On Wed, 24 Jan 2024 11:15:19 -0800, john larkin <jl@650pot.com> wrote:

>On Wed, 24 Jan 2024 10:59:47 -0800 (PST), Fred Bloggs
><bloggs.fredbloggs.fred@gmail.com> wrote:
>
>>On Wednesday, January 24, 2024 at 11:28:36?AM UTC-5, John Larkin wrote:
>>> On Wed, 24 Jan 2024 08:00:15 -0800 (PST), Fred Bloggs
>>> <bloggs.fred...@gmail.com> wrote:
>>>
>>> >On Monday, January 22, 2024 at 6:29:33?PM UTC-5, Anthony William Sloman wrote:
>>> >> On Tuesday, January 23, 2024 at 7:43:34?AM UTC+11, john larkin wrote:
>>> >> > On Mon, 22 Jan 2024 11:47:54 -0800 (PST), Fred Bloggs <bloggs.fred...@gmail.com> wrote:
>>> >> > >On Sunday, January 21, 2024 at 7:06:28?PM UTC-5, John Larkin wrote:
>>> >> > >> On Sun, 21 Jan 2024 18:16:01 -0500, Phil Hobbs <pcdhSpamM...@electrooptical.net> wrote:
>>> >> > >> >On 2024-01-21 10:12, John Larkin wrote:
>>> >>
>>> >> > I don't think so. Just a few words are not enough to specify and generate a specific, reliable design.
>>> >> They are enough to specify a patentable idea. Reducing it to practice takes a lot more work, and documenting a complete system takes a lot of words (and pictures). Oddly enough, software can do a lot of the documentation.
>>> >> > There's not much I in AI. It's mostly a silly fad.
>>> >> For particular problems it can already find solutions that humans can't
>>> >>
>>> >> https://en.wikipedia.org/wiki/Protein_folding
>>> >>
>>> >> AlphaFold is well ahead of any expert, and some theorem-proving programs operate without making mistakes to a degree that allows them to outperform human mathematicians on specific complex problems. It really isn't any kid of silly fad.
>>> >> > But brainstorming isn't so-called. Done right, it really works.
>>> >> Mainly by discouraging status-seeking creeps from insisting on concentrating on their own ideas.
>>> >
>>> >To be replaced by group concentration on no ideas at all.
>>> The people have to be right for the process to be productive of ideas.
>>> Some people will poison a brainstorming session, and too much general
>>> sociability in the room will reinforce conventional thinking.
>>>
>>> >
>>> >https://resources.pcb.cadence.com/blog/2022-the-role-of-machine-learning-in-analog-circuit-design
>>>
>>> That's absurd. Sounds like they are trying to sell cad options to
>>> beginners.
>>>
>>>
>>> >
>>> >https://www.synopsys.com/blogs/chip-design/ai-analog-design-migration-samsung-safe-forum-2023.html
>>>
>>>
>>> Certainly a lot of computing helps design digital ICs, but I wouldn't
>>> call that intelligence. Smart people wrote very specialized software.
>>> I sometimes write software to solve circuit problems, but the software
>>> just does what I told it to do.
>>>
>>>
>>> >
>>> >https://www.planetanalog.com/what-can-ai-do-for-analog-design/
>>>
>>>
>>> I'd love to have a good component selection tool. The intelligence
>>> would be in inferring things from bad data sheets that have no
>>> standards. It would of course have to read and understand application
>>> schematics and mechanical drawings and find gotchas buried in
>>> footnotes and graphs.
>>>
>>> Find me a right-angle Gbit PoE compatible RJ45 jack that has multiple
>>> drop-in sources, two LEDs on the high side, lots of stock from
>>> non-Chinese sources, at a good price. They have to mount on my PCB and
>>> ground to a cutout in my panel. That's an easy one.
>>
>>Lots of sources for that, but if you want a good price, it will be made in Asia. The shielded ones will ground to the panel. High demand parts like that will have a long lead time:
>>
>>https://www.digikey.com/en/products/detail/w%C3%BCrth-elektronik/615008137421/2060608
>>
>>
>>
>>> >
>>> >https://www.electronicdesign.com/technologies/embedded/article/21272567/electronic-design-ai-lends-a-helping-hand-with-analog-and-custom-ic-design
>>> >
>>> >https://semiengineering.com/ai-for-circuit-design-quality-productivity-and-advanced-node-mapping/
>>> >
>>> >http://ieeexplore.ieee.org/document/31523/
>>> >
>>> >The list is endless. Humans are not as unique and special as they make themselves out to be. They'll all be replaced by AI before long.
>>> Has AI ever invented anything?
>>
>>It's doing things like running through impossibly large numbers of permutations to find something useful, as with drug discovery. It's more the case creative people are using AI to enable inventive ideas.
>
>That's not intelligent. It's just automating a lot of grunt work, as
>programmed. Line monte carlo simulation. The person who set it up is
>the intelligence. All that's new is having more compute power than we
>had in the past.

John, AI is NOT just more computing power.

It is neural networks running on hardware that work well with NN

I see that with the Agent filter you put out that stops the Google
Groups postings stops the Fred Bloggs and other responders evidently.
But I haven't seen any sporge posts either so that is good.

boB

>
>Computers automate grunt work and let us work faster and better and
>move up the abstraction stack. Nonlinear differential equations were
>never much fun.
>
>I would like a Spice that was, say, 500x as fast as mine is now,
>nvidia or something. And I'd love some way to specify results and have
>a program juggle values and even library parts for a best solution.
>
>Past attempts at such optimizations have tended to diverge. Even most
>interns are smarter than that.
>
>
>>>
>>> >
>>> >
>>>
>>> I check up on Flux.ai now and then. I wonder when they will run out of
>>> money.
>
>Take a look at flux. It's funny.

On Thu, 25 Jan 2024 16:02:45 -0700, boB <boB@K7IQ.com> wrote:

>On Wed, 24 Jan 2024 11:15:19 -0800, john larkin <jl@650pot.com> wrote:
>
[snip]
>>
>>That's not intelligent. It's just automating a lot of grunt work, as
>>programmed. Line monte carlo simulation. The person who set it up is
>>the intelligence. All that's new is having more compute power than we
>>had in the past.
>
> John, AI is NOT just more computing power.
>
>It is neural networks running on hardware that work well with NN
Yes and no. No computer hardware "works well with NN" (Neural
Networks), because nobody has invented a true direct associative
hardware memory yet, so the computer hardware roughly emulates the
desired NN kind and behaviors, at stunning expense in hardware and
electrical power (plus cooling systems to remove all that heat).

It is useful to note that the pacing task for implementing a neural
net in a digital computer is matrix inversion, where the matrix to be
inverted may be billions of lines by billions of rows, and is not at
all sparse. It's a long story, but well documented.

By contrast, the human brain has a volume of about 1.3 liters and
consumes about 20 watts, and contains something like 171 billion
cells, of which 86 billion are neurons. Computations are performed by
analog hardware, cells. The number of synapses per neuron is
something like a factor of ten thousand larger. Every synapse needs a
cell in the matrix holding at least an 8-bit value. And so on.

Joe Gwinn

On Thu, 25 Jan 2024 18:38:28 -0500, Joe Gwinn <joegwinn@comcast.net>
wrote:

>On Thu, 25 Jan 2024 16:02:45 -0700, boB <boB@K7IQ.com> wrote:
>
>>On Wed, 24 Jan 2024 11:15:19 -0800, john larkin <jl@650pot.com> wrote:
>>
>[snip]
>>>
>>>That's not intelligent. It's just automating a lot of grunt work, as
>>>programmed. Line monte carlo simulation. The person who set it up is
>>>the intelligence. All that's new is having more compute power than we
>>>had in the past.
>>
>> John, AI is NOT just more computing power.

If it runs on a compuer it sure is.

>>
>>It is neural networks running on hardware that work well with NN

Do any NNs work well? NNs are cargo-cult crude cartoons of an actual
organism. Single- and few-cell organisms without a nervous system
learn and do complex stuff, and our brain has billions.

>
>Yes and no. No computer hardware "works well with NN" (Neural
>Networks), because nobody has invented a true direct associative
>hardware memory yet, so the computer hardware roughly emulates the
>desired NN kind and behaviors, at stunning expense in hardware and
>electrical power (plus cooling systems to remove all that heat).
>
>It is useful to note that the pacing task for implementing a neural
>net in a digital computer is matrix inversion, where the matrix to be
>inverted may be billions of lines by billions of rows, and is not at
>all sparse. It's a long story, but well documented.
>
>By contrast, the human brain has a volume of about 1.3 liters and
>consumes about 20 watts, and contains something like 171 billion
>cells, of which 86 billion are neurons. Computations are performed by
>analog hardware, cells. The number of synapses per neuron is
>something like a factor of ten thousand larger. Every synapse needs a
>cell in the matrix holding at least an 8-bit value. And so on.
>
>Joe Gwinn

And a human brain can play tennis, or recognize one face out of a
million, or design circuits, with wet chemistry gates that have
millisecond prop delays.

On Friday, January 26, 2024 at 11:03:27 AM UTC+11, john larkin wrote:
> On Thu, 25 Jan 2024 18:38:28 -0500, Joe Gwinn <joeg...@comcast.net>
> wrote:
> >On Thu, 25 Jan 2024 16:02:45 -0700, boB <b...@K7IQ.com> wrote:
> >
> >>On Wed, 24 Jan 2024 11:15:19 -0800, john larkin <j...@650pot.com> wrote:
> >>
> >[snip]
> >>>
> >>>That's not intelligent. It's just automating a lot of grunt work, as
> >>>programmed. Line monte carlo simulation. The person who set it up is
> >>>the intelligence. All that's new is having more compute power than we
> >>>had in the past.
> >>
> >> John, AI is NOT just more computing power.
>
> If it runs on a computer it sure is.

It runs on a different kind of computer, which works in a rather different way from the micropressors we are used to.

> >>It is neural networks running on hardware that work well with NN
> >
> Do any NNs work well? NNs are cargo-cult crude cartoons of an actual
> organism. Single- and few-cell organisms without a nervous system
> learn and do complex stuff, and our brain has billions.

They are an abstractions of what biological neural networks do, and to that extent they are cruder than the parts they are designed to emulate.

As with all new and poorly understood technology, there are loads of confidence tricksters trying to sell people neural network solutions that don't work.

> >Yes and no. No computer hardware "works well with NN" (Neural
> >Networks), because nobody has invented a true direct associative
> >hardware memory yet, so the computer hardware roughly emulates the
> >desired NN kind and behaviors, at stunning expense in hardware and
> >electrical power (plus cooling systems to remove all that heat).
> >
> >It is useful to note that the pacing task for implementing a neural
> >net in a digital computer is matrix inversion, where the matrix to be
> >inverted may be billions of lines by billions of rows, and is not at
> >all sparse. It's a long story, but well documented.
> >
> >By contrast, the human brain has a volume of about 1.3 liters and
> >consumes about 20 watts, and contains something like 171 billion
> >cells, of which 86 billion are neurons. Computations are performed by
> >analog hardware, cells. The number of synapses per neuron is
> >something like a factor of ten thousand larger. Every synapse needs a
> >cell in the matrix holding at least an 8-bit value. And so on.
>
> And a human brain can play tennis, or recognize one face out of a
> million, or design circuits, with wet chemistry gates that have
> millisecond prop delays.

So what?

--
Bill Sloman, Sydney

On Friday 26 January 2024 at 03:59:15 UTC, Anthony William Sloman wrote:
> On Friday, January 26, 2024 at 11:03:27 AM UTC+11, john larkin wrote:
> > On Thu, 25 Jan 2024 18:38:28 -0500, Joe Gwinn <joeg...@comcast.net>
> > wrote:
> > >On Thu, 25 Jan 2024 16:02:45 -0700, boB <b...@K7IQ.com> wrote:
> > >
> > >>On Wed, 24 Jan 2024 11:15:19 -0800, john larkin <j...@650pot.com> wrote:
> > >>
> > >[snip]
> > >>>
> > >>>That's not intelligent. It's just automating a lot of grunt work, as
> > >>>programmed. Line monte carlo simulation. The person who set it up is
> > >>>the intelligence. All that's new is having more compute power than we
> > >>>had in the past.
> > >>
> > >> John, AI is NOT just more computing power.
> >
> > If it runs on a computer it sure is.
>
> It runs on a different kind of computer, which works in a rather different way from the micropressors we are used to.
> > >>It is neural networks running on hardware that work well with NN
> > >
> > Do any NNs work well? NNs are cargo-cult crude cartoons of an actual
> > organism. Single- and few-cell organisms without a nervous system
> > learn and do complex stuff, and our brain has billions.
> They are an abstractions of what biological neural networks do, and to that extent they are cruder than the parts they are designed to emulate.
>
> As with all new and poorly understood technology, there are loads of confidence tricksters trying to sell people neural network solutions that don't work.
> > >Yes and no. No computer hardware "works well with NN" (Neural
> > >Networks), because nobody has invented a true direct associative
> > >hardware memory yet, so the computer hardware roughly emulates the
> > >desired NN kind and behaviors, at stunning expense in hardware and
> > >electrical power (plus cooling systems to remove all that heat).
> > >
> > >It is useful to note that the pacing task for implementing a neural
> > >net in a digital computer is matrix inversion, where the matrix to be
> > >inverted may be billions of lines by billions of rows, and is not at
> > >all sparse. It's a long story, but well documented.
> > >
> > >By contrast, the human brain has a volume of about 1.3 liters and
> > >consumes about 20 watts, and contains something like 171 billion
> > >cells, of which 86 billion are neurons. Computations are performed by
> > >analog hardware, cells. The number of synapses per neuron is
> > >something like a factor of ten thousand larger. Every synapse needs a
> > >cell in the matrix holding at least an 8-bit value. And so on.
> >
> > And a human brain can play tennis, or recognize one face out of a
> > million, or design circuits, with wet chemistry gates that have
> > millisecond prop delays.
> So what?

Some useful NN architectures such as the multi-layer perceptron can fit very well
and efficiently onto a DSP using fixed point arithmetic once training is complete.

John

On Thursday, January 25, 2024 at 7:59:15 PM UTC-8, Anthony William Sloman wrote:
> On Friday, January 26, 2024 at 11:03:27 AM UTC+11, john larkin wrote:

> > Do any NNs work well? NNs are cargo-cult crude cartoons of an actual
> > organism.
> > And a human brain can play tennis, or recognize one face out of a
> > million, or design circuits, with wet chemistry gates that have
> > millisecond prop delays.

> So what?

The takeaway here, is that we social animals have evolved IFF (identification
friend-or-foe) firmware, because that's an important task. Thus,
it's no surprise that facial recognition can be precise.
So can food-aroma and flavor distinction, there's things your
ancestors did not want to eat.

Some of our other important tasks are also hard to relegate to logic gates,
or analog computers, or locks/keys/cams. The expansion of a part of
our technology into those important tasks is inevitable, and... just
in its infancy.

The wetware IFF works for facial recognition quite well. It doesn't
apply to distinguishing Donald Trump against a real leadership candidate
nearly so well. Some voters are virtually still infants, I suspect.

On January 24, Fred Bloggs wrote:
> Humans are not as unique and special as they make themselves out to be.
> They'll all be replaced by AI before long.

This has already begun -
https://arxiv.org/abs/1810.10525

Who needs physicists?

--
Rich

On Thu, 25 Jan 2024 16:03:10 -0800, john larkin <jl@650pot.com> wrote:

>On Thu, 25 Jan 2024 18:38:28 -0500, Joe Gwinn <joegwinn@comcast.net>
>wrote:
>
>>On Thu, 25 Jan 2024 16:02:45 -0700, boB <boB@K7IQ.com> wrote:
>>
>>>On Wed, 24 Jan 2024 11:15:19 -0800, john larkin <jl@650pot.com> wrote:
>>>
>>[snip]
>>>>
>>>>That's not intelligent. It's just automating a lot of grunt work, as
>>>>programmed. Line monte carlo simulation. The person who set it up is
>>>>the intelligence. All that's new is having more compute power than we
>>>>had in the past.
>>>
>>> John, AI is NOT just more computing power.
>
>If it runs on a compuer it sure is.

Different kind of computer.

Well, in this case, using multi-core graphics controllers is
organized way better for the die size allowed in the neural network
application. Its different than what you can get these days in a
particular die size for the particula application. A PC micro,
although as or more complicated than an Nvidea graphics processor,
it works better for that.

As for being THE processor for a NN like Joe better points out, these
processors are what we had (and have) at the time so they were used.

Just wait for a just as complicated, circuitry wise, neural network
chip somes out. It will be even better.

Anyway, NNs are different too in that they "learn" better than a
"program" running on a 100X faster PC chip. That's what I considered
being different than just more computing power. In a non-linear way
mabe.

boB

>
>>>
>>>It is neural networks running on hardware that work well with NN
>
>Do any NNs work well? NNs are cargo-cult crude cartoons of an actual
>organism. Single- and few-cell organisms without a nervous system
>learn and do complex stuff, and our brain has billions.
>
>>
>>Yes and no. No computer hardware "works well with NN" (Neural
>>Networks), because nobody has invented a true direct associative
>>hardware memory yet, so the computer hardware roughly emulates the
>>desired NN kind and behaviors, at stunning expense in hardware and
>>electrical power (plus cooling systems to remove all that heat).
>>
>>It is useful to note that the pacing task for implementing a neural
>>net in a digital computer is matrix inversion, where the matrix to be
>>inverted may be billions of lines by billions of rows, and is not at
>>all sparse. It's a long story, but well documented.
>>
>>By contrast, the human brain has a volume of about 1.3 liters and
>>consumes about 20 watts, and contains something like 171 billion
>>cells, of which 86 billion are neurons. Computations are performed by
>>analog hardware, cells. The number of synapses per neuron is
>>something like a factor of ten thousand larger. Every synapse needs a
>>cell in the matrix holding at least an 8-bit value. And so on.
>>
>>Joe Gwinn
>
>And a human brain can play tennis, or recognize one face out of a
>million, or design circuits, with wet chemistry gates that have
>millisecond prop delays.

On Sun, 21 Jan 2024 22:14:34 -0800, John Larkin <jl@997PotHill.com>
wrote:

>On Mon, 22 Jan 2024 00:12:36 -0500, Joe Gwinn <joegwinn@comcast.net>
>wrote:
>
>>On Sun, 21 Jan 2024 19:43:18 -0800, John Larkin <jl@997PotHill.com>
>>wrote:
>>
>>>On Sun, 21 Jan 2024 22:08:08 -0500, Joe Gwinn <joegwinn@comcast.net>
>>>wrote:
>>>
>>>>On Sun, 21 Jan 2024 16:05:07 -0800, John Larkin <jl@997PotHill.com>
>>>>wrote:
>>>>
>>>>>On Sun, 21 Jan 2024 18:16:01 -0500, Phil Hobbs
>>>>><pcdhSpamMeSenseless@electrooptical.net> wrote:
>>>>>
>>>>>>JL wrote an interesting post in the depths of the "better
>>>>>>microelectronics from coal" thread that I thought was worth pulling out
>>>>>>on its own.
>>>>>>
>>>>>>On 2024-01-21 10:12, John Larkin wrote:>
>>>>>>
>>>>>>"...what IS electronic
>>>>>> > design, and what's the best way to do it? <snip>
>>>>>> >
>>>>>> > Short answer, cobbling. When presented with a problem or an
>>>>>> > opportunity to design electronics, the most efficient way to do that
>>>>>> > is to grab a piece of paper and immediately sketch a circuit or an
>>>>>> > assembly. Sometimes one can do that instantly, without thinking, or
>>>>>> > sometimes one can ignore the issue for a few days and then the design
>>>>>> > pops up. Sometimes brainstorming and whiteboarding help. Sometimes
>>>>>> > fiddling with Spice helps.
>>>>>> >
>>>>>> > All that literature research and math analysis and simulation and
>>>>>> > breadboarding and prototyping are just slow and expensive follow-up
>>>>>> > chores for people who don't have 100% confidence in their instincts.
>>>>>> > Analysis, sometimes prudent to do, but not design.
>>>>>> >
>>>>>> > Design is subconsious and instinctive. And it's free! And to some
>>>>>> > extent, it can be taught, but seldom is.
>>>>>> >
>>>>>> > Most of us design things to sell, so do whatever works. We're selling
>>>>>> > stuff, not publishing papers.
>>>>>> >
>>>>>>
>>>>>>Hmm. I don't think that I agree in general, because you make it sound
>>>>>>as though the process were just intuitively plucking one idea out of
>>>>>>somewhere-or-other and cranking it out.
>>>>>
>>>>>If an idea is new, where else would come from?
>>>>>
>>>>>>
>>>>>>You've often argued in favor of brainstorming, where you get a few smart
>>>>>>people in front of a white board and try out ideas to find the best one
>>>>>>and flesh it out. We've done that together, very fruitfully.
>>>>>>
>>>>>>It's possible to do more or less the same thing by oneself, but it
>>>>>>requires the ability to tolerate uncertainty for extended periods.
>>>>>>(That's a skill well worth developing, which most people are really,
>>>>>>really bad at, IME.)
>>>>>
>>>>>The uncertainty period is probably necessary, to let ones neurons
>>>>>prowl the noisy solution space. The period is usually a day or two,
>>>>>but can be years.
>>>>>
>>>>>Some engineers are uncomfortable with uncertainty, and want to lock
>>>>>down a design as soon as possible, preferably something sanctioned by
>>>>>some authority. I like to stay confused for a while.
>>>>>
>>>>>>
>>>>>>I sometimes need to do a family of designs, rather than just one.
>>>>>>Recently I've been working on some very fast, very cheap SPAD preamps,
>>>>>>intended to go in the guts of positron-emission scanners.
>>>>>>
>>>>>>Designs with lots of real-world constraints are often the most fun, and
>>>>>>this one's specs include: 300-ps edges with 100-ps timing repeatability
>>>>>>from unit to unit; no magnetics allowed; and a BOM cost of $1 or less.
>>>>>>(You need a whole lot of channels, and PET and MRI machines are often
>>>>>>combined.)
>>>>>>
>>>>>>I do a fair amount of analysis of circuits of that sort, to figure out
>>>>>>what actually limits their performance. It isn't super detailed--in
>>>>>>this case, just enough to figure out whether it'll be the base-emitter
>>>>>>time constant, the Miller effect, or the SPAD's series resistance that
>>>>>>will be the limiting factor.
>>>>>
>>>>>Certainly quantitative reality should filter the solution space. But
>>>>>even that can be mostly intuitive. I was talking about that with C on
>>>>>Friday, about how some people have good quantitative intuition and
>>>>>some don't. She can look at soup in a round pot and know if it will
>>>>>fit into a square plastic container, to about 10%. I can do that.
>>>>>Neither of our spouses can.
>>>>>
>>>>>
>>>>>>
>>>>>>Miller, I can deal with using circuit hacks. The BE time constant is
>>>>>>Rbb' * Cbe, which gets slightly worse at high current, but is mainly a
>>>>>>device parameter--to get a big improvement you have to change
>>>>>>transistors. The SPAD can be negotiable depending on whose process
>>>>>>you're making them on--when each machine needs thousands of them,
>>>>>>vendors tend to listen.
>>>>>>
>>>>>>Eventually, of course, you have to pick one and go with it, but picking
>>>>>>a topology usually takes me an iteration or two.
>>>>>
>>>>>Sometimes a circuit takes me dozens, lots of sheets in the trash can.
>>>>>I think it's important to give as many ideas as possible a chance.
>>>>>
>>>>>See Barrie Gilbert's essay "Where do little circuits come from?"
>>>>>
>>>>>"Prod and poke" and "doodling" are suggested.
>>>>>
>>>>
>>>>I agree with both of you. What Phil is doing is figuring out where to
>>>>focus the brainstorming and fiddling, and the resulting wild
>>>>alternatives can easily be assessed. It's at the very least an
>>>>orthogonal method.
>>>>
>>>>My personal experience is that iterations and inspirations require
>>>>studying extensively followed by sleeping on it, so the metric isn't a
>>>>few days, it's a few nights.
>>>
>>>Actually, it is a few showers.
>>
>>So, you're all wet?
>
>That's the idea.
>
>>
>>Actually, I also get ideas in the shower, probably because I stopped
>>focusing so hard.
>
>I think sleepytime ideas get delivered in a morning shower. I don't
>have ideas if I shower later in the day.

I opened an email in the morning and took a shower and had a bunch of
ideas. So ideas both get delivered in the suds, and happen there too.

Other people have noted the creative powers of hot water falling on
your head.

Good book, First Steps by Jeremy DeSilva. It's about the evolution of
upright walking, but he mentions that various great thinkers had ideas
sleeping, showering, or walking. Walking works best in the woods, not
on city streets.

"In London, where Southampton Row passes Russell Square,
across from the British Museum in Bloomsbury, Leo
Szilard waited irritably one gray Depression morning
for the stoplight to change. A trace of rain had fallen
during the night; Tuesday, September 12, 1933, dawned
cool, humid and dull. Drizzling rain would begin again
in early afternoon. When Szilard told the story later he
never mentioned his destination that morning. He may
have had none; he often walked to think. In any case
another destination intervened. The stoplight changed to
green. Szilard stepped off the curb. As he crossed the
street time cracked open before him and he saw a way to
the future, death into the world and all our woe,
the shape of things to come."

https://en.wikipedia.org/wiki/Leo_Szilard

On Mon, 05 Feb 2024 07:04:59, Wanderer<dont@emailme.com> wrote:

>
>
>"In London, where Southampton Row passes Russell Square,
> across from the British Museum in Bloomsbury, Leo
> Szilard waited irritably one gray Depression morning
> for the stoplight to change. A trace of rain had fallen
> during the night; Tuesday, September 12, 1933, dawned
> cool, humid and dull. Drizzling rain would begin again
> in early afternoon. When Szilard told the story later he
> never mentioned his destination that morning. He may
> have had none; he often walked to think. In any case
> another destination intervened. The stoplight changed to
> green. Szilard stepped off the curb. As he crossed the
> street time cracked open before him and he saw a way to
> the future, death into the world and all our woe,
> the shape of things to come."
>
>
>https://en.wikipedia.org/wiki/Leo_Szilard

Nice story. Richards Rhodes is a great writer.

On a sunny day (Mon, 05 Feb 2024 14:47:33 -0800) it happened john larkin
<jl@650pot.com> wrote in <jso2sil36ljn7ucbpmgbup90ki9ub71dd0@4ax.com>:

>On Sun, 21 Jan 2024 22:14:34 -0800, John Larkin <jl@997PotHill.com>
>wrote:
>
>>On Mon, 22 Jan 2024 00:12:36 -0500, Joe Gwinn <joegwinn@comcast.net>
>>wrote:
>>
>>>On Sun, 21 Jan 2024 19:43:18 -0800, John Larkin <jl@997PotHill.com>
>>>wrote:
>>>
>>>>On Sun, 21 Jan 2024 22:08:08 -0500, Joe Gwinn <joegwinn@comcast.net>
>>>>wrote:
>>>>
>>>>>On Sun, 21 Jan 2024 16:05:07 -0800, John Larkin <jl@997PotHill.com>
>>>>>wrote:
>>>>>
>>>>>>On Sun, 21 Jan 2024 18:16:01 -0500, Phil Hobbs
>>>>>><pcdhSpamMeSenseless@electrooptical.net> wrote:
>>>>>>
>>>>>>>JL wrote an interesting post in the depths of the "better
>>>>>>>microelectronics from coal" thread that I thought was worth pulling out
>>>>>>>on its own.
>>>>>>>
>>>>>>>On 2024-01-21 10:12, John Larkin wrote:>
>>>>>>>
>>>>>>>"...what IS electronic
>>>>>>> > design, and what's the best way to do it? <snip>
>>>>>>> >
>>>>>>> > Short answer, cobbling. When presented with a problem or an
>>>>>>> > opportunity to design electronics, the most efficient way to do that
>>>>>>> > is to grab a piece of paper and immediately sketch a circuit or an
>>>>>>> > assembly. Sometimes one can do that instantly, without thinking, or
>>>>>>> > sometimes one can ignore the issue for a few days and then the design
>>>>>>> > pops up. Sometimes brainstorming and whiteboarding help. Sometimes
>>>>>>> > fiddling with Spice helps.
>>>>>>> >
>>>>>>> > All that literature research and math analysis and simulation and
>>>>>>> > breadboarding and prototyping are just slow and expensive follow-up
>>>>>>> > chores for people who don't have 100% confidence in their instincts.
>>>>>>> > Analysis, sometimes prudent to do, but not design.
>>>>>>> >
>>>>>>> > Design is subconscious and instinctive. And it's free! And to some
>>>>>>> > extent, it can be taught, but seldom is.
>>>>>>> >
>>>>>>> > Most of us design things to sell, so do whatever works. We're selling
>>>>>>> > stuff, not publishing papers.
>>>>>>> >
>>>>>>>
>>>>>>>Hmm. I don't think that I agree in general, because you make it sound
>>>>>>>as though the process were just intuitively plucking one idea out of
>>>>>>>somewhere-or-other and cranking it out.
>>>>>>
>>>>>>If an idea is new, where else would come from?
>>>>>>
>>>>>>>
>>>>>>>You've often argued in favor of brainstorming, where you get a few smart
>>>>>>>people in front of a white board and try out ideas to find the best one
>>>>>>>and flesh it out. We've done that together, very fruitfully.
>>>>>>>
>>>>>>>It's possible to do more or less the same thing by oneself, but it
>>>>>>>requires the ability to tolerate uncertainty for extended periods.
>>>>>>>(That's a skill well worth developing, which most people are really,
>>>>>>>really bad at, IME.)
>>>>>>
>>>>>>The uncertainty period is probably necessary, to let ones neurons
>>>>>>prowl the noisy solution space. The period is usually a day or two,
>>>>>>but can be years.
>>>>>>
>>>>>>Some engineers are uncomfortable with uncertainty, and want to lock
>>>>>>down a design as soon as possible, preferably something sanctioned by
>>>>>>some authority. I like to stay confused for a while.
>>>>>>
>>>>>>>
>>>>>>>I sometimes need to do a family of designs, rather than just one.
>>>>>>>Recently I've been working on some very fast, very cheap SPAD preamps,
>>>>>>>intended to go in the guts of positron-emission scanners.
>>>>>>>
>>>>>>>Designs with lots of real-world constraints are often the most fun, and
>>>>>>>this one's specs include: 300-ps edges with 100-ps timing repeatability
>>>>>>>from unit to unit; no magnetics allowed; and a BOM cost of $1 or less.
>>>>>>>(You need a whole lot of channels, and PET and MRI machines are often
>>>>>>>combined.)
>>>>>>>
>>>>>>>I do a fair amount of analysis of circuits of that sort, to figure out
>>>>>>>what actually limits their performance. It isn't super detailed--in
>>>>>>>this case, just enough to figure out whether it'll be the base-emitter
>>>>>>>time constant, the Miller effect, or the SPAD's series resistance that
>>>>>>>will be the limiting factor.
>>>>>>
>>>>>>Certainly quantitative reality should filter the solution space. But
>>>>>>even that can be mostly intuitive. I was talking about that with C on
>>>>>>Friday, about how some people have good quantitative intuition and
>>>>>>some don't. She can look at soup in a round pot and know if it will
>>>>>>fit into a square plastic container, to about 10%. I can do that.
>>>>>>Neither of our spouses can.
>>>>>>
>>>>>>
>>>>>>>
>>>>>>>Miller, I can deal with using circuit hacks. The BE time constant is
>>>>>>>Rbb' * Cbe, which gets slightly worse at high current, but is mainly a
>>>>>>>device parameter--to get a big improvement you have to change
>>>>>>>transistors. The SPAD can be negotiable depending on whose process
>>>>>>>you're making them on--when each machine needs thousands of them,
>>>>>>>vendors tend to listen.
>>>>>>>
>>>>>>>Eventually, of course, you have to pick one and go with it, but picking
>>>>>>>a topology usually takes me an iteration or two.
>>>>>>
>>>>>>Sometimes a circuit takes me dozens, lots of sheets in the trash can.
>>>>>>I think it's important to give as many ideas as possible a chance.
>>>>>>
>>>>>>See Barrie Gilbert's essay "Where do little circuits come from?"
>>>>>>
>>>>>>"Prod and poke" and "doodling" are suggested.
>>>>>>
>>>>>
>>>>>I agree with both of you. What Phil is doing is figuring out where to
>>>>>focus the brainstorming and fiddling, and the resulting wild
>>>>>alternatives can easily be assessed. It's at the very least an
>>>>>orthogonal method.
>>>>>
>>>>>My personal experience is that iterations and inspirations require
>>>>>studying extensively followed by sleeping on it, so the metric isn't a
>>>>>few days, it's a few nights.
>>>>
>>>>Actually, it is a few showers.
>>>
>>>So, you're all wet?
>>
>>That's the idea.
>>
>>>
>>>Actually, I also get ideas in the shower, probably because I stopped
>>>focusing so hard.
>>
>>I think sleepytime ideas get delivered in a morning shower. I don't
>>have ideas if I shower later in the day.
>
>I opened an email in the morning and took a shower and had a bunch of
>ideas. So ideas both get delivered in the suds, and happen there too.
>
>Other people have noted the creative powers of hot water falling on
>your head.
>
>Good book, First Steps by Jeremy DeSilva. It's about the evolution of
>upright walking, but he mentions that various great thinkers had ideas
>sleeping, showering, or walking. Walking works best in the woods, not
>on city streets.

On Tue, 06 Feb 2024 05:21:10 GMT, Jan Panteltje <alien@comet.invalid>
wrote:

>On a sunny day (Mon, 05 Feb 2024 14:47:33 -0800) it happened john larkin
><jl@650pot.com> wrote in <jso2sil36ljn7ucbpmgbup90ki9ub71dd0@4ax.com>:
>
>>On Sun, 21 Jan 2024 22:14:34 -0800, John Larkin <jl@997PotHill.com>
>>wrote:
>>
>>>On Mon, 22 Jan 2024 00:12:36 -0500, Joe Gwinn <joegwinn@comcast.net>
>>>wrote:
>>>
>>>>On Sun, 21 Jan 2024 19:43:18 -0800, John Larkin <jl@997PotHill.com>
>>>>wrote:
>>>>
>>>>>On Sun, 21 Jan 2024 22:08:08 -0500, Joe Gwinn <joegwinn@comcast.net>
>>>>>wrote:
>>>>>
>>>>>>On Sun, 21 Jan 2024 16:05:07 -0800, John Larkin <jl@997PotHill.com>
>>>>>>wrote:
>>>>>>
>>>>>>>On Sun, 21 Jan 2024 18:16:01 -0500, Phil Hobbs
>>>>>>><pcdhSpamMeSenseless@electrooptical.net> wrote:
>>>>>>>
>>>>>>>>JL wrote an interesting post in the depths of the "better
>>>>>>>>microelectronics from coal" thread that I thought was worth pulling out
>>>>>>>>on its own.
>>>>>>>>
>>>>>>>>On 2024-01-21 10:12, John Larkin wrote:>
>>>>>>>>
>>>>>>>>"...what IS electronic
>>>>>>>> > design, and what's the best way to do it? <snip>
>>>>>>>> >
>>>>>>>> > Short answer, cobbling. When presented with a problem or an
>>>>>>>> > opportunity to design electronics, the most efficient way to do that
>>>>>>>> > is to grab a piece of paper and immediately sketch a circuit or an
>>>>>>>> > assembly. Sometimes one can do that instantly, without thinking, or
>>>>>>>> > sometimes one can ignore the issue for a few days and then the design
>>>>>>>> > pops up. Sometimes brainstorming and whiteboarding help. Sometimes
>>>>>>>> > fiddling with Spice helps.
>>>>>>>> >
>>>>>>>> > All that literature research and math analysis and simulation and
>>>>>>>> > breadboarding and prototyping are just slow and expensive follow-up
>>>>>>>> > chores for people who don't have 100% confidence in their instincts.
>>>>>>>> > Analysis, sometimes prudent to do, but not design.
>>>>>>>> >
>>>>>>>> > Design is subconscious and instinctive. And it's free! And to some
>>>>>>>> > extent, it can be taught, but seldom is.
>>>>>>>> >
>>>>>>>> > Most of us design things to sell, so do whatever works. We're selling
>>>>>>>> > stuff, not publishing papers.
>>>>>>>> >
>>>>>>>>
>>>>>>>>Hmm. I don't think that I agree in general, because you make it sound
>>>>>>>>as though the process were just intuitively plucking one idea out of
>>>>>>>>somewhere-or-other and cranking it out.
>>>>>>>
>>>>>>>If an idea is new, where else would come from?
>>>>>>>
>>>>>>>>
>>>>>>>>You've often argued in favor of brainstorming, where you get a few smart
>>>>>>>>people in front of a white board and try out ideas to find the best one
>>>>>>>>and flesh it out. We've done that together, very fruitfully.
>>>>>>>>
>>>>>>>>It's possible to do more or less the same thing by oneself, but it
>>>>>>>>requires the ability to tolerate uncertainty for extended periods.
>>>>>>>>(That's a skill well worth developing, which most people are really,
>>>>>>>>really bad at, IME.)
>>>>>>>
>>>>>>>The uncertainty period is probably necessary, to let ones neurons
>>>>>>>prowl the noisy solution space. The period is usually a day or two,
>>>>>>>but can be years.
>>>>>>>
>>>>>>>Some engineers are uncomfortable with uncertainty, and want to lock
>>>>>>>down a design as soon as possible, preferably something sanctioned by
>>>>>>>some authority. I like to stay confused for a while.
>>>>>>>
>>>>>>>>
>>>>>>>>I sometimes need to do a family of designs, rather than just one.
>>>>>>>>Recently I've been working on some very fast, very cheap SPAD preamps,
>>>>>>>>intended to go in the guts of positron-emission scanners.
>>>>>>>>
>>>>>>>>Designs with lots of real-world constraints are often the most fun, and
>>>>>>>>this one's specs include: 300-ps edges with 100-ps timing repeatability
>>>>>>>>from unit to unit; no magnetics allowed; and a BOM cost of $1 or less.
>>>>>>>>(You need a whole lot of channels, and PET and MRI machines are often
>>>>>>>>combined.)
>>>>>>>>
>>>>>>>>I do a fair amount of analysis of circuits of that sort, to figure out
>>>>>>>>what actually limits their performance. It isn't super detailed--in
>>>>>>>>this case, just enough to figure out whether it'll be the base-emitter
>>>>>>>>time constant, the Miller effect, or the SPAD's series resistance that
>>>>>>>>will be the limiting factor.
>>>>>>>
>>>>>>>Certainly quantitative reality should filter the solution space. But
>>>>>>>even that can be mostly intuitive. I was talking about that with C on
>>>>>>>Friday, about how some people have good quantitative intuition and
>>>>>>>some don't. She can look at soup in a round pot and know if it will
>>>>>>>fit into a square plastic container, to about 10%. I can do that.
>>>>>>>Neither of our spouses can.
>>>>>>>
>>>>>>>
>>>>>>>>
>>>>>>>>Miller, I can deal with using circuit hacks. The BE time constant is
>>>>>>>>Rbb' * Cbe, which gets slightly worse at high current, but is mainly a
>>>>>>>>device parameter--to get a big improvement you have to change
>>>>>>>>transistors. The SPAD can be negotiable depending on whose process
>>>>>>>>you're making them on--when each machine needs thousands of them,
>>>>>>>>vendors tend to listen.
>>>>>>>>
>>>>>>>>Eventually, of course, you have to pick one and go with it, but picking
>>>>>>>>a topology usually takes me an iteration or two.
>>>>>>>
>>>>>>>Sometimes a circuit takes me dozens, lots of sheets in the trash can.
>>>>>>>I think it's important to give as many ideas as possible a chance.
>>>>>>>
>>>>>>>See Barrie Gilbert's essay "Where do little circuits come from?"
>>>>>>>
>>>>>>>"Prod and poke" and "doodling" are suggested.
>>>>>>>
>>>>>>
>>>>>>I agree with both of you. What Phil is doing is figuring out where to
>>>>>>focus the brainstorming and fiddling, and the resulting wild
>>>>>>alternatives can easily be assessed. It's at the very least an
>>>>>>orthogonal method.
>>>>>>
>>>>>>My personal experience is that iterations and inspirations require
>>>>>>studying extensively followed by sleeping on it, so the metric isn't a
>>>>>>few days, it's a few nights.
>>>>>
>>>>>Actually, it is a few showers.
>>>>
>>>>So, you're all wet?
>>>
>>>That's the idea.
>>>
>>>>
>>>>Actually, I also get ideas in the shower, probably because I stopped
>>>>focusing so hard.
>>>
>>>I think sleepytime ideas get delivered in a morning shower. I don't
>>>have ideas if I shower later in the day.
>>
>>I opened an email in the morning and took a shower and had a bunch of
>>ideas. So ideas both get delivered in the suds, and happen there too.
>>
>>Other people have noted the creative powers of hot water falling on
>>your head.
>>
>>Good book, First Steps by Jeremy DeSilva. It's about the evolution of
>>upright walking, but he mentions that various great thinkers had ideas
>>sleeping, showering, or walking. Walking works best in the woods, not
>>on city streets.
>
>I have been doing 1 to 2 hours meditation every day since the mid seventies.
>Had ideas in the shower too.
>Walking is good, I had a box full of medals as a kid for completing long marches.
>Sill running faster than everybody here it seems, yesterday big storm
>was on the bike, flying with wind in back.
>On the way back walking with bike in hand.. now way with this bike against the wind
>no gears...
>More storm coming...
>Satellite dish still works...