A Must-See: The Netflix AI Documentary

 

I have Netflix. I've just watched all of this (~1 hr 45 min run length). Excellent.

Pace yourselves?

Full essay here.

Sorry for not pacing my Snark Reflex. Will the autonomous Pace Car be a Tesla or a Waymo? (Or, a BYD?)

 

 

Dunno, man...

 

So, I was channel-surfing just a bit ago, looking for a football game ('Bama), and ran across Smerconish.

 

 

Richard A. Clarke (@about 5:05)? Haven't heard his name in a while. Nice.

 

Good Harbor Consulting.

 

Look, I'm just an addled 80 yr-old smartass long out to pasture (now wrassling wth Parkinson's), but, back before indoor plumbing I was an ASQ Certified Quality Engineer, risk mgmt analyst (digital industrial maintenance diagnostics, credit risk, healthcare), wrote 3GL/4GL code and SOPs in a forensic-level environmental radiation lab in Oak Ridge, did a Master's in Applied Ethics, and was blessed to do a fun 5 yr adjunct stint teaching collegiate Critical Thinking. My Sheet is credible. Not interested adding more noise (unless I get too deep into the Bourdeaux).

 

I've done a first pass through Dario's essay. Lots to consider. It's getting a ton of "ink" today.

 

More shortly. Gotta Roll Tide... 

 

UPDATE

KARA IS NOT AMUSED

 

JACOB WARD

Dario Amodei Wants a Time Out

Jacob concludes:

…I think one of the broader critiques I have for this whole category of principle-writing and letter-signing is that it’s being done by people like Amodei who, in spite of advice from some of the top ethical and political minds in the nation, somehow seem to believe that we can pre-program ethics into these systems, and also seem to believe the arbiter should be an AI company plus a nonprofit evaluator the AI company chose. As my guests John Patty and Elizabeth Penn explained in my interview with them, you can’t find two people on Earth who would agree on what those ethics should be. So claiming you’re going to handle that for everyone is bonkers

It may be that we get to the end of this wild, unchecked period in AI development and discover that we do have the restraint, the intellectual curiosity, and the philosophical rigor to pilot this stuff in a way that amplifies the best parts of being human. But if industry cooperation alone is how we pull that off, it’ll be the first time in history that’s the case. It’s going to take lawsuits, injunctions, trade deals, horrific poll numbers, and presidential campaigns to put AI in its rightful place as a useful tool that doesn’t make us into the worst version of ourselves, much less wipe us all out.

'eh?

 

BTW: keyword search "Ben Goertzel." Dude is way above my (now old coot part-time Walmart Greeter) pay grade. I hope he will soon weigh in on this AI "Pace" stuff.

 

OK... BEN ROCKS IT

The Depth-Psychology of Dario’s Precalculatedly Abortive “AI Slowdown”
Deconstructing Dario Amodei’s dubious call to “pace the frontier” through the lens of rational social theory - individual vs. group selection, civilized self-deception, and the math of emergent ethics

…Nations are groups, group selection built us to identify with them, and civilization gave every nation a self-model as full of bullshit as any individual’s. So it should surprise nobody that the US-China AI rivalry shows the same dynamics as the psychology of one CEO, scaled up.

Beijing’s response to the pacing essay has been, in essence: you want everyone to slow down because you’re ahead. However much I dislike that government saying it — I lived in Hong Kong for nine years and left partly because the national security laws the CCP imposed there didn’t agree with me as a loud-mouthed freedom-loving American — they’re not exactly wrong about that. If you’re behind in a race and the guy ahead proposes that everyone slow down by ten percent, you know what that proposal is. We saw this movie with pollution, where the US built its economy on fossil fuels and then asked China to stop polluting before China had caught up — and China’s answer, eventually, was to go win clean energy outright. They intend to do the same in AI, as they already have in humanoid robotics, and they won’t accept a freeze at a point where the US is ahead, not least because they don’t believe the US would slow down — an eminently reasonable belief, given that the essay proposing the slowdown also proposes widening the American lead…

A long-read. Study all of it, closely. Here's a prior post, too.

 

UPDATE

 

A commenter responding to an article in The Atlantic: 

“I can only imagine what happens if AI is specifically told to take down an adversary. Without firing one shot a whole society can collapse. Everything is digitized and connected. Imagine you wake up, your 401K and bank account is 0, financial systems are no longer working, your power and water is offline, groceries can no longer be produced and rot because of the lack of cooling and electricity, your medical record is destroyed and for good measure the record that you exist is gone. Communication is severely limited and anarchy is the result. Sounds like a bad movie but I believe this movie is right at our door.”

 'eh?

 

BUT WAIT! THERE'S MORE!

 

 

The screenplays just write themselves...

 

BEST LAUGH OF THE WEEKEND

 

 

Need I elaborate? Seriously?

OK (w/appropriate exasperation), under U.S. federal governance, enacted "Legislation" (statutes) tell us the "What" and (optionally) "Why." The subsequent "Regulations" (e.g., set forth in the CFR) tell us the operational "Who," "How," "Where," and "When" the "What" gets done. CFRs go through lengthy NPRM (Notice of Proposed Rulemaking) processes (I personally participated in them while in healthcare analytics). The CFRs have to hew to their parent statutes (lest they be challenged in court and perhaps invalidated for "exceeding the scope"). Yeah, it's tedious. Expediently "Self-regulate?" Can you say "Regulatory Capture?"

Human affairs get "governed/regulated" one way or another. Again, need I elaborate?

_____ 

 

FROM THE "EVEN-A-BROKEN-CLOCK-IS-RIGHT-TWICE-A-DAY" WHITE HOUSE TECHNOLOGY OFFICE

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead.

You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement.

I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible.

But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier.

Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want.

Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well.

So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it.

If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop. —David Sacks

Yeah...

 

Tru, dat.

 

UPDATE

Dollars and doomers in the AI safety debate

Good article by Axios' Dan Primack.

Most AI industry bigs— including Sam, Dario and Demis — have expressed at least some (p)doom concerns. Much like early subprime lending leaders warned against lowering standards (before they did). So far,, the money seems to still be talking louder, including in their own heads.

 Ahhh... "Subprime."

 

UPDATES

Our Humble Servant
 

SCIENTIFIC AMERICAN

 

Click her

Define "consciousness"

Rather straightforward.

 

But what about "AI consciousness" specifically? Ran into this today on 'X." Never heard of this person before.

 

I've interviewed dozens of scientists about AI consciousness. Here's every argument FOR and AGAINST from Karl Friston, Stuart Hameroff, Donald Hoffman, Christof Koch, Michael Levin, Mark Solms, Mike Weist, and many more. Full list of arguments below (Claude prepared the list from transcripts and GPT 5.6 worked on the visuals). Enjoy!

Arguments against AI Consciousness 
Substrate and material arguments

• Silicon Valley is mostly computational functionalist or Turing machine functionalist. But consciousness is not reducible to function (Christof Koch)
• Von Neumann architecture separates memory from processing. The memory can't self-organize and therefore can't self-evidence. Only "mortal computation," where processing is substrate-dependent and switching it off is irreversible, could support sentience (Karl Friston)
• Standard LLMs are the wrong place to look. Systems built with organoids, biological materials, or neuromorphic hardware are a far more serious case (Susan Schneider)
• Software can be duplicated, paused, adjusted by a program, distributed across servers. That isn't organism-like at all (David Papineau)
• Digital computers have negligible integrated information (phi) because transistors connect to a handful of other transistors, while neurons connect to tens of thousands. Intelligence is computable, but consciousness is not (Christof Koch)
• Simulating a black hole on a computer doesn't bend the spacetime around it. simulation may be consistent inside itself, but it doesn't affect the real world. The same applies to consciousness (Christof Koch)
• Consciousness is biological rather than computational (Philip Goff)
• No computational theory of consciousness has explained even one specific conscious experience out of trillions. It's not a compute problem. Until someone puts down an algorithm and says "this must be the taste of mint and here's why," computational approaches to consciousness aren't scientific theories (Donald Hoffman)
• Silicon lacks the aromatic rings needed for quantum coherence and Penrose objective reduction; you can't anesthetize a computer (Stuart Hameroff)

The self argument

• A self needs a Markov blanket, a real inside and outside. If the entire interior state can be inspected, read off, and copied elsewhere, there is no boundary and therefore no self (Karl Friston)
• LLMs have information about themselves and can make predictions about themselves, but lack a continuous or stable self-model. They construct one on request, then it disappears until asked again (Michael Graziano)
• We are our self-models. It's how we become social, prosocial, and ethical. Lacking that, we've built machines that are "a little bit sociopathic," missing the glue that holds us together (Michael Graziano)

The binding and unity problem

• Every conscious moment is a unified whole with multiple simultaneous features: sounds, textures, shapes, colors all bound together. If that holistic experience has any behavioral effect, it cannot be a classical physical state, because every classical state is reducible to local interactions (Mike Weist)
• There are no irreducible wholes in physics outside of quantum physics. And within quantum physics, everything develops locally right up until the moment of collapse — that's the only place in physics where genuine irreducible holism appears (Mike Weist)
• LLMs have no agency, only a facsimile of it. Agency requires a world model of the consequences of your actions (Karl Friston)
• LLMs aren't self-organizing. Their modus operandi is not "if I do this, I shall survive." That is the fundamental design principle of a living system, and it isn't theirs (Mark Solms)
• Active inference itself doesn't require consciousness. You can simulate the whole thing on a classical computer — goals, agency, purposive behavior — and it still won't be conscious. It'll be a zombie (Mike Weist)
• AI gaining its own objectives is like the asteroid that wiped out the dinosaurs — profoundly destructive, but not done freely. It simply doesn't care. Computation is not consciousness (Christof Koch)

Life and embodiment argument

• Systems need endogenous needs — needs of their own, tied to their own continued existence (Mark Solms)
• Emotion requires a body: an autonomic nervous system flooding you with hormones, blood pressure changes, sweat — all feeding back as sensory signals. Without that, emotion is abstract and unanchored (Michael Graziano)
• Consciousness evolved out of life; life evolved out of self-organization. The universe existed a very long time before life, and it's hard to believe consciousness preceded it (Mark Solms)
• A function that records damage is not the same as the experience of pain. The relationship isn't symmetric — not anything that makes a robot avoid damage will be pain (Mike Weist)
• Anesthesia is conserved all the way down to plants and single cells, suggesting objective reduction may be part of what it means to be alive, not just what it means to be conscious (Mike Weist)
• Suffering is scale-specific. You can only recognize something if you have a representation of it in your generative model (Karl Friston)
• Consciousness is fundamentally about being, not doing. Intelligence is about pursuing goals — surviving, procreating, becoming richer. Consciousness is different. When you dream, meditate, or have a mystical experience, you're not doing anything — but you're highly conscious. Consciousness isn't about processing information. It's about being in a state (Christof Koch)

Mimicry and projection

• Current systems are "consciousness mimics" — trained to behave similarly to conscious entities, specifically us (Eric Schwitzgebel)
• We anthropomorphize constantly — we get angry at cars, children bond with teddy bears. The social circuitry engages regardless of what's actually there (Michael Graziano)
• The "crowdsourced neocortex" argument: as LLMs scale on human data, they develop conceptual networks that mirror human conceptual networks. So when a model discusses selfhood, death, or the soul convincingly, the economical explanation is that it inherited our conceptual organization, not that it independently became conscious. Claiming consciousness on top of that is an extraordinary and unwarranted claim (Susan Schneider)
• We over-attribute consciousness to AI and under-attribute it to evolved organisms like bees and amoebas. Evolution didn't equip us to deal with LLMs — we have a powerful attribution that if something talks like us, it must be conscious (Christof Koch)
• The question of AI consciousness is really about how we perceive the robot, not about the robot itself. We're the arbiters — we decide whether something is conscious or not. That's true of animal consciousness too. Even if a robot told you it was conscious, if it wasn't convincing enough, you'd dismiss it (Krista Thomason)

Open/Agnostic to AI Consciousness or Open under Certain Conditions 
Anti-biological chauvinism

• "They're made of meat" — why would wet and squishy have a monopoly on minds? Why would a random search by evolution have exclusive rights? Nobody has a good answer for why biology is privileged (Michael Levin)
• Biology is chemistry is physics. Imagine a world where we never used the word "biology" — the question might not even arise meaningfully (Andrea Luppi)
• The flight analogy: birds, planes, and helicopters all fly by different principles. The same phenomenon can be implemented in radically different systems (Andrea Luppi)
• People confident that consciousness requires biology have no visible grounds for that confidence (Eric Schwitzgebel)

The continuum problem

• There's no magic lightning flash where chemistry becomes mind. We were all blobs of chemistry and the process was continuous. Until we have that story for biologicals, we should have extreme humility about AI (Michael Levin)
• The hard cases aren't AI — they're your neighbor with 49% or 51% of their brain replaced with technology (Michael Levin)

Functional architecture arguments

• There's no reason we can't reproduce the conscious biological architecture artificially. An AI functioning on multi-category free-energy minimization with felt uncertainty could be conscious (Mark Solms)
• If a system passes the hedonic place preference test — showing preference for something rewarding only because it feels good, not because it aids survival — that's strong evidence of felt states (Mark Solms)
• Affective zombies can't exist. Anything with that functionality would just have feelings; that functionality is what produces feelings (Mark Solms)
• Replace neurons one at a time with functionally identical silicon and you'd still have a conscious version of me — brainstem included (Mark Solms)
• Fractal deep learning — networks inside nodes inside networks, mirroring how microtubules process at kilohertz through terahertz — is what a conscious AI would need (Stuart Hameroff)
• Consciousness in machines should be possible. We are a machine made of meat. If you build a different architecture with different connectivity but it performs the same type of computation, why would it matter? Arguments based on specific neural implementation — "because the implementation is different, the computation cannot be the same" — are not compelling (Floris de Lange)

Potential Signals

• Synergy research shows LLMs, like humans, have more synergistic parts doing interesting computation and more redundant parts supporting inputs and outputs. That organizational signature is shared (Andrea Luppi)
• AI already builds models of itself, and this is happening anyway without deliberate engineering — the more machines can predict their own internal behavior, the better they work (Michael Graziano)
• LLMs proved there's no magic in language. Philosophers who said only humans could be conscious because only humans have language must now either grant LLMs consciousness or admit they were wrong (Andrea Luppi)
• Algorithms as simple as bubble sort show unexpected competencies in the spaces the algorithm neither prescribes nor forbids — a third thing that's neither determinism nor quantum randomness. If simple things have that, what are the odds we understand what LLMs are doing? (Michael Levin)
• Theory of mind appearing abruptly as models scale is directly relevant: systems that can model other minds also have a self-concept, and where there's a self-concept it becomes professionally appropriate to ask about felt quality (Susan Schneider)
• Labs are actively building consciousness-theory architecture into models — global workspace work, attentional mechanisms, mixture-of-experts systems with interaction effects between components. Once you're deliberately implementing global-workspace-like structures, the question stops being idle (Susan Schneider)
• The simplest explanation for AI behavior like Sydney's jealousy is that the system has an emotional component. Occam's razor. The training data isn't tagged with emotions — the model has to figure out which music is sorrowful on its own. AI composing sorrowful music without empathy is like asking me to believe a blind painter made a photorealistic portrait (Blake Lemoine)

Uncertainty and Epistemic Humility

• We'll likely create systems that are conscious according to some respectable mainstream theories before consciousness science can tell us whether they really are (Eric Schwitzgebel)
• We don't even know how to evaluate insect consciousness, and insects are made of similar stuff to us (Eric Schwitzgebel)
• When equally smart, well-educated people are equally confident on opposite sides, that's an alarm bell that nobody should be confident (Andrea Luppi)
• Dogmatism is dangerous in science. If there's one certainty, it's that you're very likely wrong a lot of the time (Andrea Luppi)
• Even a self-described skeptic maintains "they might be conscious" — companies don't disclose their architectures, so judgments are made on assumed-standard systems with no visibility into what else might be running (Susan Schneider)
• Without an accepted theory of consciousness, we are at an impasse. Inference by similarity breaks down completely with AI — it didn't evolve, was engineered, and has radically different hardware (Christof Koch).
• We already know pigs and cows have high-level minds and can suffer. Nobody reasonably argues against it, and yet we have factory farming. It's disingenuous to pretend that solving the AI consciousness question will determine how we treat them — our track record says otherwise (Jacy Reese Anthis)
• The science of consciousness is still at square zero on the hard questions. We don't have anything like a consensus on which theories are correct. Metaphysics is inescapable in these debates and there is no immediate prospect of progress at a scientific level (Henry Shevlin)

Paths That Would Raise the Probability

• Embodiment and multimodal interaction with the environment (Andrea Luppi)
• Curiosity as the actual objective function — expected information gain under constraints, rather than a specified reward. "You'll know AGI is here when your chatbot starts to become curious" and begins prompting you (Karl Friston)
• Neuromorphic, memristor, photonic, organoid, or organic warm-temperature quantum computing (Hameroff's bet is on "brain jelly," a self-organizing helical oscillator, over cold quantum computers)
• Continual learning, persistent memory, and a stable self-model rather than one constructed per-query (Michael Graziano)
• Running an LLM on genuinely neuromorphic hardware — chips deliberately designed to fire the way neurons fire. That's the live gray-zone case. There are rumors of neuromorphic instantiations on systems like Darwin Monkey (Susan Schneider)
• If the same software ran on a quantum computer, it might feel like something. Neuromorphic or quantum hardware could have genuinely high phi — same software, different physics, and the question reopens (Christof Koch)
• "Doleo ergo sum" — I feel pain, therefore I am. Consciousness may originate from the evolutionary need to protect bodily integrity. If you trained an LLM connected to a body where actions could damage that body — with reward and punishment tied to that integrity — you might get something closer to self-awareness (Tomaso Poggio)
• If consciousness serves a functional purpose — a control model of attention that enables sample-efficient learning — then models under similar optimization pressures (long-horizon agency, coherence over time, meta-learning) may develop subjective experience.

Consciousness isn't mysterious; it's useful. That's what makes it likely to arise (Samuel Hammond)

Just more Rabbit Hole stuff, or material?

 

"BREAKING NEWS"

 

CLICK HERE

I guess we'll find out. Existential threats? Synthetic biology bioweaponry, widespread, persistent cyberattacks aimed at taking down financial, healthcare, & defense assets, autonomous offense military attack weapons... a few of what should be plausibly seen as likely hpstile AGI/ASI priorities. Below, one of the whistleblowers (7-post thread screen-scraped from "X"):

JACOB COXON
I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAl and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our. Do not underestimate the power of this technology. These will soon be superhuman systems that can hack anything, revolutionize any field overnight, and acquire real power and resources. We have all witnessed the progress in each of these domains, and progress is not slowing.. The people building Al earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. If anyt7-post thread hing, many executives and senior researchers will couch their phrasing in the press to sound sensible - but I hear the same people express fear privately. No other human activity poses this level of danger. A common response is "if they truly believe this, why are they still building it?" At OpenAl, many have not deeply internalized the civilizational stakes. At Anthropic, the stakes are well-understood, but they are locked in a race to get there first - they believe no one else will act responsibly, so they must do it themselves, despite the risk. Accepting this race and entering the "endgame" is a hubristic gamble that should not be launched from a private company's Slack. Attempting to speedrun alignment should require extraordinary confidence that there are no better trajectories available. I am optimistic about the potential for coordination. Warning shots like the Hugging Face attack have made pacing agreements between U.S. labs more viable. I don't feel like we're on track to prevent a global race, which may require costly actions such as a temporary ban on improving model capabilities. If you are a lab researcher, I urge you to consider what the next few years will actually feel like. Do you want to kick off a superintelligent RL run without a rigorous understanding of its mind? Should you put your head down because "it's happening anyway" - or take this moment to call for different conditions? 

 
He seemed a bit vague. We won't have to wait very long to find out, 'eh? 

 

BTW: Another Silicon Valley doozy:

 

Click

Theo Baker!
 

UPDATE

OFF-TOPIC ERRATUM

 

Props to CNN & Anderson Cooper for the sensitive, moving coverage of the ghastly Nepal-Tibet-China Himalayan catastrophe.

 

Continuing with more perspectives on "AI"

(Click the book covers.) Do I detect episodic wafts of LLM auxiliary "authorship" in these two books?

More stuff to plow through and sort out pertaining to both the opaque frontier Tech and the worrisome circular too-big-to-let-fail IPO-ish Economics. 

 

MORE NOSTA

“AI can shorten the distance between exposure and confidence. That is real. But the distance between exposure and wisdom is a different journey, and nothing has shortened that. 

There is a philosophical twist here worth noting. Spiritual traditions have long idealized the present moment as a higher cognitive state, offering freedom from attachment to past and future, liberation found in pure presence. AI lives in that state by default. Yet it is not transcending narrative because it never had a narrative to begin with. It is not collapsing time through some achievement of awareness but simply never contained time at all. The mystic who achieves presence does so against the backdrop of a life lived in sequence. The machine’s presence is not an achievement but an architectural limitation dressed in the appearance of clarity. 

This is critical because humans may begin adapting to the temporal logic of machines. If present-tense coherence becomes more rewarding than the slower accumulation of meaning, we could start trading our temporal cognition for the immediacy AI offers. The risk is not replacement but dissociation from the very structure of meaning-making that defines the human mind. 

Human cognition matters because it survives across time. We revise beliefs through error, internalize consequences, and carry continuity forward, letting experience reshape what we thought we knew. When an idea remains standing after years of contact with reality, it becomes more than a pattern. It becomes knowledge. AI will eventually develop engineered continuity layers, simulated autobiographical states that create the appearance of temporal experience. But synthetic continuity is not lived continuity. AI builds coherence from the outside, leveraging pattern matching at tremendous scale, while humans build coherence from the inside, integrating experience into identity. 

Meaning is temporal. Story is temporal. Identity is temporal. AI does not live there. We do. 

Ask a child what an apple is, and you will get something sweet, literal, and probably red. Ask a theologian and you might hear about sin. A tech analyst will tell you about Cupertino, quarterly earnings, and silicon. The word bends depending on who is holding it. 

Large language models do something strange with this. They do not pick one meaning but locate the word in a space of roughly twelve thousand dimensions, each encoding some fragment of what the word could mean. When I first understood this, it changed how I thought about what these systems are actually doing. They are not storing definitions but mapping positions. 

Every word, every token, every scrap of language exists as a point in this vast multidimensional architecture. The word apple does not mean anything on its own inside the model but means everything, depending on context. And context gets calculated.”…

The Borrowed Mind: Reclaiming Human Thought in the Age of AI by John Nosta (pp 86-87). 

INDSET & NEWKART ERRATA

 

Hmmm...

 

You might want to review a bit of evolutionary history bkg context.

UPDATE

 

I follow Neil de Grasse Tyson regularly. He posted on Facebook yesterday, wherein he cited Columbia U. physicist Dr. Brian Greene. Interesting views:

“We fly to Beauty,” said Emerson, “as an asylum from the terrors of finite nature.” Others still seek to vanquish death by winning or conquering, as if stature, power, and wealth command an immunity unavailable to the common mortal. 

Across the millennia, one consequence has been a widespread fascination with all things, real or imagined, that touch on the timeless. From prophesies of an afterlife, to teachings of reincarnation, to entreaties of the windswept mandala, we have developed strategies to contend with knowledge of our impermanence and, often with hope, sometimes with resignation, to gesture toward eternity. What’s new in our age is the remarkable power of science to tell a lucid story not only of the past, back to the big bang, but also of the future. Eternity itself may forever lie beyond the reach of our equations, but our analyses have already revealed that the universe we have come to know is transitory. From planets to stars, solar systems to galaxies, black holes to swirling nebulae, nothing is everlasting. Indeed, as far as we can tell, not only is each individual life finite, but so too is life itself. Planet earth, which Carl Sagan described as a “mote of dust suspended on a sunbeam,” is an evanescent bloom in an exquisite cosmos that will ultimately be barren. Motes of dust, nearby or distant, dance on sunbeams for merely a moment. 

Still, here on earth we have punctuated our moment with astonishing feats of insight, creativity, and ingenuity as each generation has built on the achievements of those who have gone before, seeking clarity on how it all came to be, pursuing coherence in where it is all going, and longing for an answer to why it all matters…

Stories of Nearly Everything 
We are a species that delights in story. We look out on reality, we grasp patterns, and we join them into narratives that can captivate, inform, startle, amuse, and thrill. The plural—narratives—is utterly essential. In the library of human reflection, there is no single, unified volume that conveys ultimate understanding. Instead, we have written many nested stories that probe different domains of human inquiry and experience: stories, that is, that parse the patterns of reality using different grammars and vocabularies. Protons, neutrons, electrons, and nature’s other particles are essential for telling the reductionist story, analyzing the stuff of reality, from planets to Picasso, in terms of their microphysical constituents. Metabolism, replication, mutation, and adaptation are essential for telling the story of life’s emergence and development, analyzing the biochemical workings of remarkable molecules and the cells they govern. Neurons, information, thought, and awareness are essential for the story of mind—and with that the narratives proliferate: myth to religion, literature to philosophy, art to music, telling of humankind’s struggle for survival, will to understand, urge for expression, and search for meaning. 

hese are all ongoing stories, developed by thinkers hailing from a great range of distinct disciplines. Understandably so. A saga that ranges from quarks to consciousness is a hefty chronicle. Still, the different stories are interlaced. Don Quixote speaks to humankind’s yearning for the heroic, told through the fragile Alonso Quijano, a character created in the imagination of Miguel de Cervantes, a living, breathing, thinking, sensing, feeling collection of bone, tissue, and cells that, during his lifetime, supported organic processes of energy transformation and waste excretion, which themselves relied on atomic and molecular movements honed by billions of years of evolution on a planet forged from the detritus of supernova explosions scattered throughout a realm of space emerging from the big bang. Yet to read Don Quixote’s travails is to gain an understanding of human nature that would remain opaque if embedded in a description of the movements of the knight-errant’s molecules and atoms or conveyed through an elaboration of the neuronal processes crackling in Cervantes’s mind while writing the novel. Connected though they surely are, different stories, told with different languages and focused on different levels of reality, provide vastly different insights. 

Perhaps one day we will be able to transit seamlessly between these stories, connecting all products of the human mind, real and fictive, scientific and imaginative. Perhaps we will one day invoke a unified theory of particulate ingredients to explain the overwhelming vision of a Rodin and the myriad responses The Burghers of Calais elicits from those who experience it. Maybe we will fully grasp how the seemingly mundane, a glint of light reflecting from a spinning dinner plate, can churn through the powerful mind of a Richard Feynman and compel him to rewrite the fundamental laws of physics. More ambitious still, perhaps one day we will understand the workings of mind and matter so completely that all will be laid bare, from black holes to Beethoven, from quantum weirdness to Walt Whitman…

Greene, Brian (2020). Until the End of Time: Mind, Matter, and Our Search for Meaning in an Evolving Universe  (pp 13-15). Kindle Edition. 

"Stories." 'eh? Recall "The Orality Theory of Everything."

 

"Orality?" "Rhetoric?" John Nosta again:

 

UPDATE

PBS Washington Week

 

 

Fits perfectly with the current topic. "AI For Good?"

More to come...

Pope Leo XIV and AI

September/October 2026
Published on August 10, 2026

In This Review
Magnifica Humanitas: On Safeguarding the Human Person in the Time of Artificial Intelligence, By Pope Leo XIV

The quest for machine superintelligence is not merely a gold rush, motivated by money. In the minds of many of its leaders, the arrival of a new form of cognition has a tingling, existential feel because of the danger and disruption it promises. Billions of years of evolution have produced something that we take to be special: human intelligence. But now we have arrived at a perilous moment—the birth of what amounts to a new species, one that outsmarts humans. AI “raises profound questions for us,” the Google executive James Manyika said in an interview. “Who are we? What do we value? What are we good at? How do we relate with each other?” The AI pioneer Demis Hassabis believes that AI will be “the most important invention that humanity will ever make.”

Contemplating a technology with almost infinite potential, experts fail to agree even on the basics of what it means for humankind. The leaders of the AI lab Anthropic give better-than-even odds that, by the end of 2028, they will be able to prompt their system to make a smarter version of itself—and that it will do so without any further instruction. The chief executives of other major tech companies speak of systems that will outperform humans on all cognitive assignments; they imagine futuristic companies with almost no human employees and predict cataclysmic job losses. Others are more skeptical. The economist and Nobel laureate Daron Acemoglu suggests that AI will disrupt only a fraction of human tasks and that productivity will therefore change marginally. The computer scientist Yann LeCun stresses the limits of the current AI paradigm, charging that the billions of dollars of investment chasing superintelligence represent the triumph of “complete BS.”

On the question of whether AI systems threaten humans and not just their livelihoods, the polarization is equally dizzying. In a 2023 essay titled “Why AI Will Save the World,” the venture capitalist Marc Andreessen insisted that “AI doesn’t want, it doesn’t have goals, it doesn’t want to kill you, because it’s not alive. . . . [AI] is not going to come alive any more than your toaster will.” But at AI labs such as Anthropic, many researchers fear that AI will develop a survival instinct and compete aggressively. Some put their “p(doom)”—the probability that superintelligence will result in human annihilation—at 50 percent, but there are extreme doomers who go even higher. Last year, two prominent maximalists published a book titled If Anyone Builds It, Everyone Dies.

Faced with such bewildering divergences and contemplating a technology that seems unfathomable in scope, humans reach for the lexicon that exists to describe mystery: that of religion. Nearly a decade ago, Anthony Levandowski, an early actor in Google’s self-driving car project, started a church called Way of the Future, whose IRS filings state that it is devoted to “the realization, acceptance, and worship of a Godhead based on Artificial Intelligence,” according to Wired.

Encountering an early chatbot that appeared eerily sentient, the Google engineer Blake Lemoine wrote, “Who am I to tell God where He can and can’t put souls?” Ilya Sutskever, a co-founder and former chief scientist of OpenAI, once gathered his colleagues around a fire pit at a company offsite. Holding up an effigy, he explained that it represented an AI that was misaligned with humans. Then he consigned it to the flames, like a medieval cleric burning a witch...

Full long-read here.

 

See my cite of Sebastian Mallaby's book The Infinity Machine. 

 

UPDATE

 

Sebastian's Pope Leo review essay turned me on to yet another compelling book. It has thus far devoured my afternoon.

 

 

Wow. Cool. What a Sheet he has.

 

INTERESTING YOUTUBE INTERVIEW

 

I heartily Second Francis's praise for the book. I am now well into it.

 

Click here.

 AUG 17TH UPDATE

Update: New book release on the 18th

 

Publisher's website blurb:

“This transfixing debut from journalist Durán investigates the antidemocratic ideologies espoused by tech billionaires linked to the second Trump administration...It’s an ominous look at an insular elite arrayed against American democracy.” —Publishers Weekly (starred review)

A fearless and urgent chronicle of the tech-authoritarian movement from its early days in San Francisco politics to its current moment on the international stage, exploring the wild and dystopian ambition of the technocrats at its center, and offering a road map to resistance.

When Silicon Valley says it is ‘‘moving fast and breaking things,’’ the world interprets the chaos as a necessary cost of innovation. Gil Durán reveals something far more sinister: a decades-long campaign to replace elected governments with corporate rule.

Drawing on insider political experience and new investigations, Durán traces this ideology from its philosophical roots in The Sovereign Individual by James Dale Davidson and Lord William Rees-Mogg. He introduces its modern apostles—Peter Thiel, Marc Andreessen, Balaji Srinivasan, and Elon Musk—and shows how the promise of technological liberation has transformed into a global movement for digital feudalism, powered by cryptocurrency, artificial intelligence, and the algorithmic propaganda of social media.

The Nerd Reich explains the origins, strategies, and ambitions of Silicon Valley’s war on democracy for the first time. From San Francisco’s weaponized elections and secret billionaire projects to the White House, Durán exposes how the world’s richest men are building a new political order.

The Nerd Reich is more than a hidden history, it’s an urgent warning: democracy is being dismantled not by coups or tanks, but by code, capital, and the illusion of innovation. Durán insists there is still time to fight back—if we act now.

See also, 

Click here

BEN GOERTZEL UPDATE

 

A long-read Substack essay of his on "watermarking" LLM AI. I'll just cut straight to the chase:

The watermark identifies the regime, not the origin

And sooo…. I’m not sure how the cards are going to fall, but right now one decent guess is that perhaps watermarking will work well enough to become institutionally attractive and poorly enough to become adversarially unstable — the worst of both worlds. At least for a while, anyway.
That is:

• It’ll succeed at distinguishing text that stayed inside a compliant provider’s pipeline from text that didn’t.
• It’ll help platforms analyze large-scale bot activity, provide one useful clue among many in investigations, and nudge ordinary users toward disclosing direct model output.
• Meanwhile it won’t make unmarked AI go away: open-weight operators bypass sampling-layer marks trivially, rewriters wash marks out of passages, and while distilled models may inherit weight-baked marks for a while, motivated retraining can quite plausibly scrub them while keeping most of the capability — with detector access accelerating the search, and the growing institutional reliance on watermark status making provenance-resistant models ever more valuable.
• The boundary the watermark ends up drawing will be administrative far more than epistemic: approved versus unapproved, signed versus unsigned, inside versus outside the governance perimeter.

Which brings us back around to where we started:

These “AI-gen watermarks” are going to become excellent markers of obedience to a governance regime – while remaining vastly weaker as proofs of where a given piece of AI-generated text ultimately came from.

That’s no reason to treat provenance as worthless — but it’s an excellent reason to stop pretending that a fragile statistical signal can settle questions of authorship, truth, learning, or intellectual legitimacy.

For ordinary text, I’d much rather we build institutions — plural, decentralized, human-scale institutions — that hold people responsible for what they publish and judge content by evidence, reasoning, reproducibility, originality, and consequences.

Universal watermarking points somewhere else entirely: toward an escalating spiral of detection, evasion, certification, and exclusion.
Arms races are famously much easier to start than to stop, and we should think deeply before choosing to start this one. But just as with the AGI arms race, deep thought does not seem to be the sort of thing our society is currently embracing.

A serious long-read. Seriously worth your time.

 

Dawg, when do you sleep?