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 <friam-boun...@redfish.com> *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 <mar...@snoutfarm.com
<mailto:mar...@snoutfarm.com>> wrote:
If one takes results like this --https://arxiv.org/abs/2402.04494
<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 <friam-boun...@redfish.com
<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 <friam@redfish.com
<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 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 of idea-finding for complex phenomena are
those that arise when you have modularized as much as you can, and you have run
out of interesting things to add within the modules, because the things you
can’t see transcend them.
But of course I haven’t “made” anything of this string of words, like a
self-help consultancy or the presidency of any institution.
Eric
On Feb 9, 2024, at 7:45 PM, Roger Critchlow <r...@elf.org
<mailto:r...@elf.org>> wrote:
Yeah, it seems like the premise of the cartoon, or maybe Jochen's
interpretation, was that people have limited scopes of application, and the
average scope of application doesn't include interdisciplinary research. But
there are people who have larger scope and have a lot of fun doing
interdisciplinary projects. And if an interdisciplinary group can adapt to its
participant areas of strength, lots of interesting things can happen.
-- rec --
On Fri, Feb 9, 2024 at 3:19 PM Frank Wimberly <wimber...@gmail.com
<mailto:wimber...@gmail.com>> wrote:
I didn't read the article but Carnegie Mellon, where I worked
for almost 20 years, prides itself on the amount of interdisciplinary research
accomplished there.. Herb Simon had appointments in psychology, computer
science, business and public policy, I believe. I was a coauthor of papers in
robotics, public policy, computer science and philosophy.
On Fri, Feb 9, 2024 at 1:54 PM Jochen Fromm <j...@cas-group.net
<mailto:j...@cas-group.net>> wrote:
Tom Gauld describes most of the problems of
interdisciplinary research in a single image
https://www.newscientist.com/article/2389834-tom-gauld-on-areas-of-expertise/
<https://www.newscientist.com/article/2389834-tom-gauld-on-areas-of-expertise/>
-J.
--
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