[FRIAM] Some brands of digital electric meters wildly inaccurate on nonlinear loads, and NM may get them soon!

[_ Bruno W]

I'm hoping some Friam member who knows a little about how an electric meter
works will be interested
enough to get this addressed BEFORE PNM spends $ 300+ million giving us all
new meters.

If interested I can send the full paper abstracted here:
https://ieeexplore.ieee.org/document/8077940
There is also a thesis from the same group that gives more info

The paper makes clear that one of the preferred technologies in electric
meters (the Rogowski coil)
can go haywire when nonlinear loads are present. The smart meters gave
readings up to 500% higher
than the actual usage. The meters PNM has proposed for its entire territory
is the Itron "Gen5" Riva,
which has been deployed in the last 2 years in Denver and parts of Texas.
Sure enough, some customers'
bill have gone way up (3 or 4-fold in one news report), and they have
little recourse: https://www.youtube.com/watch?v=dpOhTXV59pI=20s

I intervened in this PRC proceeding last year, and may be able to get this
info onto the record, and try to
get the PRC to require better testing on nonlinear loads. But I need
someone with some relevant expertise
(can be education or experience) to explain the published findings and
their implications to the PRC in an affidavit by March.
This person would then answer questions from the PRC and possibly PNM via
zoom in a short hearing in late April or May.

I have several reasons for not wanting to see PNM make this huge investment
(and by law they are entitled to a nice
rate of return paid by us, the customers) in a very messed-up technology.
Probably most of us in this group
don't sweat much about our electric bills (actually maybe if ours
quadrupled, we would), but for low-income families, this is
potentially very cruel, since the cost of the meters will be charged with
interest regardless of usage, and energy-saving
appliances typically have nonlinear load usages).

I hope to be at the St. John's gathering Friday am, but feel free to reply
or contact me directly if interested in this.


--William J. Bruno, Ph.D.
wbr...@gmail.com
-. --- - / ...- .- .-.. .. -.. / -- --- .-. ... . / -.-. --- -.. .
FRIAM Applied Complexity Group listserv
Fridays 9a-12p Friday St. Johns Cafe   /   Thursdays 9a-12p Zoom 
https://bit.ly/virtualfriam
to (un)subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
FRIAM-COMIC http://friam-comic.blogspot.com/
archives:  5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/
  1/2003 thru 6/2021  http://friam.383.s1.nabble.com/

Re: [FRIAM] The problems of interdisciplinary research

[glen]

Discussions of curiosity are like discussions of side effects, spandrels, and the rest. The simple 
conception of curiosity is information seeking to no purpose, no "instrumental benefit". 
But that's clearly nonsense, barring some sophistry around "instrumental benefit".

Curiosity seems to me to be an affect(ation), i.e. it refers to some other 
thing. Of course, that begs us to ask whether more curious people have a larger 
domain for the curiosity operator than other people. So if you can call Sally 
curious about nearly every topic and Bob only curious about particular topics, 
then Sally is more curious than Bob. But that suffers from so many confounders 
as to be meaningless. If Sally only engages with any particular topic for an 
hour, whereas Bob, when he does engage, engages for decades, then which is more 
curious?

And if curiosity is always about some (domain of) referent(s), then how is it 
distinguishable from any other appetite (e.g. inquisitiveness, paraphilia, 
obsessive-compulsion)?

I can't help but hearken back to our past exchanges on this list discussing concepts like 
free will, consciousness, or qualia, all of which seem to me to occupy the same category 
as curiosity. The distinguishing factor seems only to be "energy" and a 
willingness to play others' games -- or any particular game that happens to plop down on 
the table. If one has the energy, one can entertain whatever arbitrary game others 
propose. But when you lack the energy, you're accused of incuriosity or whatever other 
epithet the privileged find convenient.

On 2/12/24 08:30, Marcus Daniels wrote:

With a robot using a generative model, one way a curiosity could manifest is in 
how it learns from experience.   With a somewhat higher sampling temperature, 
the performance of a skill would vary.  At a much higher temperature, the skill 
would not be evident.   If the skill had not been mastered, or there were 
equivalently good ways to perform it, random deviations might find these 
variants.   This sampling temperature doesn’t itself change the model, but the 
feedback loop from the robot in its environment would lead to different losses, 
that would then be corrected through the model, e.g. through back propagation.

An example for me is learning sculling -- finding a rhythm is as much about 
feeling the consequences of a set of movements on the water, as water 
conditions vary, as it is executing a specified set of moves in order.

*From:*Friam  *On Behalf Of *Prof David West
*Sent:* Monday, February 12, 2024 7:15 AM
*To:* friam@redfish.com
*Subject:* Re: [FRIAM] The problems of interdisciplinary research

The notion of search brings to mind two different experiences:

1- traditional "searching" of the library via the card catalog (yes, I know I 
am old) for relevant inputs; and,

2- the "serendipity of the stacks"—simply looking around me at the books I 
located via search type 1 to see what was in proximity.

My experience: the second type of "search" was far more valuable, to me, than 
the first.

Also, with the books found via search '1-', the included bibliography was 
frequently of more ultimate use than the book containing the bibliography.

Computerized search—ala Google—has always seemed limited; precisely because it is 
exclusively search type '1-'. (Even Google Scholar) Attempts to "improve" 
search by narrowing it on the basis of prior searches makes it really, really, worse.

LLM based search seems, to me, to have some capability to approximate the 
serendipity of the stacks.

davew

On Mon, Feb 12, 2024, at 6:12 AM, David Eric Smith wrote:

It’s kind of fascinating.

I imagine that one of the next concepts to come into focus will be 
“curiosity”.  I remember a discussion years ago (15? 18?), I think involving 
David K., about what the nature of “curiosity” is and what role it plays in 
learning.

Where the paper talks about supervision to train weights, but eschewing 
“search” per se as a component of the capability learned, it makes me think of 
the role of search in the pursuit of inputs, the ultimate worth of which you 
can’t know at the time of searching.  I can imagine (off the cuff) that 
whatever one wants to mean by “curiosity”, it has some flavor of a non-random 
search, but one not guided by known criteria, rather by appropriateness to fit 
existing gaps in (something: confidence? consistency?).

This also seems like it should tie into Leslie Valiant’s ideas in Probably 
Approximately Correct about how to formally conceptualize teaching in relation 
to learning.  I guess Valiant is now considered decades passe, as AI has 
charged ahead.  But the broad outlines of his argument don’t seem like they 
have become completely superseded.

We already have “attention” as a secret sauce with important impacts.  I 
wonder when some shift of architectural paradigm will include a design that we 
think is a good formalization of the pre-formal gestures toward curiosity.

Eric

  

Re: [FRIAM] The problems of interdisciplinary research

[Marcus Daniels]

With a robot using a generative model, one way a curiosity could manifest is in 
how it learns from experience.   With a somewhat higher sampling temperature, 
the performance of a skill would vary.  At a much higher temperature, the skill 
would not be evident.   If the skill had not been mastered, or there were 
equivalently good ways to perform it, random deviations might find these 
variants.   This sampling temperature doesn’t itself change the model, but the 
feedback loop from the robot in its environment would lead to different losses, 
that would then be corrected through the model, e.g. through back propagation.

An example for me is learning sculling -- finding a rhythm is as much about 
feeling the consequences of a set of movements on the water, as water 
conditions vary, as it is executing a specified set of moves in order.

From: Friam  On Behalf Of Prof David West
Sent: Monday, February 12, 2024 7:15 AM
To: friam@redfish.com
Subject: Re: [FRIAM] The problems of interdisciplinary research

The notion of search brings to mind two different experiences:

1- traditional "searching" of the library via the card catalog (yes, I know I 
am old) for relevant inputs; and,
2- the "serendipity of the stacks"—simply looking around me at the books I 
located via search type 1 to see what was in proximity.

My experience: the second type of "search" was far more valuable, to me, than 
the first.

Also, with the books found via search '1-', the included bibliography was 
frequently of more ultimate use than the book containing the bibliography.

Computerized search—ala Google—has always seemed limited; precisely because it 
is exclusively search type '1-'. (Even Google Scholar) Attempts to "improve" 
search by narrowing it on the basis of prior searches makes it really, really, 
worse.

LLM based search seems, to me, to have some capability to approximate the 
serendipity of the stacks.

davew


On Mon, Feb 12, 2024, at 6:12 AM, David Eric Smith wrote:
It’s kind of fascinating.

I imagine that one of the next concepts to come into focus will be “curiosity”. 
 I remember a discussion years ago (15? 18?), I think involving David K., about 
what the nature of “curiosity” is and what role it plays in learning.

Where the paper talks about supervision to train weights, but eschewing 
“search” per se as a component of the capability learned, it makes me think of 
the role of search in the pursuit of inputs, the ultimate worth of which you 
can’t know at the time of searching.  I can imagine (off the cuff) that 
whatever one wants to mean by “curiosity”, it has some flavor of a non-random 
search, but one not guided by known criteria, rather by appropriateness to fit 
existing gaps in (something: confidence? consistency?).

This also seems like it should tie into Leslie Valiant’s ideas in Probably 
Approximately Correct about how to formally conceptualize teaching in relation 
to learning.  I guess Valiant is now considered decades passe, as AI has 
charged ahead.  But the broad outlines of his argument don’t seem like they 
have become completely superseded.

We already have “attention” as a secret sauce with important impacts.  I wonder 
when some shift of architectural paradigm will include a design that we think 
is a good formalization of the pre-formal gestures toward curiosity.

Eric



On Feb 10, 2024, at 8:19 PM, Marcus Daniels 
mailto:mar...@snoutfarm.com>> wrote:

If one takes results like this -- https://arxiv.org/abs/2402.04494 -- and then 
consider what happens with, say, Code Llama, it seems plausible that it is 
representing both the breadth and depth of what humans know about large and 
complex code bases.   It is not clear to me why knowledge can’t be extended far 
beyond what the highest-bandwidth humans can learn in a lifetime.   I agree 
mastery of the idiomatic patterns could constrain invention, though.   For 
software engineering, the most impressive people to me are those that can 
navigate large and complex code bases, often remembering a lot of the code, but 
also can discard whole modules at a time and reimagine them.Managers are 
suspicious of such people because managers want to modularize expertise for 
division of labor.   Scrum is in some sense a way to impede the development of 
expertise and to deny the need for it.

From: Friam mailto:friam-boun...@redfish.com>> On 
Behalf Of David Eric Smith
Sent: Saturday, February 10, 2024 2:25 AM
To: The Friday Morning Applied Complexity Coffee Group 
mailto:friam@redfish.com>>
Subject: Re: [FRIAM] The problems of interdisciplinary research

There’s a famous old rant by von Neumann, known at least by those who were 
around to hear it, or so I was told by Martin Shubik.

von Neumann was grumping that “math had become too big; nobody could understand 
more than 1/4 of it”.  As always with von Neumann, the point of saying 
something included an element of self-aggrandizement: von Neumann was inviting 
the listener to notice that _he_ was 

Re: [FRIAM] The problems of interdisciplinary research

[Prof David West]

The notion of search brings to mind two different experiences:

1- traditional "searching" of the library via the card catalog (yes, I know I 
am old) for relevant inputs; and,
2- the "serendipity of the stacks"—simply looking around me at the books I 
located via search type 1 to see what was in proximity.

My experience: the second type of "search" was far more valuable, to me, than 
the first.

Also, with the books found via search '1-', the included bibliography was 
frequently of more ultimate use than the book containing the bibliography.

Computerized search—ala Google—has always seemed limited; precisely because it 
is exclusively search type '1-'. (Even Google Scholar) Attempts to "improve" 
search by narrowing it on the basis of prior searches makes it really, really, 
worse.

LLM based search seems, to me, to have some capability to approximate the 
serendipity of the stacks.

davew


On Mon, Feb 12, 2024, at 6:12 AM, David Eric Smith wrote:
> It’s kind of fascinating.
> 
> I imagine that one of the next concepts to come into focus will be 
> “curiosity”.  I remember a discussion years ago (15? 18?), I think involving 
> David K., about what the nature of “curiosity” is and what role it plays in 
> learning.  
> 
> Where the paper talks about supervision to train weights, but eschewing 
> “search” per se as a component of the capability learned, it makes me think 
> of the role of search in the pursuit of inputs, the ultimate worth of which 
> you can’t know at the time of searching.  I can imagine (off the cuff) that 
> whatever one wants to mean by “curiosity”, it has some flavor of a non-random 
> search, but one not guided by known criteria, rather by appropriateness to 
> fit existing gaps in (something: confidence? consistency?).
> 
> This also seems like it should tie into Leslie Valiant’s ideas in Probably 
> Approximately Correct about how to formally conceptualize teaching in 
> relation to learning.  I guess Valiant is now considered decades passe, as AI 
> has charged ahead.  But the broad outlines of his argument don’t seem like 
> they have become completely superseded.
> 
> We already have “attention” as a secret sauce with important impacts.  I 
> wonder when some shift of architectural paradigm will include a design that 
> we think is a good formalization of the pre-formal gestures toward curiosity.
> 
> Eric
> 
> 
> 
>> On Feb 10, 2024, at 8:19 PM, Marcus Daniels  wrote:
>> 
>> If one takes results like this -- https://arxiv.org/abs/2402.04494 -- and 
>> then consider what happens with, say, Code Llama, it seems plausible that it 
>> is representing both the breadth and depth of what humans know about large 
>> and complex code bases.   It is not clear to me why knowledge can’t be 
>> extended far beyond what the highest-bandwidth humans can learn in a 
>> lifetime.   I agree mastery of the idiomatic patterns could constrain 
>> invention, though.   For software engineering, the most impressive people to 
>> me are those that can navigate large and complex code bases, often 
>> remembering a lot of the code, but also can discard whole modules at a time 
>> and reimagine them.Managers are suspicious of such people because 
>> managers want to modularize expertise for division of labor.   Scrum is in 
>> some sense a way to impede the development of expertise and to deny the need 
>> for it.
>>  
>> *From:* Friam  *On Behalf Of *David Eric Smith
>> *Sent:* Saturday, February 10, 2024 2:25 AM
>> *To:* The Friday Morning Applied Complexity Coffee Group 
>> *Subject:* Re: [FRIAM] The problems of interdisciplinary research
>>  
>> There’s a famous old rant by von Neumann, known at least by those who were 
>> around to hear it, or so I was told by Martin Shubik.  
>>  
>> von Neumann was grumping that “math had become too big; nobody could 
>> understand more than 1/4 of it”.  As always with von Neumann, the point of 
>> saying something included an element of self-aggrandizement: von Neumann was 
>> inviting the listener to notice that _he_ was the one who could understand a 
>> quarter of all existing math at the time (whether or not such an absurdity 
>> could be called “true” in any sense).
>>  
>> I have wondered if this problem marks a qualitative threshold from which to 
>> define a “complex systems” science.  The premise would be that all 
>> innovations ultimately occur in individual human heads, triggered somehow.  
>> (And much of the skill of science is to structure your environment of 
>> reading and experience and people to “trigger” you in productive ways, since 
>> insight isn’t something that can be willed into existence).  But those ideas 
>> need to be answerable to the fullest scope of whatever is currently 
>> understood that is pertinent.  
>>  
>> The old answer used to be to cram more and more of current knowledge into 
>> single heads as the fuel for their insights, and then to limit to more and 
>> more rarified heads that could hold the most and still 

Re: [FRIAM] The problems of interdisciplinary research

[David Eric Smith]

It’s kind of fascinating.

I imagine that one of the next concepts to come into focus will be “curiosity”. 
 I remember a discussion years ago (15? 18?), I think involving David K., about 
what the nature of “curiosity” is and what role it plays in learning.  

Where the paper talks about supervision to train weights, but eschewing 
“search” per se as a component of the capability learned, it makes me think of 
the role of search in the pursuit of inputs, the ultimate worth of which you 
can’t know at the time of searching.  I can imagine (off the cuff) that 
whatever one wants to mean by “curiosity”, it has some flavor of a non-random 
search, but one not guided by known criteria, rather by appropriateness to fit 
existing gaps in (something: confidence? consistency?).

This also seems like it should tie into Leslie Valiant’s ideas in Probably 
Approximately Correct about how to formally conceptualize teaching in relation 
to learning.  I guess Valiant is now considered decades passe, as AI has 
charged ahead.  But the broad outlines of his argument don’t seem like they 
have become completely superseded.

We already have “attention” as a secret sauce with important impacts.  I wonder 
when some shift of architectural paradigm will include a design that we think 
is a good formalization of the pre-formal gestures toward curiosity.

Eric



> On Feb 10, 2024, at 8:19 PM, Marcus Daniels  wrote:
> 
> If one takes results like this -- https://arxiv.org/abs/2402.04494 -- and 
> then consider what happens with, say, Code Llama, it seems plausible that it 
> is representing both the breadth and depth of what humans know about large 
> and complex code bases.   It is not clear to me why knowledge can’t be 
> extended far beyond what the highest-bandwidth humans can learn in a 
> lifetime.   I agree mastery of the idiomatic patterns could constrain 
> invention, though.   For software engineering, the most impressive people to 
> me are those that can navigate large and complex code bases, often 
> remembering a lot of the code, but also can discard whole modules at a time 
> and reimagine them.Managers are suspicious of such people because 
> managers want to modularize expertise for division of labor.   Scrum is in 
> some sense a way to impede the development of expertise and to deny the need 
> for it.
>  
> From: Friam mailto:friam-boun...@redfish.com>> On 
> Behalf Of David Eric Smith
> Sent: Saturday, February 10, 2024 2:25 AM
> To: The Friday Morning Applied Complexity Coffee Group  >
> Subject: Re: [FRIAM] The problems of interdisciplinary research
>  
> There’s a famous old rant by von Neumann, known at least by those who were 
> around to hear it, or so I was told by Martin Shubik.  
>  
> von Neumann was grumping that “math had become too big; nobody could 
> understand more than 1/4 of it”.  As always with von Neumann, the point of 
> saying something included an element of self-aggrandizement: von Neumann was 
> inviting the listener to notice that _he_ was the one who could understand a 
> quarter of all existing math at the time (whether or not such an absurdity 
> could be called “true” in any sense).
>  
> I have wondered if this problem marks a qualitative threshold from which to 
> define a “complex systems” science.  The premise would be that all 
> innovations ultimately occur in individual human heads, triggered somehow.  
> (And much of the skill of science is to structure your environment of reading 
> and experience and people to “trigger” you in productive ways, since insight 
> isn’t something that can be willed into existence).  But those ideas need to 
> be answerable to the fullest scope of whatever is currently understood that 
> is pertinent.  
>  
> The old answer used to be to cram more and more of current knowledge into 
> single heads as the fuel for their insights, and then to limit to more and 
> more rarified heads that could hold the most and still come up with 
> something.  
>  
> But at some point, that model no longer works because there is a limit (some 
> kind of extreme-value distribution, I guess) to what human heads can hold, at 
> all.
>  
> The project then shifts over into an effort of community design with explicit 
> concerns that are not reducible to head-packing.  How do good insights come 
> into existence, still limited by heads, but properly responsible to much more 
> knowledge than the heads do, or even could, contain?  
>  
>  
> I can, of course, shoot down my own way of saying this, immediately.  In a 
> sense, engineers have been doing this for some very very long time.  No 
> “person” knows what is in a 777 aircraft (or for the Europeans, an A380).  
> Those cases still feel different to me somehow, and like a more standard 
> expansion of the concept of the assembly line and modularization of tasks 
> through reliable interfaces (the various ideas behind object design etc.)  I 
> imagine that the interesting problem