I was introduced to Monty <https://github.com/thousandbrainsproject/tbp.monty> 
something like last year or the year before maybe. It was a presentation and I've 
forgotten who invited them to talk. It was intriguing as an alternative to deep 
learning world modelers.

But I was always a bit leery of the CMP in the sense that it's grounded in *space*. While it seems 
obvious that *animals* (including robots with onboard computers, but not robots tethered to their 
computers) are grounded in 3D space (+ time), it's not at all obvious that things like 
interoception is so grounded. So, given others may know more about Monty or the whole program of 
1kbrains, can we formulate CMP hypotheses based on something akin to "poses", but in 
other homeostaic/allostatic "spaces"?

To be clear, it seems to me that such "spaces" can be inferred by the deep 
learning modelers like VLA or JEPA. But Monty seems a bit top-down ... like it's imposing 
how *we* work onto the artificial organisms we might one day build. (That's not 
pejorative ... just evidence of a slightly different purpose.)

On 7/7/26 3:46 PM, Steve Smith wrote:
*Hierarchy or Heterarchy? A Theory of Long-Range Connections for the 
Sensorimotor Brain - Hawkins, et al*

    https://arxiv.org/abs/2507.05888

Do heterarchies of turtles have tops and bottoms?



    "what did the snail riding on the turtle's back say?"

             "wheee!"


On 7/7/26 10:10 am, glen wrote:
Yeah, something like that, I guess. But the voting isn't as important as the process that 
assembles/reduces the votes. So w.r.t. to doxastic voluntarism, when I (a percolating 
stew of circuits, some small, some large) accidentally burp out an action - like punching 
a Patriot Front nazi in the throat - a very large feedback loop holds "me" 
(this percolating stew) accountable. And then the prosecution and defense go about 
teasing apart the process by which the burp came about (mens rea).

Mugg's mixing board set up seems to assume some kind of teleology I'm not 
comfortable with. I don't *intend* to hate masked men in khaki pants ... I just 
*do*. I can't help it. No amount of adjusting my sliders in any purposeful way 
can change that. I'd have to embed with them for a looooong time so that the 
sliders adjusted themselves. Nazis are *grown* not *made*.

And then we have a bit of a vicious regress. When a small circuit votes, does 
it also comprise a percolating stew of even smaller circuits, whose votes are 
also processed? And if so, is there a larger accountability circuit that has to 
tease apart its reduction process? Is there a bottom turtle?


On 7/7/26 8:49 AM, Frank Wimberly wrote:
Maybe the small, fast, predictive processes "vote"?

Frank Wimberly
140 Calle Ojo Feliz
Santa Fe, NM 87505
505 670-9918

Research: https://www.researchgate.net/profile/Frank_Wimberly2 
<https://www.researchgate.net/profile/Frank_Wimberly2>

On Tue, Jul 7, 2026, 8:35 AM glen <[email protected] 
<mailto:[email protected]>> wrote:

    Of course. You have a knack for pushing my buttons. 8^D

    What irritates me about all this active inference and predictive processing advocacy 
[⛧] is well-represented in the title of that chapter "From Sensorimotor Skills to 
Higher Cognition". [grrrr] The reason I took the time to download it and start 
skimming it was my hope for a thorough *composition* from the very small-fast feedback 
loops to the large-slow ones. There are a lot of citations. So maybe the clues are in 
there. But I'm lazy.

    What I *want* ... what I really really want is evidence of predictive 
processing in a minimal model organism like C. Elegans or Drosophilia. Such 
exist [1-5]! But now we need something like connectome (or simpler?) circuits 
in more complex organisms that show how small-fast predictive processing 
composes into large-slow predictive processing. Does the model work at *all* 
scales? Only some scales? Is it like a percolating stew of predictions, some of 
which are suppressed by the larger circuits?

    Speaking of which, I discovered this book just last night:

https://bookshop.org/p/books/from-human-reasoning-to-belief-an-empirical-account-joshua-mugg/de6c8394b4e24d99?ean=9781032736952
 
<https://bookshop.org/p/books/from-human-reasoning-to-belief-an-empirical-account-joshua-mugg/de6c8394b4e24d99?ean=9781032736952>

    But as always, it's silly to keep buying books I'll never read. I post it here in the 
hopes that you readers out there might read it and tell me what it says ... or maybe I'll 
buy the epub and feed it to Claude ... or maybe it's read it already? I haven't checked. 
You'll remember we've had such arguments before, when you claimed I *must* believe in the 
floor in order to get out of bed in the morning. And my counter was that it is my *doubt* 
about the existence of the floor that allows me to get out of bed. IDK if Mugg's "DJ 
mixing board" model fits one of our stances better. But I do like it better than the 
overly simplistic fast vs slow thinking model.


    [1] Dimakou A, Pezzulo G, Zangrossi A, Corbetta M. The predictive nature of 
spontaneous brain activity across scales and species. Neuron. Published online 
March 1, 2025. doi:10.1016/j.neuron.2025.02.009
    [2] Kaplan H, Nichols A, Zimmer M. Sensorimotor integration in 
Caenorhabditis elegans: a reappraisal towards dynamic and distributed 
computations. Philosophical Transactions of the Royal Society B: Biological 
Sciences. 2018;373. doi:10.1098/rstb.2017.0371
    [3] Kim A, Fitzgerald J, Maimon G. Cellular evidence for efference copy in 
Drosophila visuomotor processing. Nature neuroscience. 2015;18:1247-1255. 
doi:10.1038/nn.4083
    [4] Lin A, Witvliet D, Hernandez-Nunez L, Linderman S, Samuel A, 
Venkatachalam V. Imaging whole-brain activity to understand behavior. Nature 
reviews Physics. 2022;4:292-305. doi:10.1038/s42254-022-00430-w
    [5] Wang S, Segev I, Borst A, Palmer S. Maximally efficient prediction in 
the early fly visual system may support evasive flight maneuvers. PLoS 
Computational Biology. 2019;17. doi:10.1371/journal.pcbi.1008965


    [⛧] It seems to me that most of the peri-Friston work borders on advocacy 
of the model(s) as opposed to challenging them. But I'm not a scholar. So my 
scope is very small.

    On 7/6/26 8:15 PM, Nicholas Thompson wrote:
     > Hi, Glen,
     >
     > I liked the predictive processing thing.  It coheres with an idea I have 
been kicking around of late.  People tend to think of cognitive processes as 
putting us in touch with the world as it is.  Then we look at that represented 
world and make decisions about the future.  Wouldn't it make more sense for 
cognitive processes to put us in touch with the world as it is going to be? To 
translate that back into monist talk, we live in a world of successive 
anticipations.   As I get more frail, I become aware of all the hard work my 
cerebellum must be doing to anticipate the consequences of any action I might take 
that changes my center of gravity.  A delayed prediction can lead to my taking 
actions that compound a balance prediction and send me to the floor.  it's like I 
am doing judo to myself.
     >
     > Is that annoying enough to feed the beast?
     >
     > Nick
     >
     > On Mon, Jul 6, 2026 at 6:31 PM glen <[email protected] <mailto:[email protected]> 
<mailto:[email protected] <mailto:[email protected]>>> wrote:
     >
     >     It's so dead, here, I figure it can't hurt to post arbitrary 
nonsense I've run across lately:
     >
     >     Meningeal lymphatic architecture and drainage dynamics surrounding 
the human middle meningeal artery
     > https://doi.org/10.1016/j.isci.2025.113693 
<https://doi.org/10.1016/j.isci.2025.113693> <https://doi.org/10.1016/j.isci.2025.113693 
<https://doi.org/10.1016/j.isci.2025.113693>>
     >
     >     Constructing a lower-bound estimate of the global number of insect 
species on a hyperdiverse empirical foundation
     > https://www.pnas.org/doi/10.1073/pnas.2524283123 
<https://www.pnas.org/doi/10.1073/pnas.2524283123> 
<https://www.pnas.org/doi/10.1073/pnas.2524283123 
<https://www.pnas.org/doi/10.1073/pnas.2524283123>>
     >
     >     Predictive Processing: From Sensorimotor Skills to Higher Cognition
     > https://doi.org/10.7551/mitpress/15999.003.0011 
<https://doi.org/10.7551/mitpress/15999.003.0011> 
<https://doi.org/10.7551/mitpress/15999.003.0011 
<https://doi.org/10.7551/mitpress/15999.003.0011>>
     >
     >     As always, I'm reading them in fitful bursts, interleaved across 
each other and all the other open tabs and crap strewn about my desk. So .... 
grain of salt and all.
     >
     >     --

--
8647 ⊥ ɐןןǝdoɹ ǝ uǝןƃ
ὅτε oi μὲν ἄλλοι κύνες τοὺς ἐχϑροὺς δάκνουσιν, ἐγὰ δὲ τοὺς φίλους, ἵνα σώσω.


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