Fools rush in.... We're about six insights away from AGI, says John Carmack [& I've got perpetual motion figured out]

Lex Friedmand interviews John Carmack. At about 1:50 Carmack says:

I am not a madman for saying that it is likely that the code for artificial general intelligence is going to be tens of thousands of line of code not millions of lines of code. This is code that conceivably one individual could write, unlike writing a new web browser or operating system and, based on the progress that AI has machine learning had made in the recent decade, it's likely that the important things that we don't know are relatively simple. There's probably a handfull of things and my bet is I think there's less than six key insights that need to be made. Each one of them can probably be written on the back of an envelope. We don't know what they are, but when they're put together in concert with GPUs at scale and the data that we all have access to, that we can make something that behaves like a human being or like a living creature and that can then be educated in whatever ways that we need to get to the point where we can have universal remote works where anything that somebody does mediated by a computer and doesn't require physical interaction, that an AGI will be able to do.

He also believes that antecedents of all the critical ideas are already in the literature, but have been lost.

On the six-or-less insights, I'm between agnostic and deeply skeptical (he doesn't know what he's talking about). But on the idea that the existing literature contains important insights that have been lost, that's likely true. My favorite example is Miriam Yevick's 1975 paper, Holographic or Fourier Logic, Pattern Recognition 7, 1975, pp. 197-213. FWIW, that article was published five years after Carmack was born.

Along Weehawken Cove

AGI as shibboleth, symbols [reacting to Jack Clark]

Jack Clark has a LONG tweet stream on AI policy. Though I don’t agree with every tweet – would anyone? – it’s worth at least a quick look. I want to comment on two of the tweets.

AGI as shibboleth, and beyond

Discussions about AGI tend to be pointless as no one has a precise definition of AGI, and most people have radically different definitions. In many ways, AGI feels more like a shibboleth used to understand if someone is in- or out-group wrt some issues.

— Jack Clark (@jackclarkSF) August 6, 2022

Has AGI ever been anything other than a shibboleth? I believe the term was coined in the 1990s because some researchers felt that AI had become stale and focused on specialized domains, so-called “narrow” AI. The phrase “artificial general intelligence” (AGI) was as a banner under which to revive the founding goal of AI, to construct the artificial equivalent of human intelligence.

What researchers actually construct are mechanisms. But no one knows how to specify a mechanism or set of mechanisms for AGI. Oh, sure, there’s the Universal Turing machine which can, in point of abstract theory, compute any computable function. It may be a mechanism, but the idea so abstract that it provides little to no guidance in the construction of computer systems.

AGI, like AI before it, is an abstract goal, a beacon, without a procedure that will lead to it. No matter how vigorously you chase over the surface of the earth for the North Star, you’re never going to get there. And so AGI simply functions as a shibboleth. If you want into the club, you have to pledge allegiance to AGI.

But you don’t need to pledge allegiance in order to construct interesting and even useful systems. So why invent this unreachable goal? Is it just to define a club?

Meanwhile I’ve written a paper in which I define the idea of an artificial mind. I begin by defining mind:

A MIND is a relational network of logic gates over the attractor landscape of a partitioned neural network. A partitioned network is one loosely divided into regions where the interaction within a region is (much) stronger than the interactions between regions. Each of these regions will have many basins of attraction. The relational network specifies relations between basins in different regions.

Note that the definition takes the form of specifying a mechanism involving logic gates and a neural network. Given that:

A NATURAL MIND is one where the substrate is the nervous system of a living animal.

And:

An ARTIFICIAL MIND is one where the substrate is inanimate matter engineered by humans to be a mind.

There are other definitions as well as some caveats and qualifications.

However, those definitions come after 50 pages of text and diagrams in which I lay out the mechanisms that support those definitions. The paper is primarily about the human brain, but one can imagine constructing artificial devices that meet those specifications. Now, whether those specifications are the right specifications, that’s open for discussion. However that discussion turns out, it is a discussion about mechanisms, not myths and magic.

The paper:

Relational Nets Over Attractors, A Primer: Part 1, Design for a Mind, Version 2, Working Paper, July 13, 2022, pp. 76, https://www.academia.edu/81911617/Relational_Nets_Over_Attractors_A_Primer_Part_1_Design_for_a_Mind

Ah, symbols

Here’s a twofer:

Richard Sutton's The Bitter Lesson is one of the best articulations of why huge chunks of research are destined to be irrelevant as a consequence of scale. This makes people super mad, but also seems like a real phenomenon.

— Jack Clark (@jackclarkSF) August 6, 2022

It's the first tweet that interests me, but let’s look Richard Sutton’s bitter lesson. Here’s his opening paragraph:

The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. The ultimate reason for this is Moore's law, or rather its generalization of continued exponentially falling cost per unit of computation. Most AI research has been conducted as if the computation available to the agent were constant (in which case leveraging human knowledge would be one of the only ways to improve performance) but, over a slightly longer time than a typical research project, massively more computation inevitably becomes available. Seeking an improvement that makes a difference in the shorter term, researchers seek to leverage their human knowledge of the domain, but the only thing that matters in the long run is the leveraging of computation. These two need not run counter to each other, but in practice they tend to. Time spent on one is time not spent on the other. There are psychological commitments to investment in one approach or the other. And the human-knowledge approach tends to complicate methods in ways that make them less suited to taking advantage of general methods leveraging computation. There were many examples of AI researchers' belated learning of this bitter lesson, and it is instructive to review some of the most prominent.

Sutton then goes on to list domains where there has proven so: chess, Go, speech recognition, and computer vision. He then draws some conclusions, which I want to bracket.

Note, however, that Sutton talks of researchers seeking “to leverage their human knowledge of the domain.” Is that what’s going on symbolic AI? Perhaps in expert systems, which may have been the most pervasive practical result of GOFAI. But I don’t think that’s an accurate general characterization. That’s not what was going on in computational linguistics, for example, or in much of the work on knowledge representation. That research was based on the belief that much of human knowledge is inherently symbolic in character and therefore that we must create models that capture that symbolic character.

Why did those models collapse? I think there are several factors involved:

1. Combinatorial explosion: Symbolic systems tend to generate large numbers of alternative with little or no way of choosing among them.

2. Hand coding: Symbolic systems have to be painstakingly hand-coded, which takes time.

3. Too many models, difficult to choose among them: This exacerbates the hand-coding problem.

4. Common sense has proven elusive: But then it has proven elusive for deep learning as well.

Perhaps the first problem can be solved through more computing power, though exponential search can easily outstrip the addition of CPU cycles and memory. The third problem is one for science, and is, I believe, entangled with the fourth one. The second problem is inconvenient, but, alas, if hand-coding is necessary, then it’s necessary. But perhaps if we’re clever....

On the fourth one, here’s what I said in my GPT-3 paper:

A lot of common-sense reasoning takes place “close” to the physical world. I have come to believe, but will not here argue, that much of our basic (‘common sense’) knowledge of the physical world is grounded in analogue and quasi-analogue representations. This gives us the power to generate language about such matters on the fly. Old school symbolic machines did not have this capacity nor do current statistical models, such as GPT-3.

Thus the problem is not specific to symbolic systems. It is quite general. It’s not at all clear that we can deal with this problem without having robots out and about in the world. I note that the working paper I mentioned in the previous section, Relational Nets Over Attractors, is about constructing symbolic structures over quasi-analog representations, which, following the terminology of Saty Chary, I characterize as structured physical systems.

Let’s return to Sutton’s paper. Here’s his final paragraph:

The second general point to be learned from the bitter lesson is that the actual contents of minds are tremendously, irredeemably complex; we should stop trying to find simple ways to think about the contents of minds, such as simple ways to think about space, objects, multiple agents, or symmetries. All these are part of the arbitrary, intrinsically-complex, outside world. They are not what should be built in, as their complexity is endless; instead we should build in only the meta-methods that can find and capture this arbitrary complexity. Essential to these methods is that they can find good approximations, but the search for them should be by our methods, not by us. We want AI agents that can discover like we can, not which contain what we have discovered. Building in our discoveries only makes it harder to see how the discovering process can be done.

I’m hesitant to think of symbol systems as being “simple ways to think about the contents of minds.” That strikes me as rhetorical overkill. But Sutton is right about “the arbitrary, intrinsically-complex, outside world.” He says that “we should build in only the meta-methods that can find and capture this arbitrary complexity.” Well, sure, why not?

But are we doing that now? That’s not at all obvious to me. it seems likely to me that the DL community is hoping that they’ve discovered the metamethods, or will do so in the near future, and so we don’t have to think about what’s going on inside either human minds or the machines we’re building. Well, if human minds use symbols, and it seems all but self-evident that we do – if language isn’t a symbol system, what is? – then the current repertoire of DL methods is not up to the task.

What meta-methods are needed to detect patterns of symbolic meaning and construct those quasi-analog representations?

My GPT-3 paper:

GPT-3: Waterloo or Rubicon? Here be Dragons, Version 4.1, Working Paper, May 7, 2022, 38 pp., https://www.academia.edu/43787279/GPT_3_Waterloo_or_Rubicon_Here_be_Dragons_Version_4_1

Spot the Empire State Building

Liszt, childhood, and improvisation

I’ve been reading a fascinating book about improvisation in 19th century classical music, Dana Gooley, Fantasies of Improvisation: Free Playing in nineteenth-Century Music (Oxford 2018). Here’s a passage from a remarkable discussion of conceptions of childhood in relationship to prodigies and improvisation (pp. 204-205):

The prevailing response to both Liszt and Mozart as improvising prodigies was a feeling of wonder and uncanniness. Their mastery of the piano was extraordinary in itself, but their capacity to generate music off the cuff heightened the sense of awe. Improvisation manifested mental and inventive capacities that were thought to belong to adults alone. In his classic study Centuries of Childhood, Philippe Ariès argued that the conception of the child as a different type of being, distinct from adults, be- came more pronounced over the course of the sixteenth and seventeenth centuries, and took its modern form in the educated middle classes of the eighteenth century. The educational philosophy of Rousseau, in particular, promoted the idea that children lack knowledge and need prolonged tutelage to acquire it. Yet Rousseau’s ideas attained general dissemination only in the last quarter of the eighteenth century, after Mozart’s prodigy years, and there is a measurable shift of response between Mozart and Liszt.16 Responses to Mozart were dominated by a discourse of wonder that greeted extraordinary phenomena with assertions of absolute inscrutability. The Englishman Daines Barrington, in his famous 1769 anecdotes of Mozart, did not try to explain how the child prodigy did what he did. Bracketing causal explanations, he merely reiterated the “extraordinary facts” and “amazing and incredible” performances he witnessed, in which improvisations figured prominently: “his extemporary compositions also, of which I was a witness, prove his genius and invention to have been most astonishing.”

By the time of Liszt, however, the conceptual differentiation of children from adults had become more pronounced, and contemporary observers focused less on the “divine gift” than on the precocious maturity of Liszt’s mind. This shift of focus did not entirely kill off the discourse of wonder. A Toulouse paper, for example, reported that “the young virtuoso reawakens the memory of pagan mythology, and it is merely a child that has produced these marvels, this magic, these prodigious feats.” This same review, however, invoked more up-to-date psychological ideas, claiming that “this likeable child manifests a superior mental constitution [organisation].” The notion that a child might possess a mature, adult musical mind had a latent insurgent potential. It suggested that children were not only behavioral mimics, but might also possess independent cognitive-productive power. This was not only at odds with a general perception of children as “unformed,” but also with the way the professional music establishment upheld its authority. As discussed in Chapter 2, improvised free fantasies were often valued for the guild-like learning and professionalism they put on display. Liszt’s fantasies threw into doubt the cherished idea that deep study of harmony and counterpoint were really necessary to improvise well. Czerny, recalling Liszt’s audition to study with him, was struck by the boy’s intuitive grasp of musical rules: “at his father’s request I gave him a theme for improvisation. Without the slightest learned harmonic knowledge he nevertheless brought a certain intelligent sense [genialen Sinn] to his playing.” Critics responded similarly, making a categorical separation between the child’s technical and mental capacities:

Performance on the piano is little more than mechanical work. Thinking, so to speak, plays no role in it . . . but the faculty of improvising music, of pursuing a theme long enough to move from one key to another, of vigorously attacking the most difficult modulations without getting lost and without breaching the rule of composition, this talent is truly the effect of a mind quite particular to the young Liszt. (Pandore, 14 April 1824)20

The baffled responses to Liszt’s early improvisations belong to a more general uncertainty surrounding improvisation. The question of its origins, of how it is possible at all, returns perpetually among both insiders and lay spectators. Answers tend to fall into two polarized lines of explanation: a disenchanted one, according to which it is a “mechanical” reshuffling of learned and practiced patterns, and a quasi-theological one, according to which it channels some supernatural agent or spirit beyond human volition (in romantic discourse, “genius”). Even authors who recognize the binary terms of this debate rarely find a way to avoid them. This persistent undecidability about improvisation’s originating agency affected the discourse around the young Liszt. Any child who exhibited adult-like behavior seemed to cross a “natural” threshold. Paradoxically, though, “nature” also offered the best account of how a child prodigy could do what he did. Liszt, according to the writer just quoted, was “endowed by nature with the rarest capacities.” A conceptual conflict arose between the theory that children’s minds are shaped by conscientious education and the theory that these minds are formed by natural endowments. Liszt’s improvisations pressed this conflict to the fore, and the explanation by “nature” only reaffirmed the mystery of origination.

With the help of his free fantasies Liszt managed to escape the skepticism and suspicion critics increasingly expressed toward child prodigies. In the fifty or sixty years intervening between Mozart and Liszt there had emerged an entire world of keyboard pedagogy oriented specifically toward children—a world represented well enough by Czerny’s incessant stream of private lessons and published exercises. Consequently, musical prodigies and pseudo-prodigies cropped up more often than they had in previous eras. By the 1840s a musical observer could write that “musical child prodigies are shooting up from the ground like mushrooms after a night of warm rain.” It was becoming more difficult to resist the impression that an exceptionally talented child was not the product of a punishing educational regime or an overbearing, exploitative parent.

I’m struck by this sentence: “Any child who exhibited adult-like behavior seemed to cross a ‘natural’ threshold.” It’s interesting to think about that threshold in the context of, for example, Henry Lau’s presentation of young Korean prodigies [1]. He’s aware of both their musical abilities and the fact that they’re still children and is at ease with both roles. But there is also the remarkable performance of the Nakagurose Elementary School band [2]. There’s no reason to believe that any of these children are prodigies, nor is the composition they perform particularly difficult, though few middles-school bands in America could play so well. But, as they perform, they are neither children nor adults; rather, they are simply musicians, human beings engrossed in making music.

References

[1] See my posts:

• Kids and Music 6: Get Aboard Henry Lau’s Freestyle Express [Born to Groove]
• Kids and Music 5: Kwak DaKyung, Jazz Trumpeter [Born to Groove]
• Born to Groove, Kids and Music 3: Henry Lau has a good heart & knows how to work with kids [kawaii alert!]

[2] They are the third of three examples in this post: Born to Groove, Kids and Music 1: Three Examples. I would also call your attention to the second example, Colt Clark and the Quarantine Kids. This is a family band, father (Colt) and three children, Cash (bass), Beckett (drums), and Bellamy, who fronts the band in various ways. While both Cash and Beckett are capable enough, Cash is certainly not at good as Ellen Alaverdyan and Beckett is not as good as either Nandi Bushell or Yoyoka.

So you want to go to Mars? Don't hold your breath.

The neuroscience of memory: Papez, the hippocampus, and beyond

Highlights
• Why it is time for the concept of Papez circuit to be retired
• The anterior thalamic nuclei and hippocampus conjointly support episodic memory
• Focus should now shift to how these two structures jointly interact with neocortex
..

— Shane O'Mara (@ShaneOMara3) August 6, 2022

This analysis complements our recent paper on why hippocampal-centric models of memory are, at best, incomplete: a tripartite model of memory ftw is necessary - https://t.co/UVPPChWQQe

— Shane O'Mara (@ShaneOMara3) August 6, 2022

Memory is complicated, as are the supporting brain systems. We're just scratching the surface.
While you're here, see:
Neural, psychological, and social foundations of collective memory: Implications for common mnemonic processes, agency, and identityhttps://t.co/9hhiVngCNR

— Shane O'Mara (@ShaneOMara3) August 6, 2022

Glenn Loury gets read the riot act by Richard Wolff, a Marxist economist

Friday Fotos: Night light

Persuasion, Clueless [Media Notes 77] {mediated desire}

I’ve just watched the recent movie adaptation of Jane Austen’s Persuasion and Clueless, which is a loose adaptation of Austen’s Emma. First, I want to comment very briefly on the Girardian nature of both plots and then offer some comments on adaptation.

Mimetic desire in the films

For whatever reason I didn’t watch Persuasion in a single sitting. I forget whether it was late in the first sitting or during the second sitting that I noticed, Hey! this story is steeped in mimetic desire. The heroine, Anne, doesn’t realize that she’s still in love with an old flame until he is both pursued by and pursues her best friend. That’s classic Girard, and in the medium in which he did his original research, the novel.

A couple days later I decided to watch Clueless, though I have a vague sense that I may have seen it in theaters on original release in 1995. Sure enough, about two-thirds of the way through or so the heroine, Cher, realizes that she’s in love with Josh when she realizes that she’s jealous of Tai’s interest in him (Tai is a new friend).

In both films we see mimesis working in other relationship pairings as well, but I have no intention of working any of this out. This is mostly a note to myself.

I will observer, however, that I’ve never been a Girardian. I became aware of his ideas about mimetic desire and sacrifice from lectures he gave a Johns Hopkins when I was an undergraduate. Later I read Violence and the Sacred with some care when the English translation came out in 1977, but I’ve forgotten it. Girard never made it into my working repertoire until earlier this year I decided to write about Jaws, and there I called on my friend, David Porush, to validate my Girardian interpretation as David knows Girard’s thought much better than I do.

Here's the thing: If I’m to do much work with Girard’s ideas I’m going to have to recast them into a more contemporary intellectual form. I have no idea what that would look like or how much apparatus building it will require. As it is, Girard is just another humanist with his feet in the 19th century.

Adaptation: Clueless

Since I’ve not read Emma, I have no idea just how loose the adaptation is. Obviously the setting has changed enormously. Mores have as well; there’s a fair amount of talk about virginity that wouldn’t have happened in Austen. But it’s the plot that matters most and I have no way of judging that.

However, I’m pretty sure that the film makers were not counting on an audience familiar with Emma, any more than the makers of Forbidden Planet were counting on an audience familiar with The Tempest. They’re just doing what story tellers have always done, borrow, steal, and adapt.

Adaptation: Persuasion

Persuasion is a different story. Here I think there is some presumption that viewers will at least know that this is an adaptation of an early 19th century novel and even that a significant portion of the audience will have read the novel. I have not, but I do know that it is a 19th century novel. Apparently it has received quite a bit of criticism for anachronism. I supposed I could care less about “breaking the fourth wall,” nor am I so much concerned that Anne apparently is a bit more free-spirited that Jane depicted her, though perhaps this should bother me.

But I am somewhat puzzled that the film offers up black aristocrats in early 19th century England, which is certainly an anachronism. Surely they don’t think any viewers will believe that this is authentic. I have a vague general idea about why this is being done – something about egalitarianism – but that general idea collapses upon inspection. For the same general sensibility argues against so-called “color blind” casting on the grounds that only black people can pretend to be other black people with full depth and authenticity, only East Asians can pretend to be and so forth and so on. Except in this case, 21st century black actors can play early 19th century white English aristocrats.

In this case I suppose one can resort to Ralph Waldo Emerson: “A foolish consistency is the hobgoblin of little minds, adored by little statesmen and philosophers and divines.” Somehow, though, I don’t think this is what he had in mind.

What are the chances we’ll outgrow this?

High wire act [Hoboken]

From My Notes: Religion and Music in America

References:

Ann Taves, Fits, Trances, & Visions, Princeton UP, 1999.

Richard Crawford, America’s Musical Life, WW Norton, 2001.

Hymns

FWIW, it seems that the first full-length book printed on American soil in the English-speaking colonies was a hymnal, in 1640, the so-called Bay Psalm Book (Crawford 2001, p. 23).

Note that European American hymnody established its own methods during the 17th and 18th centuries. While obviously drawing on European sources, these methods were nonetheless different in style, reflecting the reformist intent of the Puritans, etc.

Religious Experience

According to Taves, religious experience was a major concern to protestants, especially the Methodists. Some denigrated and discouraged the fits, trances, and visions that constituted such experience while others valued and even cultivated them. For my purposes, these experiences from the tertium quid between European and African cultures. It is thus on sacred ground that European and African cultures first met on more or less equal terms during the Second Awakening that straddled the turn of the 19th century in N. America.

The major locus of this awakening was the camp meeting. These meetings took place outside institutional religion, both physically – they were generally held in rural areas – and institutionally – they were not sponsored by any one domination, though ordained ministers preached at them. They generally lasted for several days of prayer, preaching, and song. Both blacks and whites attended the meetings, and they often attended the same meeting, though the camp grounds were often segregated – which segregation was often broken down on the final day of a meeting.

Judging from available accounts, the singing style owed more to African-American models than to European or even European-American models. The lyrics were rudimentary and repetitious and there was a great deal of call and response – which may own as much to New England “lining out” as to Africa. Often hymns were stitched together back to back in continuous performance. The style seems to have been joyful and unrestrained and the music would go on for hours at a time.

There were lots of these meetings, by one account, 1811 saw 400 of them. Often thousands of people attended a single meeting. The fact that they took place outside ordinary religious institutions is, of course, anthropologically significant. These meetings would seem to constitute a liminal zone (Victor Turner’s term) outside the institutions of the formal culture. Even though segregation was often maintained at these meetings, they constituted an arena in which blacks and whites interacted on a different basis from that of ordinary life. It may not have been equality, but it’s not clear that the difference maintained within the meeting was hierarchical either. It was simply difference. Of course, when folks left the meeting, hierarchy was restored to difference.

This then, forms the originating bond, the natal connection, between African and European cultures. This style died out in the North during the 19th century but persisted in the South, both black and white, and especially in the rural South. When blacks migrated from the South in the early 20th century they took their ecstatic religion with them (with a bit of help from the Pentecostals). But it wasn’t until the mid 1950s that this ecstatic style would surface in the mainstream of secular American culture.

Ecstasy in the 20th Century

Jazz and blues emerged during the early 20th century, with swing jazz becoming the dominant popular music during the 1930s. Jazz seems derived from mostly secular traditions (brass bands, minstrelsy, and so forth), though many of the musicians were raised in ecstatic churches. Swing disintegrated after WWII, but many of its devices persisted in the small group form that became rhythm and blues. During the mid 1950s this tradition linked up with its sacred cousins.

On the one hand, we have the music of Chuck Berry, Fats Domino, Little Richard (Penniman), Jerry Lee Lewis, and Elvis Presley; this became rock and roll. Penniman, Lewis, and Presley were all raised in ecstatic churches. On the other hand, we have Ray Charles taking gospel music and putting secular words to it, giving us the birth of soul music. These two styles then developed in parallel through the 1960s and into the 1970s, with Motown running down the middle.

At the same time, jazz gets “soul” during the middle and late 50s with Art Blakey, Horace Silver, Charles Mingus and others. And during the early 1960s Coltrane emerges as the avant-garde avatar of jazz spirituality. Henceforth, overtly spiritual music would become a fixture of the avant-garde, mixing freely with African and Indian influences and shading easily into furious “energy” music where anger was as on an equal footing with devotion as an emotional force.

* * * * *

See earlier posts on

• Camp Meetings, Music, and the Civil War: Some Quick Notes on Culture as a Historical Force
• Appalachian Soul

Christmas exotica [Longwodd Gardens]

Structured physical system hypothesis (SPSH), Polyviscous connectivity [The brain as a physical system]

Over in the discussion of Yann LeCun’s recent paper (A Path Towards Autonomous Machine Intelligence), Saty Chary has been arguing for something he calls the Structured Physical System Hypothesis (SPSH):

‘A structured physical system has the necessary and sufficient means for specific intelligent response’. By structured physical system, I mean, an analog design, e.g. a Rube Goldberg apparatus, or a Braitenberg (!) vehicle, etc. This is in contrast to this: PSSH - Physical Symbol System Hypothesis - 'A physical symbol system has the necessary and sufficient means for general intelligent action'.

I would add the slide rule as another example. From Wikipedia:

The slide rule is a mechanical analog computer, which is used primarily for multiplication and division, and for functions such as exponents, roots, logarithms, and trigonometry. It is not typically designed for addition or subtraction, which is usually performed using other methods. Maximum accuracy for standard linear slide rules is about three decimal significant digits, while scientific notation is used to keep track of the order of magnitude of results. [...]

At its simplest, each number to be multiplied is represented by a length on a pair of parallel rulers that can slide past each other. As the rulers each have a logarithmic scale, it is possible to align them to read the sum of the numbers' logarithms, and hence calculate the product of the two numbers.

My father used a slide rule for his entire career as an engineer. I learned to use one in my teens – everyone did back that – but never had any use for one. They’ve been replaced by cheap electronic calculators and PCs.

But that’s a digression. It’s the more general Structured Physical System Hypothesis that interests me, as Saty has been argued that the brain is such a system I agree (see this recent post, Once more around the merry-go-round: Is the brain a computer?). Here’s my reply to Saty:

Hi, Saty. I like your hypothesis – Structured Physical System Hypothesis (SPSH) – a lot. I think that a lot about the brain is consistent with it. For example, we know that mappings from one area to another as we move from the sense organs (or muscles), to the subcortex, and into the cortex tend to preserve topological relations between neurons. That’s of obvious value in the visual and motor systems. But there are subtleties. In the cortical visual system we have a so-called What-system and a so-called Where-system beyond the primary cortex. The What-system tracks location in space while the Where-system identifies objects. I assume that the Where-system has links to the hippocampus and I’d expect it can deal with both ego-centric and geocentric coordinates (this must be in the literature). But I’d think the What-system deals in object-centered coordinates. And so forth and so on.

In thinking about Freeman’s results, and others, I’ve coined a phrase: polyviscous connectivity. Thus I say that the cortical network as a whole exhibits polyviscous connectivity. What do I mean? Some connections are highly resistant to change, and thus have high viscosity. Others change quite readily, and have low viscosity. There is a literature on long-term (LTP) and short-term potentiation (STP) of neural connectivity that is certainly relevant here, but I’ve not looked at it in quite a while.

Consider Freeman’s results. He’s measuring neural activity with an 8 by 8 array of electrodes mounted on the cortical surface. They’re going to detect activity of neurons at varying levels of viscosity. Let’s a assume that the patterns of connectivity encoding odorants that rat already recognizes have a relatively high viscosity. Let’s further assume that the neurons most susceptible to learning new odorants have a relatively low viscosity.

Once they’ve formed a stable response to the new odorant that will result in a new pattern of neural activity for the ensemble. But it is also going to change the patterns exhibited by already learned odorants even though the high-viscosity connections haven’t changed. The high viscosity connections maintain the overall integrity of the ensemble. In time, if the new odorant continues to be encountered, the connections registering it will increase in viscosity. So, polyviscous connectivity allows a structured connectionist physical system to maintain its overall integrity while adding new items to its repertoire.

More later.

* * * * *

Note: Looking around on my hard-drive I found an article which is about what I have called polyviscosity, though it doesn’t use that term:

Poonam Mishra and Rishikesh Narayanan, Stable continual learning through structured multiscale plasticity manifolds, Current Opinion in Neurobiology 2021, 70:51–63, https://doi.org/10.1016/j.conb.2021.07.009

Abstract: Biological plasticity is ubiquitous. How does the brain navigate this complex plasticity space, where any component can seemingly change, in adapting to an ever-changing environment? We build a systematic case that stable continuous learning is achieved by structured rules that enforce multiple, but not all, components to change together in specific directions. This rule-based low-dimensional plasticity manifold of permitted plasticity combinations emerges from cell type–specific molecular signaling and triggers cascading impacts that span multiple scales. These multiscale plasticity manifolds form the basis for behavioral learning and are dynamic entities that are altered by neuromodulation, metaplasticity, and pathology. We explore the strong links between heterogeneities, degeneracy, and plasticity manifolds and emphasize the need to incorporate plasticity manifolds into learning-theoretical frameworks and experimental designs.

* * * * *

Note: I’d previously been using the terms “hyperciscosity” or “hyperviscous”, and you’ll find them in my posts and notes on this topic going back to 2013 (when I wrote about From Associative Nets to the Fluid Mind). But I have reluctantly decided to coin a new term since “hyperviscosity” is already being used.

The return of analog computing [artificial intelligence]

Tight Like This: A Tale of High Adventure in Ancient Nubia [the fourth arena]

I'm bumping this to the top of the queue. Why? Because I can, that's why. Because the world's got to change and it's got to change NOW. You know, now's the time! We've been mugged by the future and don't realize it. We're still waiting for jet packs when the time for jet packs has done come and gone. There isn't going to be any AGI (artificial general intelligence) coming down the pike, not in time to make a difference and maybe not ever. Get real and figure out how we're doing to deal with a network of self-driving cars that can learn. Anyhow, this is going to require major changes in how we think, and that's going to require a new mythology. I figure maybe old Golfotep and the Mystic Jewels have something to say about that.

I published this on The Valve some years ago and, as the introductory note says, I'd published it on Meanderings, now defunct, before that. No doubt I will republish it somewhere else sometime in the future. Or maybe someone will make it into a movie. Who knows.

Oh, and be sure to check out Tight Like This (this is Wynton Freakin' Marsalis, Armstrong link in text below).  High drama & low-down hoochie coochie. 

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Jivometrics

Back in the mid 1990s, about the time Mosaic was being unleashed on the internet, I met a fellow in the African-American Forum at AOL Online. Called himself Cuda Brown. We hit it off and began emailing privately. Before you know it we were collaborating on a website called Meanderings - which later became Gravity. Cuda did most of the work, including all of the HTML coding and the back-end database coding. I helped editorially, wrote some pieces, and did some art.

One day I sent Cuda an email containing a spur-of-the moment paragraph satirizing Afrocentrism, something much discussed at Meanderings. While Cuda and I were sympathetic, we were doubtful about the more inventive flavors of the brew. Thus I had improvised something about golf being invented by one Pharoah Golfotep: the primo white-shoe Anglo country club plus-fours game was invented in ancient Egypt. What could be sillier? Over the next two weeks, however, this little bit of satire jes grew and grew, like Topsy, and became something else.

So, we posted it in Meanderings, which may have become Gravity by that time, I forget. And people read it. In time, however, Gravity died. Since then I've been looking for a place to revive “Fore Play.” Well, here it is. Let's call it a cultural studies primer for the new millennium.

Some of it is a bit dated. Who remembers Dennis Rodman, much less his experimental tonsorial stylings? Back then Tiger Woods was more potential than achievement – but what potential! – while boom boxes have now bifurcated into iPods and beat boxes. "Muggles" hadn't become a Potteresque term of art for – well, just what exactly, non-magicals? (I've never read any of the books.) Back then I used it as the name of a Louis Armstrong blues and I'm sticking to it. It's also old New Orleans slang for something Bill Clinton didn't inhale.

Otherwise, it's pretty much now as it was then. Only back then the turn of the millennium was in the future. Now it's in the past.

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Fore Play:

A Lesson in Jivometric Drummology


Jefferson Ribonucleic Parker IV

aka

Mr. Ribs

Tiger Woods is only the most recent in a long line of fine black golfers. In saying that I refer to players other than the moderns such as Charles Sifford, Jim Thorpe, Jim Dent, Lee Elder, Calvin Peete, and Renee Powell. Truth be told, the tradition of sepia swing masters started in ancient Egypt, where the game was invented. In that company Woods would be no more than a middling player.

By today's standards Tiger is ferociously talented and filled with promise for the future. Perhaps he'll become the best in post-modern times, the primo putter of the 21st Century, the first master to break par on the New Savanna. But those African drivers of ancient Egypt were giants the like of which haven't been seen in thousands of years.

Their stories, like so many stories, have been suppressed by the Europeans. Fortunately many of those stories have been collected by The Order of Mystic Jewels for the Propagation of Grace, Right Living, and Saturday Night through Historic Intervention by Any Means Necessary. The Jewels are dedicated to preserving the ancient stories and to intervening in history in ways variously clever and indirect. They are the chief source of that version of Afrocentric thinking known as Jivometric Drummology. In her classic study, Klactoveededstene: Riffing the Noumena, Ella Birks Roach defined the basic concept thus:

Jivometric Drummology: A philosophical system grounded in African and African-American musical practice. “Drummology” indicates that the governing logos is that of the drum, of rhythm, of hands and sticks coaxing sound from skin, of people joining together, each playing a simple rhythm, with the many simple rhythms melting into a single stream of infinite diversity. “Jivometric” is here because of the way it rolls off the tongue and tickles the ear; its meaning is secondary to its sound. Jivometrics is thus a principle of grace. When jivometrics is in play outer sonic auras join in the creation of tones played by no one, but heard by all. A treatise may have drummological ideas, but if the language lacks grace, then the treatise is not jivometric -- jiveturkey is all too often the appropriate term. In the most profound works of this school jivometrics and drummology are joined through agape.