is no 
such thing as an independent observer.   Even if that is true, sampling 
techniques are used in many machine learning algorithms -- it is not a question 
of if they work, it is an academic question of why they work.


Marcus


From: Friam <friam-boun...@redfish.com> on behalf of Grant Holland 
<grant.holland...@gmail.com>
Sent: Monday, August 7, 2017 11:38:03 PM
To: The Friday Morning Applied Complexity Coffee Group; Carl Tollander
Subject: Re: [FRIAM] Future of humans and artificial intelligence


That sounds right, Carl. Asimov's three "laws" of robotics are more like 
Asimov's three "wishes" for robotics. AI entities are already no longer 
servants. They have become machine learners. They have actually learned to 
project conditional probability. The cat is out of the barn. Or is it that the 
horse is out of the bag?

Whatever. Fortunately, the AI folks don't seem to see - yet - that they are 
stumbling all over the missing piece: stochastic adaptation. You know, like in 
evolution: chance mutations. AI is still down with a bad case of causal 
determinism. But I expect they will fairly shortly get over that. Watch out.

And we still must answer Stephen Hawking's burning question: Is intelligence a 
survivable trait?

On 8/7/17 9:54 PM, Carl Tollander wrote:
It seems to me that there are many here in the US who are not entirely on board 
with Asimov's First Law of Robotics, at least insofar as it may apply to 
themselves, so I suspect notions of "reining it in" are probably not going to 
fly.




On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez 
<alfr...@covaleda.co<mailto:alfr...@covaleda.co>> wrote:
Future will be quite interesting. How will be the human being of the future? 
For sure not a human being in the way we know.

http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158


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Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[Grant Holland]

That sounds right, Carl. Asimov's three "laws" of robotics are more like 
Asimov's three "wishes" for robotics. AI entities are already no longer 
servants. They have become machine learners. They have actually learned 
to project conditional probability. The cat is out of the barn. Or is it 
that the horse is out of the bag?


Whatever. Fortunately, the AI folks don't seem to see - yet - that they 
are stumbling all over the missing piece: stochastic adaptation. You 
know, like in evolution: chance mutations. AI is still down with a bad 
case of causal determinism. But I expect they will fairly shortly get 
over that. Watch out.


And we still must answer Stephen Hawking's burning question: Is 
intelligence a survivable trait?



On 8/7/17 9:54 PM, Carl Tollander wrote:
It seems to me that there are many here in the US who are not entirely 
on board with Asimov's First Law of Robotics, at least insofar as it 
may apply to themselves, so I suspect notions of "reining it in" are 
probably not going to fly.





On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez 
> wrote:


Future will be quite interesting. How will be the human being of
the future? For sure not a human being in the way we know.


http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158




FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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 by Dr. Strangelove





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Re: [FRIAM] Future of humans and artificial intelligence

[Carl Tollander]

The notion of AI's as necessarily sentient seems a bit of a jump.

However, I see a difference between an AI augmented sentience (a la a
spiffy AR) and a bunch of possibly sentient AI's flying in formation (a la
a murder of crows or a pack of wolves).

Going further out into Niel Stephenson's D.O.D.O. fictional world, all
sentients might be flying in formation with different selves in adjacent
possibility spaces (hi, Stu?), feeding off the information gradients.

However, my original point was that people project their notion of self
onto AI's, so narratives about self will predominate in any regulatory
scheme.


On Mon, Aug 7, 2017 at 10:20 PM, Marcus Daniels 
wrote:

> Here in the US there are many human animals to reign-in first.  Sentients
> will need to stick together and accept the help they can get!
>
> Sent from my iPhone
>
> On Aug 7, 2017, at 9:54 PM, Carl Tollander  wrote:
>
> It seems to me that there are many here in the US who are not entirely on
> board with Asimov's First Law of Robotics, at least insofar as it may apply
> to themselves, so I suspect notions of "reining it in" are probably not
> going to fly.
>
>
>
>
> On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez <
> alfr...@covaleda.co> wrote:
>
>> Future will be quite interesting. How will be the human being of the
>> future? For sure not a human being in the way we know.
>>
>> http://m.eltiempo.com/tecnosfera/novedades-tecnologia/
>> peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158
>>
>> 
>> FRIAM Applied Complexity Group listserv
>> Meets Fridays 9a-11:30 at cafe at St. John's College
>> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
>> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>

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Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[Marcus Daniels]

Here in the US there are many human animals to reign-in first.  Sentients will 
need to stick together and accept the help they can get!

Sent from my iPhone

On Aug 7, 2017, at 9:54 PM, Carl Tollander 
> wrote:

It seems to me that there are many here in the US who are not entirely on board 
with Asimov's First Law of Robotics, at least insofar as it may apply to 
themselves, so I suspect notions of "reining it in" are probably not going to 
fly.




On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez 
> wrote:
Future will be quite interesting. How will be the human being of the future? 
For sure not a human being in the way we know.

http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158


FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove


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Meets Fridays 9a-11:30 at cafe at St. John's College
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FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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Re: [FRIAM] Future of humans and artificial intelligence

[Carl Tollander]

It seems to me that there are many here in the US who are not entirely on
board with Asimov's First Law of Robotics, at least insofar as it may apply
to themselves, so I suspect notions of "reining it in" are probably not
going to fly.




On Mon, Aug 7, 2017 at 1:57 AM, Alfredo Covaleda Vélez 
wrote:

> Future will be quite interesting. How will be the human being of the
> future? For sure not a human being in the way we know.
>
> http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-
> de-la-inteligencia-artificial-para-los-humanos-117158
>
> 
> FRIAM Applied Complexity Group listserv
> Meets Fridays 9a-11:30 at cafe at St. John's College
> to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
> FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove
>

FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
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[FRIAM] Future of humans and artificial intelligence

[Alfredo Covaleda Vélez]

Future will be quite interesting. How will be the human being of the
future? For sure not a human being in the way we know.

http://m.eltiempo.com/tecnosfera/novedades-tecnologia/peligros-y-avances-de-la-inteligencia-artificial-para-los-humanos-117158

FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/ by Dr. Strangelove