AI learns to design

[Jan Panteltje]

https://www.sciencedaily.com/releases/2019/11/191106144932.htm

What is funny is the sort of lame excuse at the end:
"It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "


It is totally obvious at least to me that a more complex neural net can do more.

This is going to be bigger and bigger..


Paper:
https://arxiv.org/abs/1907.11813

This is also why I an sceptical of too much math and things like El Tea Spies,
I design differently.

Rats :-)

[jla...@highlandsniptechnology.com]

The number of circuits that one can make from, say, thirty 4-pin parts
probably exceeds the number of electrons in the universe. A human
brain can explore an incredibly large possibility space that no
procedural computer program could ever approach.

But LT Spice is great for evaluating and evolving ideas. It
complements the more creative but less quantitative brain. I sometimes
design by fiddling in Spice, letting it check the reasonableness of my
instincts.

I have a couple of recent designs that evolved in LT Spice and work
great, that I still don't understand.



--

John Larkin Highland Technology, Inc

lunatic fringe electronics

[tabb...@gmail.com]

On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
> <pNaOnSt...@yahoo.com> wrote:
>
> > https://www.sciencedaily.com/releases/2019/11/191106144932.htm
> >
> >What is funny is the sort of lame excuse at the end:
> > "It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "
> >
> >
> >It is totally obvious at least to me that a more complex neural net can do more.
> >
> >This is going to be bigger and bigger..
> >
> >
> >Paper:
> > https://arxiv.org/abs/1907.11813
> >
> >This is also why I an sceptical of too much math and things like El Tea Spies,
> >I design differently.
> >
> >Rats :-)
> >
>
> The number of circuits that one can make from, say, thirty 4-pin parts
> probably exceeds the number of electrons in the universe. A human
> brain can explore an incredibly large possibility space that no
> procedural computer program could ever approach.

On the contrary computers excel at assessing far more designs than we can because they're fast & tireless. We can rule out most options very quickly so we don't need to spend time assessing them. Which is faster? Depends on what's being assessed and how.

> But LT Spice is great for evaluating and evolving ideas. It
> complements the more creative but less quantitative brain. I sometimes
> design by fiddling in Spice, letting it check the reasonableness of my
> instincts.
>
> I have a couple of recent designs that evolved in LT Spice and work
> great, that I still don't understand.

Spice sims of random circuits won't design anything useful, but harvest the unused cycles of half the PCs on the internet and it becomes at least possible. Maybe in 50 years we'll all be obsolete.


NT

[jla...@highlandsniptechnology.com]

On Sat, 9 Nov 2019 19:04:57 -0800 (PST), tabb...@gmail.com wrote:

>On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
>> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
>> <pNaOnSt...@yahoo.com> wrote:
>>
>> > https://www.sciencedaily.com/releases/2019/11/191106144932.htm
>> >
>> >What is funny is the sort of lame excuse at the end:
>> > "It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "
>> >
>> >
>> >It is totally obvious at least to me that a more complex neural net can do more.
>> >
>> >This is going to be bigger and bigger..
>> >
>> >
>> >Paper:
>> > https://arxiv.org/abs/1907.11813
>> >
>> >This is also why I an sceptical of too much math and things like El Tea Spies,
>> >I design differently.
>> >
>> >Rats :-)
>> >
>>
>> The number of circuits that one can make from, say, thirty 4-pin parts
>> probably exceeds the number of electrons in the universe. A human
>> brain can explore an incredibly large possibility space that no
>> procedural computer program could ever approach.
>
>On the contrary computers excel at assessing far more designs than we can because they're fast & tireless. We can rule out most options very quickly so we don't need to spend time assessing them. Which is faster? Depends on what's being assessed and how.

Conventional computers are horribly slow. They can't even drive a car
safely.

Brains are probably quantum computers that can simultaneously
superimpose enormousely large possibility sets and collapse the good
ones.

>
>
>> But LT Spice is great for evaluating and evolving ideas. It
>> complements the more creative but less quantitative brain. I sometimes
>> design by fiddling in Spice, letting it check the reasonableness of my
>> instincts.
>>
>> I have a couple of recent designs that evolved in LT Spice and work
>> great, that I still don't understand.
>
>Spice sims of random circuits won't design anything useful, but harvest the unused cycles of half the PCs on the internet and it becomes at least possible. Maybe in 50 years we'll all be obsolete.
>
>
>NT

There have been attempts to design with computers, or to do the easier
task, optimize a given circuit. Not much progress so far.

[bitrex]

Using AI to "evolve" designs on real FPGAs finds flaws in the particular
devices that it exploits, like building ring oscillators that aren't
connected to any power supply net and run on parasitics.

[bitrex]

That is to say if you only tell the algorithm to use "minimum number of
gates" and don't enforce a rule that they must all be powered in some
way it will sometimes find a minimum gate solution regardless that
works, on one particular device, for one particular task. "Life finds a way"

[Jan Panteltje]

Indeed, is that good or bad?
It may fail if the dies change..
I had those ring oscillators by accident...

[Jan Panteltje]

>On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
><pNaOnSt...@yahoo.com> wrote:
>
>> https://www.sciencedaily.com/releases/2019/11/191106144932.htm
>>
>>What is funny is the sort of lame excuse at the end:
>> "It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "
>>
>>
>>It is totally obvious at least to me that a more complex neural net can do more.
>>
>>This is going to be bigger and bigger..
>>
>>
>>Paper:
>> https://arxiv.org/abs/1907.11813
>>
>>This is also why I an sceptical of too much math and things like El Tea Spies,
>>I design differently.
>>
>>Rats :-)
>>
>
>The number of circuits that one can make from, say, thirty 4-pin parts
>probably exceeds the number of electrons in the universe. A human
>brain can explore an incredibly large possibility space that no
>procedural computer program could ever approach.

Indeed, but neural nets do not work that way, although you can emulate it somehow in a procedural way.
In the beginning it is about non-linear weights between elements where data is stored in those weights
(variables if you will).
The learning process changes those weights but the hardware complexity stays the same
while getting ever better 'answers'.
(This put right? I did some neural net programming years ago,
things have evolved enormous after that).

Our brains only uses a very small subset of its neurons for 'design'.

>But LT Spice is great for evaluating and evolving ideas. It
>complements the more creative but less quantitative brain. I sometimes
>design by fiddling in Spice, letting it check the reasonableness of my
>instincts.
>
>I have a couple of recent designs that evolved in LT Spice and work
>great, that I still don't understand.

Yes, but I still like to understand what I am doing :-)
OTOH how much in depth _do_ we understand, we do no even know everything about the electron and even less about the universe.
So from that realization we will always be tinkering.
The steam engine that started the industrial revolution was also the result of just tinkering ..
AI can do that without getting tired around the clock...

I like LTspice for filters etc, but there are many good filter design programs on the web.

Also I do think much in blocks that I have ever designed and build and chips I have used.
Also more and more is becoming software.

AI designing software???

Now that could create fun solutions.

[bitrex]

If you'd want a design that translates to all devices you'd have to run
your genetic algorithm at a higher level of abstraction that only
simulates the aspects of the FPGA you want it to be able to leverage.

Algorithms like that I think are still not any good at doing full
systems but can definitely be helpful at optimizing sections. The
mixed-Chinese postal route problem has applicability to electrical and
systems engineering and GAs seem to do better solving it than previous
human-devised solutions:

<https://www-m9.ma.tum.de/games/mcpp-game/index_en.html>

<https://link.springer.com/chapter/10.1007/978-3-642-16493-4_20>

[Jan Panteltje]

Yes, and neural nets have very different solutions to that sort of problems.
A while back a postman was arrested because he never delivered the post,
they found thousands of letters and stuff in his house after many people complained
about not getting important mail.

Just a few months before that an other postman was caught burying hundreds of letters
in the woods.
It made the routing a lot easier for them I think.

[tabb...@gmail.com]

On Sunday, 10 November 2019 03:16:20 UTC, jla...@highlandsniptechnology.com wrote:

> On Sat, 9 Nov 2019 19:04:57 -0800 (PST), tabbypurr wrote:
> >On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
> >> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
> >> <pNaOnSt...@yahoo.com> wrote:
> >>
> >> > https://www.sciencedaily.com/releases/2019/11/191106144932.htm
> >> >
> >> >What is funny is the sort of lame excuse at the end:
> >> > "It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "
> >> >
> >> >
> >> >It is totally obvious at least to me that a more complex neural net can do more.
> >> >
> >> >This is going to be bigger and bigger..
> >> >
> >> >
> >> >Paper:
> >> > https://arxiv.org/abs/1907.11813
> >> >
> >> >This is also why I an sceptical of too much math and things like El Tea Spies,
> >> >I design differently.
> >> >
> >> >Rats :-)
> >> >
> >>
> >> The number of circuits that one can make from, say, thirty 4-pin parts
> >> probably exceeds the number of electrons in the universe. A human
> >> brain can explore an incredibly large possibility space that no
> >> procedural computer program could ever approach.
> >
> >On the contrary computers excel at assessing far more designs than we can because they're fast & tireless. We can rule out most options very quickly so we don't need to spend time assessing them. Which is faster? Depends on what's being assessed and how.
>
> Conventional computers are horribly slow.

You jest. An early 70s pocket calculator could do maths faster than we can.

> They can't even drive a car
> safely.

Nor can humans

> Brains are probably quantum computers that can simultaneously
> superimpose enormousely large possibility sets and collapse the good
> ones.

we don't know

> >> But LT Spice is great for evaluating and evolving ideas. It
> >> complements the more creative but less quantitative brain. I sometimes
> >> design by fiddling in Spice, letting it check the reasonableness of my
> >> instincts.
> >>
> >> I have a couple of recent designs that evolved in LT Spice and work
> >> great, that I still don't understand.
> >
> >Spice sims of random circuits won't design anything useful, but harvest the unused cycles of half the PCs on the internet and it becomes at least possible. Maybe in 50 years we'll all be obsolete.
> >
> >
> >NT
>
> There have been attempts to design with computers, or to do the easier
> task, optimize a given circuit. Not much progress so far.

Sure, a lot more compute power is needed. That will be available & cheap one day.


NT

[tabb...@gmail.com]

We have rules that we didn't think to tell the computer. It's a major problem in programming.


NT

[jla...@highlandsniptechnology.com]

On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabb...@gmail.com wrote:

>On Sunday, 10 November 2019 03:16:20 UTC, jla...@highlandsniptechnology.com wrote:
>> On Sat, 9 Nov 2019 19:04:57 -0800 (PST), tabbypurr wrote:
>> >On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
>> >> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
>> >> <pNaOnSt...@yahoo.com> wrote:
>> >>
>> >> > https://www.sciencedaily.com/releases/2019/11/191106144932.htm
>> >> >
>> >> >What is funny is the sort of lame excuse at the end:
>> >> > "It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "
>> >> >
>> >> >
>> >> >It is totally obvious at least to me that a more complex neural net can do more.
>> >> >
>> >> >This is going to be bigger and bigger..
>> >> >
>> >> >
>> >> >Paper:
>> >> > https://arxiv.org/abs/1907.11813
>> >> >
>> >> >This is also why I an sceptical of too much math and things like El Tea Spies,
>> >> >I design differently.
>> >> >
>> >> >Rats :-)
>> >> >
>> >>
>> >> The number of circuits that one can make from, say, thirty 4-pin parts
>> >> probably exceeds the number of electrons in the universe. A human
>> >> brain can explore an incredibly large possibility space that no
>> >> procedural computer program could ever approach.
>> >
>> >On the contrary computers excel at assessing far more designs than we can because they're fast & tireless. We can rule out most options very quickly so we don't need to spend time assessing them. Which is faster? Depends on what's being assessed and how.
>>
>> Conventional computers are horribly slow.
>
>You jest. An early 70s pocket calculator could do maths faster than we can.

But it can't design anything. It can't play table tennis.

>
>
>> They can't even drive a car
>> safely.
>
>Nor can humans
>
>
>> Brains are probably quantum computers that can simultaneously
>> superimpose enormousely large possibility sets and collapse the good
>> ones.
>
>we don't know

Somehow a brain does massive processing and memory and image
recognition in fractions of a second, using millisecond logic elements
and wet chemistry. It couldn't go that with an array of equivalent
logic gates. Nobody has a clue how that works.

I was takling to a neighbor, at our annual block party. He says that
he can't remember names or numbers very well, but he never forgets a
face that he has once seen, even briefly, decades ago.

Bats echolocate with equivalent ear-to-ear timing resolution in the
nanoseconds. Whales and porposes see the shapes of moving objects with
their sonar.

>
>
>> >> But LT Spice is great for evaluating and evolving ideas. It
>> >> complements the more creative but less quantitative brain. I sometimes
>> >> design by fiddling in Spice, letting it check the reasonableness of my
>> >> instincts.
>> >>
>> >> I have a couple of recent designs that evolved in LT Spice and work
>> >> great, that I still don't understand.
>> >
>> >Spice sims of random circuits won't design anything useful, but harvest the unused cycles of half the PCs on the internet and it becomes at least possible. Maybe in 50 years we'll all be obsolete.
>> >
>> >
>> >NT
>>
>> There have been attempts to design with computers, or to do the easier
>> task, optimize a given circuit. Not much progress so far.
>
>Sure, a lot more compute power is needed. That will be available & cheap one day.

Maybe not. Some problems don't get solved much better by applying more
and faster Intel CPUs.

[Tom Del Rosso]

jla...@highlandsniptechnology.com wrote:
>
> Somehow a brain does massive processing and memory and image
> recognition in fractions of a second, using millisecond logic elements
> and wet chemistry. It couldn't go that with an array of equivalent
> logic gates. Nobody has a clue how that works.

Well nobody has ever built a logic array where each element is connected
to 500 others.

I've heard claims that the brain uses quantum events to pick options,
and the randomness gives the appearance of free will.

But if that's even possible at 98.6 F then why do quantum computers need
liquid helium?

> I was takling to a neighbor, at our annual block party.

I hope you didn't hurt him.

[Clifford Heath]

On 11/11/19 11:14 am, Tom Del Rosso wrote:
> jla...@highlandsniptechnology.com wrote:
>>
>> Somehow a brain does massive processing and memory and image
>> recognition in fractions of a second, using millisecond logic elements
>> and wet chemistry. It couldn't go that with an array of equivalent
>> logic gates. Nobody has a clue how that works.
>
> Well nobody has ever built a logic array where each element is connected
> to 500 others.

or 10,000 others, which is closer to the fan-out I've heard quoted.

> I've heard claims that the brain uses quantum events to pick options,
> and the randomness gives the appearance of free will.

Actual freedom is not necessary anyhow, except to a philosopher. Any
behaviour which cannot be distinguished from randomness is sufficient to
support the (unnecessary) hypothesis of free will.

Given the exponential rate of error magnification in a chaotic system,
even the gravitational pull of a single electron at the far end of the
observable universe can be the "butterfly in Brazil", so it hardly helps
to even talk about "true" randomness in defence of free will.

Even if the randomness is "true" doesn't make decisions *meaningful"...
rather the opposite in fact. The whole philosophical pursuit of quantum
randomness as an exercise in defending "meaningfulness" is pointless and
counter-productive. It only means something to someone wedded to a
Cartesian system where meaning comes across from another realm.

Clifford Heath.

[Bill Sloman]

On Monday, November 11, 2019 at 6:51:17 AM UTC+11, jla...@highlandsniptechnology.com wrote:
> On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabb...@gmail.com wrote:
> >On Sunday, 10 November 2019 03:16:20 UTC, jla...@highlandsniptechnology.com wrote:
> >> On Sat, 9 Nov 2019 19:04:57 -0800 (PST), tabbypurr wrote:
> >> >On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
> >> >> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
> >> >> <pNaOnSt...@yahoo.com> wrote:

<snip>

> Somehow a brain does massive processing and memory and image
> recognition in fractions of a second, using millisecond logic elements

> and wet chemistry. It couldn't do that with an array of equivalent

> logic gates. Nobody has a clue how that works.

Neural nets were invented in an attempt to explain it. To that extent we do have some clues. Functional magnetic resonance scans of working brains provide a few more. We don't know exactly what the bain is doing, but we can see which areas are doing it.

> I was talking to a neighbor, at our annual block party. He says that

> he can't remember names or numbers very well, but he never forgets a
> face that he has once seen, even briefly, decades ago.
>
> Bats echolocate with equivalent ear-to-ear timing resolution in the
> nanoseconds.

Cite? Bats can hear up to 80kHz - where the period is 12.5usec.

The speed of sound in air is 343 metres per second, so the wavelength is 4.3 mm.

Nanosecond time resolution translates to a 0.343 micron spatial resolution, and bat labs aren't set up to measure distances anything like that precisely. Neither are bats.

<snip>

--
Bill Sloman, Sydney

[Clifford Heath]

On 11/11/19 1:53 pm, Bill Sloman wrote:
> On Monday, November 11, 2019 at 6:51:17 AM UTC+11, jla...@highlandsniptechnology.com wrote:
>> On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabb...@gmail.com wrote:
>>> On Sunday, 10 November 2019 03:16:20 UTC, jla...@highlandsniptechnology.com wrote:
>>>> On Sat, 9 Nov 2019 19:04:57 -0800 (PST), tabbypurr wrote:
>>>>> On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
>>>>>> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
>>>>>> <pNaOnSt...@yahoo.com> wrote:
>
> <snip>
>
>> Somehow a brain does massive processing and memory and image
>> recognition in fractions of a second, using millisecond logic elements
>> and wet chemistry. It couldn't do that with an array of equivalent
>> logic gates. Nobody has a clue how that works.
>
> Neural nets were invented in an attempt to explain it. To that extent we do have some clues. Functional magnetic resonance scans of working brains provide a few more. We don't know exactly what the bain is doing, but we can see which areas are doing it.
>
>> I was talking to a neighbor, at our annual block party. He says that
>> he can't remember names or numbers very well, but he never forgets a
>> face that he has once seen, even briefly, decades ago.
>>
>> Bats echolocate with equivalent ear-to-ear timing resolution in the
>> nanoseconds.
>
> Cite? Bats can hear up to 80kHz - where the period is 12.5usec.

The signals are subject to a mechanical fourier transform and amplitude
detection in the ear mechanics before there is even a neural impulse to
worry about. Detection of relative phase can then be done at much lower
rates, likely by neural correlators on counter-flowing delay lines. All
very feasible in wetware without invoking majick.

[Jan Panteltje]

>On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabb...@gmail.com wrote:
>
>Maybe not. Some problems don't get solved much better by applying more
>and faster Intel CPUs.

That is the point,
a neural net is principle NOT related to CPUs.

There is hardware developed that behaves much like a neuron.

For beginners:
https://towardsdatascience.com/first-neural-network-for-beginners-explained-with-code-4cfd37e06eaf
first google hit..

The thingy in fig 2 can be made from analog components, so no 'puter needed,
but 'puters are nice to emulate such thing.
The 'weights' storage could be in the form of a capacitor charge,
does not have to be digital registers.

Chips exist that contain fig 2 in quantity...

'Learning' changes the weights.

Interesting stuff..
There is open source software for Linux to play with this.
Those are 'emulations' however, like spice.
The analog thing does it have a (CPU) clock?

We are mostly analog, that is why we cannot do big number math easily...
Math is just a sub-structure of a few neurons in our brain,
and dangerous when taken for reality, much like religion and other 'beliefs'
My view anyway :-)

[jla...@highlandsniptechnology.com]

On Mon, 11 Nov 2019 08:16:20 GMT, Jan Panteltje
<pNaOnSt...@yahoo.com> wrote:

>>On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabb...@gmail.com wrote:
>>
>>Maybe not. Some problems don't get solved much better by applying more
>>and faster Intel CPUs.
>
>That is the point,
>a neural net is principle NOT related to CPUs.

No neural nets are cargo-cult cartoons of a biological nervous system.

>
>There is hardware developed that behaves much like a neuron.

Not a bit like a neuron. Even single-cell organisms, with no nervous
system, have complex behavior. Things with a couple dozen neurons have
extremely complex behavior.

>
>For beginners:
> https://towardsdatascience.com/first-neural-network-for-beginners-explained-with-code-4cfd37e06eaf
>first google hit..
>
>The thingy in fig 2 can be made from analog components, so no 'puter needed,
>but 'puters are nice to emulate such thing.
>The 'weights' storage could be in the form of a capacitor charge,
>does not have to be digital registers.

NNs are popular in academia for some reason. I've had job applicants,
recent grads, show me their NN projects, which they didn't actually
understand.

>
>Chips exist that contain fig 2 in quantity...
>
>'Learning' changes the weights.
>
>Interesting stuff..
>There is open source software for Linux to play with this.
>Those are 'emulations' however, like spice.
>The analog thing does it have a (CPU) clock?
>
>We are mostly analog, that is why we cannot do big number math easily...
>Math is just a sub-structure of a few neurons in our brain,
>and dangerous when taken for reality, much like religion and other 'beliefs'
>My view anyway :-)

I do a lot of math at the whiteboard, in my head, which impresses
people, but it's analog computing, like a slide rule. 10% or
thereabouts accuracy is good enough at a whiteboard, exact results in
many cases.

There have been "human computers" who can do high-precision
numerical-digits math in their heads.

[tabb...@gmail.com]

On Sunday, 10 November 2019 19:51:17 UTC, jla...@highlandsniptechnology.com wrote:

> On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabbypurr wrote:
> >On Sunday, 10 November 2019 03:16:20 UTC, jla...@highlandsniptechnology.com wrote:
> >> On Sat, 9 Nov 2019 19:04:57 -0800 (PST), tabbypurr wrote:
> >> >On Saturday, 9 November 2019 17:50:51 UTC, jla...@highlandsniptechnology.com wrote:
> >> >> On Sat, 09 Nov 2019 14:26:29 GMT, Jan Panteltje
> >> >> <pNaOnSt...@yahoo.com> wrote:
> >> >>
> >> >> > https://www.sciencedaily.com/releases/2019/11/191106144932.htm
> >> >> >
> >> >> >What is funny is the sort of lame excuse at the end:
> >> >> > "It's tempting to think that this AI will replace engineers, but that's simply not true," said McComb. "
> >> >> >
> >> >> >
> >> >> >It is totally obvious at least to me that a more complex neural net can do more.
> >> >> >
> >> >> >This is going to be bigger and bigger..
> >> >> >
> >> >> >
> >> >> >Paper:
> >> >> > https://arxiv.org/abs/1907.11813
> >> >> >
> >> >> >This is also why I an sceptical of too much math and things like El Tea Spies,
> >> >> >I design differently.
> >> >> >
> >> >> >Rats :-)
> >> >> >
> >> >>
> >> >> The number of circuits that one can make from, say, thirty 4-pin parts
> >> >> probably exceeds the number of electrons in the universe. A human
> >> >> brain can explore an incredibly large possibility space that no
> >> >> procedural computer program could ever approach.
> >> >
> >> >On the contrary computers excel at assessing far more designs than we can because they're fast & tireless. We can rule out most options very quickly so we don't need to spend time assessing them. Which is faster? Depends on what's being assessed and how.
> >>
> >> Conventional computers are horribly slow.
> >
> >You jest. An early 70s pocket calculator could do maths faster than we can.
>
> But it can't design anything. It can't play table tennis.

your claim was that computers are slow. Even the most primtive CPU IC wasn't. You've got to go back to the Harwell Witch era to get slow.

But obviously coming up with lots of random or otherwise circuits & assessing them does.


NT

[Bill Sloman]

Not exactly. Learning to program involves learning to recognise all the rules you need to apply to get the result you want, and then - of course - working out how you tell them to the machine, and how you get it to check that every last one has been satisfied.

If you have rules you didn't think to tell the computer about, you haven't mastered programming.

--
Bill Sloman, Sydney

[Jan Panteltje]

>On Mon, 11 Nov 2019 08:16:20 GMT, Jan Panteltje
><pNaOnSt...@yahoo.com> wrote:
>
>>>On Sun, 10 Nov 2019 11:18:50 -0800 (PST), tabb...@gmail.com wrote:
>>>
>>>Maybe not. Some problems don't get solved much better by applying more
>>>and faster Intel CPUs.
>>
>>That is the point,
>>a neural net is principle NOT related to CPUs.
>
>No neural nets are cargo-cult cartoons of a biological nervous system.
>
>>
>>There is hardware developed that behaves much like a neuron.
>
>Not a bit like a neuron. Even single-cell organisms, with no nervous
>system, have complex behavior. Things with a couple dozen neurons have
>extremely complex behavior.

OK, getting a bit into philosophy perhaps,
my first encounter with that 'neuron' idea in programming
is from I think it was in the eighties in a German magazine called MC?? where a prof had little cars
(software emulation) controlled by only 2 or 3 ? (don't remember) of those 'neurons'.

Those cars showed amazing human like behavior, depending how you 'wired'
the neurons those would circle around each other or avoid each other etc..

It got my interest (robotics been building a little car myself)) back then,
and did some experimenting.

Later I did write some neural net code to 'learn' stuff,
but then was too busy with work etc to pay much attention.
For object recognition (video my field) it was at that time not really good enough.
A lot has been done since the eighties and many papers have been published, quite amazing
results now achieved with e=neural nets in object recognition, amazing special hardware exist too.
That field is still very much alive.

>>
>>For beginners:
>> https://towardsdatascience.com/first-neural-network-for-beginners-explained-with-code-4cfd37e06eaf
>>first google hit..
>>
>>The thingy in fig 2 can be made from analog components, so no 'puter needed,
>>but 'puters are nice to emulate such thing.
>>The 'weights' storage could be in the form of a capacitor charge,
>>does not have to be digital registers.
>
>NNs are popular in academia for some reason. I've had job applicants,
>recent grads, show me their NN projects, which they didn't actually
>understand.

mm I dunno, could it perhaps be _you_ missed something??

>>
>>Chips exist that contain fig 2 in quantity...
>>
>>'Learning' changes the weights.
>>
>>Interesting stuff..
>>There is open source software for Linux to play with this.
>>Those are 'emulations' however, like spice.
>>The analog thing does it have a (CPU) clock?
>>
>>We are mostly analog, that is why we cannot do big number math easily...
>>Math is just a sub-structure of a few neurons in our brain,
>>and dangerous when taken for reality, much like religion and other 'beliefs'
>>My view anyway :-)
>
>I do a lot of math at the whiteboard, in my head, which impresses
>people, but it's analog computing, like a slide rule. 10% or
>thereabouts accuracy is good enough at a whiteboard, exact results in
>many cases.
>
>There have been "human computers" who can do high-precision
>numerical-digits math in their heads.

Yes there are those special people, I am one of those, did electronics at 9 years old ;-),
mama had to get a waver from the library so I could get the books.
There is also somebody who can learn a new language in 12 hours or something,,,,

And recite PI to I dunno how many decimals.
Maybe with enough training and the will to do it anybody can.
The will to do it is an important factor.


I was reading about this kid last week (in Dutch):
https://www.nu.nl/wetenschap/6009969/negenjarige-jongen-behaalt-bachelordiploma-aan-technische-universiteit.html
He learns so fast he is in the guinness book of records.
He wants to go into engineering to make artificial limbs and things.
When he turns over his final study project US universities will send a delegation to see if they can use him..


WE sHoUlD KeeP hIm iN Europe

[Tom Del Rosso]

jla...@highlandsniptechnology.com wrote:
> On Mon, 11 Nov 2019 08:16:20 GMT, Jan Panteltje
> <pNaOnSt...@yahoo.com> wrote:
>>
>> There is hardware developed that behaves much like a neuron.
>
> Not a bit like a neuron. Even single-cell organisms, with no nervous
> system, have complex behavior. Things with a couple dozen neurons have
> extremely complex behavior.

I don't think there is even a way to calculate the number of states they
have. What we need is a method like the invention of the state
machine - a simpler way to design with components that already exist.

[whit3rd]

On Monday, November 11, 2019 at 12:16:29 AM UTC-8, Jan Panteltje wrote:

> Math is just a sub-structure of a few neurons in our brain,
> and dangerous when taken for reality, much like religion and other 'beliefs'
> My view anyway :-)

Anything powerful is dangerous.

Math is NOT a substructure, it's a set of universal principles
that don't depend on any physical objects (indeed, do not
depend on any properties of the universe).

Some properties of the universe, however, do match math principles.

[Jan Panteltje]

Bad time to answer for me, ju\st watched part of an alien horror movie,
but ()
as we give more decision making to AI (artificial neural nets)
AI will at some point 'invent' (make a substructure it calls 'universal principles') _math_.

As to the reality of that substructure, 'string theory' is a bit like ..well name your religious fanatics.
singularities (substructure did a divide by zero as it had no clue what it was applying itself too), etc etc..

Sometimes bear with me, I very much see myself as the ant creeping up the wall,
its worldview with its fewer neurons then (well should anyways) is enough for it to maintain the species...
keep it alive,

Math as a method.. sure, but per definition in physics it is always wrong as we do not know unlimited depth.
it then becomes a dream world of / for the math user...
Exactly like religions provide a fake reality that is however embraced by large masses as a method to live and
continue the species.

?
Maybe , but cannot put it better,