Agenda 2025

Revectoring Through Myth

:: language project video ::

The deep learning model inspires many metaphors, including that of the ancestral tree, wherein you don't get to back propagate exactly, but you do carry a memory of previous weights and so still might enjoy gradient descent over time. It's just a matter of compressing the older layers into memories as the "wave of time" rolls forwards. No math need change really, it's just a gestalt. The Fall of Man is our Gradient Descent towards Omega (falling towards God, not away from, but lagging behind).

Those following my twists and turns (why would they?) would find a long term fascination with "cult" as a term and my seeking to give it neutral grounding in "subculture". Then comes Cultagory Theory (a play on Category Theory) and Cultography, a stand-in for Anthropology but also a play on Cosmography (one of Fuller's, posthumous thanks to Kiyoshi Kuromiya).

My anchoring in this lineage jibes with the Subgenius / Discordian lineage and that Encyclopedia of Conspiracies, my website cited. That won me cred, and I'm not trying to shy away from where Fuller was going with his Grunch conspiracy (not his alone by definition, hello Marshall McLuhan).

What's some of the "revectoring" that I'm doing, outside the cube vs tetrahedron stuff that you've maybe seen a lot of by now?

My insight is when Greek mythology was still a working living system, the screenwriters would steer the melodrama to both guide and mirror the pluribus unum in that unum nation we call Greece (a meme city, or complex, more spread out than hard borders would show). They'd invent some new story, those high priests would, as they divined what the people needed. Next stop: the amphitheaters, the Broadway of that day (or Times Square).

I'm resurrecting those mythological motifs in my story about Athena, daughter of Zeus, establishing her oracular base in Delphi, omphalos of Middle Earth. The Pronea, and female aspect of the Pythia, persisted into the Age of Apollo, supposedly beginning with his slaying of the Python, in this new version Athena's pet.

The Python got away, but the Apollonians didn't need to know that, as the dragon snake no longer frequented Parnassus, the new establishment could say, which was true enough. But in a somewhat Mormon move, I move the scene to the western hemisphere, to Nashville, Tennessee, where a new Temple to Athena is built under World's Fair auspices. Athena and her Python, as well as Nike, are re-established and spread their music.

This motif has woven through these blogs back through OSCONs, when Gibson Guitar sent a bizmo to Portland, Silicon Forest, newest Capital of Open Source. The geek with the laptop was akin to the solo musician with a guitar. To program is to compose. We were the new Cult of Athena, with our PyLadies.

Back in Delphi, Apollo is always contrasted with Dionysus. Opposed to the pure light of rationality are the dark impulses of the introverted emo, frustrated by Apollonian fascism and periodically overturning the rules based order, in need of an overdue paradigm shift.  But that's not the dynamic here in the western hemisphere ("the west" once revectored), as the Athenian vibe ain't the Apollonian one -- he's her half brother BTW. Different polarity.

Perhaps the most stable arrangement for now is a triangle, although not a romantic one, more a power dynamic. Apollo and Dionysus aren't getting to trade places to rectify matters as Athena is keeping her cool, using the tension towards more creative ends, a different chaos (unpredictable content).  Like I said, this is how we programmed (steered within) the Zeitgeist back in the day, before Mad Magazine and Madison Avenue. Before Freud and Bernays. 

The slides in the above YouTube do not include subsequent slides giving more details regarding my Just Use It campaign. Mostly I'm back to "Zionetics" and "Church of Bucky" type stuff (as Snelson called it).

Iconography: A is for Apex

A is for self.Actualization()

Draft Text

Given I’m of the Quaker persuasion (there’s a more formal name) my angle on politics is who cheerleads wars? These are the ones I’m biased to disown, but I train myself to hear their arguments, partly so I understand what I’m up against.

Usually people who cheerlead for war are coming from a victim mindset, which typically involves wanting vengeance and redress, fantasizing about having someone get their comeuppance and so forth. That’s the pattern.

Does this mean Quakers don’t play victim? Of course we do. Speaking as a victim is like a tense in the language, akin to the subjunctive. 

Quakerism is more a monkey-bars / jungle gym of potentially beneficial workout practices, doing committee work, than it is a geopolitical ideology. 

Hatched in the 1600s, it knows nothing of many 21st Century obsessions. Yet committee work in support of a Meeting (a kind of business) remains an important opportunity.

Work out in a Quaker gym, so to speak, and you’ll probably become a more effective hotelier or restaurateur, because you were already not an avatar of violence, and therefore receptive to our teachings. 

However, if you’re an advocate for war, yet wish the attention of our Overseers (supervisors), don’t presume that your victimhood will go unchallenged, if indeed that’s what’s driving your despicable warmongering.

Cultagory Theory (School of Tomorrow)

In the minds of some fans, presuming fans, the above might seem a bold new direction, in terms of stepping onto the world stage. But for me it's more a tying off loose ends, as I've got these long running themes I've made some waves about, and now want to further contextualize, while I'm around to do so.

However, I'm not denying there's new content. The "USA OS" meme has burgeoned and I've been in meetings about it. My School of Tomorrow curriculum has come together more tightly.

On the matter of where and how to introduce cryptography, I want to keep Elizebeth Friedman one of the portals and her crusade against the rumrunners. Glenn Stockton educated me about this chapter. He'd been a cryptanalyst (a code breaker) himself and during his stint with the NSA, Elizebeth's husband William's works, which she'd help organize, were still classified.

The Roaring 20s, Prohibition, and Bucky Fuller's experiences with radio, including encryption, sets up a  prequel chapter to WW2, with Alan Turing and the Martians of Science (see Istvan Hargittai's book). The Vienna Circle features prominently as well, for its contributions to logic, music, and psychoanalysis. We pick up on Fuller's remarks about Freud and the importance of the invisible, relating to the metaphysical.

From Freud we jump to Bernays and those Adam Curtis documentaries about the powers of persuasion and their importance in manufacturing consent. Now that Natural Language Processing has shown us ways to model word embeddings by means of a vectorized Hilbert Space, we're better able to appreciate "tensegrity" as Fuller meant it.

21st Century Data Science

When I got to Princeton in 1976, graduating 1980, the stats department was already using APL to teach stats. I wasn't taking any stats but was looking over the shoulders of classmates, and for sure APL looked interesting, so I tackled that. APL = A Programming Language, by Kenneth Iverson, then at Harvard.

Nowadays I'm in that same realm, laying foundations in basic Python for ascending the data science mountain, a metaphor I'll use, and reminiscent of the "Calculus Mountain" I'd often decry on Math Forum, ala Andrew Hacker's The Math Myth. Calculus Mountain is abused by admin cullers to separate people from their dreams. 

So couldn't Data Science Mountain be used just as abusively? Surely it could be. Depends on the school, the curriculum. My approach is to encourage many options, many pathways, posed to a consumer willing to self educate (that's idealistic, I realize). 

If a high schooler prefers a discrete math route, such as statistics, abet that with more number and group theory, some programming, and accredit these cohorts as college ready. If their discipline requires calculus, let the discipline teach it the way it needs its students to learn it, as it comes in many flavors.

In retrospect, tackling programming has become closer to taking up an instrument, a more broadly spread skill. In this case you're the music composer, with ways of making the music loop (repeat) or flow conditionally and interactively..

The musician is in the composer role in other words, whereas the instrument plays itself (like a player piano), at superhuman speeds.

And why should only electrical or electronics engineers learn the flute? 

Obviously the question is rhetorical, the point being there's no reason stats can't be an entre into computer programming, and in fact stats have provided such a doorway since mainframes serving universities became available. The big corporations needed to keep churning out future staff. They would make their donations in the form of hardware. The PC revolution followed the same pattern, with many schools receiving tax deductible equipment donations.

Princeton had APL terminals scattered all over, including in my dorm (Princeton Inn) and at the Firestone Library. I taught myself APL, and much later J, also with Dr. Iverson on the team. I was following from Portland, writing web pages on that language, some of which Iverson saw as he helped spot some typos.

APL and J are what we now call "array based languages", such as R and BQN. Operations are performed on n-dimensional arrays, treating the latter as atomic, whereas in conventional computer languages, one has to write busy looping code to hit all the cells in the matrix, one by one. 

The Python community got busy a while back adding array-based packages, such as numpy (Travis Oliphant, 2005) and pandas (Wes McKinney, 2008), which allowed it to stay competitive in the APL-friendly array-based arena. 

Python might seem less pithy than say APL or BQN, as it sticks with the ascii-qwerty keyboard and prefers a more English wordy syntax, even though Guido himself (Python’s inventor) is a Dutchman. 

My students come through Python to the tabular data structure of rows and columns we're so used to from ancient times. Ledgers of rows and columns are in no way a new invention. Computer code becomes a way of automating the job of ledger keepers tasked with keeping those ledgers accurate and up to date, once their composer-designer has orchestrated the perfect system (I’m being idealistic again)..

Equipped with these tools, a data scientists learns to lay pipe (metaphoric pipe) from where the sluices open, allowing raw data to flow in, through successive shaping, cleaning, cutting and patching operations that transform said data into something pristine, polished and suitable for the gods. 

The gods, in this case, are the model makers of Machine Learning, where the models are like golden egg, crystal ball, magic flutes that predict (with some likelihood) the future. Data science is about inferring and predicting, and also about sensing and measuring. How small a data sample might I get away with, and still reliably track the action? That question becomes a topic for deep analysis.

Where data science meets machine learning is where Artificial Intelligence gets much of its nutrition, in terms of achieving practical results, such as when performing text to voice, voice to text, text to graphics, text to video, and extruding synthetic suggestive strands from the LLMs. 

Those famous deep learning neural network algorithms fit in here. Welcome to Hilbert Space.  

Data science is as much about data visualization (showing what’s so)  as about stochastic extrapolation (predicting what’s next). Data science is about providing dashboards, often updated in real time, meaning a set or combination of instruments sufficient to monitor and perhaps influence or control a situation (I’m bundling the car steering wheel and pedals in with the dashboard instruments).

Data science is largely about anticipating the future based on the intelligent leveraging of what's known about the past.

In my Heuristics for Teachers regarding my Silicon Forest Digital Math, the data science stuff mostly fits into my Casino Math, one of four realms. 

Casino Math about risk, taking a gamble, rolling the dice, and developing winning strategies, designing games and simulations, imparting best practices and training chief risk officers. 

The Silicon Forest is in the North American Pacific Northwest where casinos play an important role in the economy. Next to Casino Math we have Supermarket Math, Martian Math and Neolithic Math.

What's true about learning basic programming is one cannot help but butt up against well-worn math topics such as: sets, set operations, number sequences (rule based), random numbers, primes, fibonacci numbers, cryptography, the web, history of the internet, and so on. 

A data scientist is someone becoming fluent with a lot of lore, especially as the discipline becomes increasingly about representing data sets geospatially and considering Planet Earth the relevant display object. 

Landlubber math gets augmented with lat/long and spherical trig. The data scientist is likewise a geographer, taking advantage of what GIS/GPS has to offer.

Dorkbots or Dorks for Short

Isolationism

I hear a lot of talking head pundits expressing their frustration with "isolationist" tendencies within the American electorate, as if blundering on the world stage, pistols drawn, shooting at anything that moves, weren't a perfect recipe for self-isolating. 

I can't think of a more isolationist regime than this outgoing one run by President Blinken (not a typo). Threatening the world with sanctions or worse is no way to make friends. To alienate everyone else is to isolate oneself: these are basic facts of English grammar.

The real issue is the world needs high IQ solutions whereas bombing and rubblizing is low IQ barbaric. We see a lot of throwback Planet of the Apes behavior, as outgoing boomers act out their tired old fantasies, juvenile and retro though they be. No one can stop them apparently. The endless cycle of revenge, punch and counterpunch, keeps the melodrama churning.

Whereas the males of the planet deserve better, the oldsters still see them as cannon fodder, expendable, unto "the last Ukrainian" as they say. The IDF is likewise full of males and females alike who never signed up to become expendable extras in someone else's grand plan. Hearts and minds are still relevant.

As always, we need to draw the line between respect and fear. People may fear being carpet bombed by B52s, but I can't think of anyone I know who thinks carpet bombing is the answer, or has respect for those that do. My inner circle isn't that degenerate. Too bad if yours is. I'm not an isolationist in that way, even if you are.

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