A Must-See: The Netflix AI Documentary

 

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

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?

"The Singularity?"

Lots to catch up on. Cheryl and I have quietly been out of town for a week (SF Bay Area, and Las Vegas). I'll be following up topically ASAP on material relevant to my prior David Eagleman "Inner Cosmos" post. Got a good bit of reading down while gone.

 

New book coming shortly, reviewed in Science Magazine.

     

 

apropos, see "AI Slop and Scientific Publishing."

 

"Uncertainty?" "Two Cheers for Uncertainty." 

 

SUBSTACK UPDATE: THE LATEST FROM BEN GOERTZEL

Proposing an experimental OmegaHive loop for turning agentic coding into cumulative, testable progress toward human-level AGI and maybe beyond — we are actually building this now, and playing with preliminary versions!

Among the many interesting things that popped up at the AGI-26 conference last week in San Francisco, one of them stuck out for me as being of particular “meta-level” importance.

What I’m talking about is how many conference attendees I talked to who were trying to have their agent hives code AGI for them, by taking a whole bunch of papers off the internet (including my own papers, and others from the Hyperon team) and asking their agents to bash them all together into an AGI codebase and make it tick.

One form this takes uses our own OmegaClaw system. OmegaClaws are agentic loops that wrap up LLMs together with knowledge graphs built on the Hyperon AtomSpace infrastructure, with fairly sophisticated reasoning and pattern matching running over them. The symbolic component supplies the agents with more episodic memory, more long-term memory, more of a sense of self than a vanilla coding agent has. So you take a system like that — not yet an AGI, but possessing a powerful agentic loop, some memory, some reasoning, some notion of who its mother is — and you tell it: download these 25 of Ben’s papers, turn them into code, integrate them into your memory, reason with them, extend yourself.

I think this sort of process has in it the seeds of a workable approach to building AGI. 

The main problematic issue here, as anyone who has done a lot of AI research will tell you, is the gap between having a software component that sort of works in some small test — and/or, say, whose workings you can even prove correct with some nice math — and having something that really works at scale and in real life…

Okeee Dokeee, then. I'm a reasonably intelligent guy with a fairly lengthy and varied digitech Sheet, but this cat is well above my pay grade. 

 

Ben is involved with this AGI academic offering:

 

Tuition for the M.S. will set you back about $32k. Worth it? Were I not 80+ and increasingly physically ailing, I'd consider ponying up.

 

Another Ben Goertzel thingy:

 

Click

ON DECK: THE INFINITY MACHINE

 

This is yet another riveting book. Read a ton of it while returning home to BWI from LAS on Southwest. Lotta dots starting to connect. All of the current Usual Suspects and then some. Musk, Thiel, Zuckerberg, Altman, Page, Brin, Karp, Amodei...

QUICK SAMPLE

...I was shown into Hassabis’s office. Almost immediately, the enormity of AGI bubbled up again in conversation. 

“So it will be bigger than the Industrial Revolution?” I asked, curious to hear more about the post-scarcity future. 

“Yeah, I think so,” Hassabis reiterated. “Maybe AI is more like fire and language. Or maybe it’s as big as the emergence of the prefrontal cortex in humans. I mean, it’s on a level with those caves where tens of thousands of years ago some brilliant person had the idea of making handprints on the wall. 

That’s the dawn of consciousness, isn’t it? “Look, the Industrial Revolution, let’s not minimize that. Power and energy and steam engines. That’s the first information age, by the way—Maxwell’s equations.” 

Hassabis was referring to the four equations published in 1865, describing the relationship between electricity and magnetism and paving the way for everything from telescopes to electrical engineering to Einstein’s general theory. 

“Now we’re in the second information age: We’ve gone from physical information to pure information, thanks to computers. 

“And then maybe now we’re about to enter the third age, which is the AI age, where the information comes alive. It starts to process itself, to generate itself. It becomes autonomous.” 

I wondered what it was like to live in the familiar, pre-AGI world, the world of chessboards and seared bream, but also to imagine a future with AGI so vividly. 

“For me, science is a spiritual endeavor,” Hassabis answered, circling back to our discussions of religion. 

“Maybe ‘spiritual’ is too mystical a word. But I feel I’m communing with the universe whenever I am trying to understand it. 

“It’s very deep for me, building AI. Because it will help me to understand the universe and realize my purpose. 

“I mean, this is what Spinoza said,” Hassabis went on, referring to the seventeenth-century Dutch philosopher. “That God is present in nature, so understanding nature is a spiritual endeavor. And Einstein, although he was not conventionally religious, agreed. He said he believed in the God of Spinoza, and I think he meant what I mean. 

“People assume, oh, religion’s over here, science is over there, it’s weird to put them together. But in my world, humanism and spiritualism and science all go together.

“It’s like with Leonardo da Vinci. His anatomical drawings are beautiful art as well as unbelievable biology. Da Vinci is my favorite because everything’s just flowing into one river. And that’s how I try to live. Everything’s fluid.” 

I read out a line from a biography of Spinoza, which Hassabis had recommended in one of our earlier conversations. The line reminded me of the intensity with which Hassabis pursued his scientific mission. 

“Philosophy was for Spinoza, not a weapon, but a way of life, a sacred order whose servants were transported to a supreme and certain blessedness.”[7] 

“I agree with that 100 percent,” Hassabis interjected. 

“If you ask what life is really for, it’s to do with knowledge or self-knowledge. And I think that is our purpose because why otherwise would the world be constructed like this? Why would science be possible? Why should computers be possible? What about semiconductors? Why should sand, with a bit of copper, do anything?

“These things are, strangely, set up for scientific endeavor. So whether you want to call that God’s design, or whether it’s just the universe, or a simulation, I’m open-minded about all of that. I think that’s part of what we’ll find out, when we’re on this journey. 

“But in the meantime, it feels like the flow of the universe is going in this direction, towards discovering the answers. And I’m part of that flow, I’m going with that flow, and it’s exhilarating.”

Mallaby, Sebastian. The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence (pp. 113-115). (Function). Kindle Edition.  

  
This is one helluva book. About a 15 hour read (I'm not finished yet).

 

RETURN TO SOME EVOLUTIONARY GROUNDING

 

Click

What is "life?" What is "the purpose of life?" (Assumes there is one.)

 

WHAT IS "INTELLIGENCE," FOR THAT MATTER?

 

Doris & David Jonas:

   

UPDATE: BREAKING NEWS

 

Kai-Fu Lee, the C.E.O. of the artificial-intelligence company 01.AI, lives in a mirrored high-rise in Beijing, near a procession of landmarks that emperors considered the center of the cosmos. Lee takes early meetings at a nearby hotel that could be in any country, except that the room service is delivered by robots painted in the livery of butlers and maids. State propaganda hails these robots as emblems of China’s ascent; in the hallway, most people sidestep them with the kind of indifference usually reserved for a Roomba.

Over breakfast one recent morning, Lee, wearing a white polo shirt and rimless glasses, spoke about the future with an air of sanguine curiosity. He was born in Taiwan in 1961 and built his career by following the moving frontier of opportunity. He got a degree in computer science from Columbia in the eighties and went on to Carnegie Mellon to study the fledgling field of A.I.—which he described back then as a “most promising science” that would be “men’s final step to understand themselves.” He ran speech recognition at Apple, and in 1992 appeared on “Good Morning America” to show off a prototype computer that used voice commands to record the news on a VCR. (The host, Joan Lunden, marvelled, “It’s almost going to be like a friend.”) During a stint at Microsoft, he recalls, he urged Bill Gates to buy an ambitious startup called Google, but Gates declined. Lee later became the head of Google in China…

A 64-minute excellent New Yorker lomg-read that could not be more timely. Yeah, likely paywalled. Totally worth it.
 

More ASAP...  

ASI, "Artificial Superintelligence?" Update post.

What is artificial general intelligence (AGI) and how close are we to getting there? What defines the next step, called artificial superintelligence (ASI), and why might the gap between those two be so dangerous? When machines become smarter than us, what roles are left for humanity? Should we think of AI as software, or as something we’re raising like a child? Will tomorrow’s AI destroy us, ignore us, or protect us? This week Eagleman talks with computer scientist & AI researcher Ben Goertzel.

A totally fascinating discussion. Savor every minute. Notwithstanding my long-standing interest in a breadth of AI topics, I was not aware of Ben Goertzel. My Bad.

 

Total Badass.

 

Wonder what he'd have to say about this: "AI slop and scientific publishing?" 

 

Ben lives in the Seattle area. Makes me like him all the more. I have serious PacNW history. See here and here. Still have many dear friends there.

 

OFF-TOPIC ERRATUM

 

Is Ben the Allan Stone (another PacNW cat) of ASI?

Just a thought. LOL. He describes himself as "a weekend musician."

_____

Back on topic... 

 

Check out Ben's Substack. Bracing stuff.

 

apropos, some closing observations from this 1976 book.

 

Other Senses, Other Worlds, Ch. 11, Beyond Human Intelligence

…Is this as far as we can extrapolate from what we know of Laboratory Earth in our attempts to see into our own future or into other worlds?

Actually, it is not. It is within the realm of our reason and imagination to catch glimpses of still more distant possible descendants. We see that in nature successful solutions often arise by what is called convergence—that is, they arise independently in different lines that are often separated in time and place and are in no way related to each other, because these lines have encountered similar environmental problems and have coped with them in a similar way precisely because that solution is an efficient one.

Prehensile tails, for example, have developed in many kinds of monkey (although not in all), in the common opposum, and in several related
species, in the true chameleon and a few lesser genera, and in a fish, the sea horse. Similar needs in these disparate creatures have evoked a similar response in the structure and function of the tail.

In earlier pages we have from time to time described what amounts to a group brain as it exists among earth's social insects, which produces intelligent solutions, although the individuals comprising the groups are separately only capable of comparatively stereotyped actions. What if a group brain were to evolve where all the individuals were possessed of the kind of superbrain and superintelligence we are attributing to Homo neocorticus?

Utilizing the concept of convergence, we see that the social insects, by the use of chemical substances—the pheromones—that give off distinctive odors, have achieved almost instant communication, an important element in their cooperative actions. In a mass brain of cooperative superbrains that might evolve from Homo neocorticus, we could imagine an absolutely new type of communication emerging, no longer either verbal or even more refinedly symbolical. It could be a direct brain-to-brain awareness promoted by an individual brain's electric charges that might be intensified or modified so as to constitute an instant transmission without any kind of language, receptor mechanisms being evolved within the brain itself.

In order to conceptualize this thought, we paid a visit to a modern laboratory where electroencephalograms of patients being tested for brain disturbances are being recorded and processed all day long. We saw there a technician in her middle years who had spent all her working life recording and interpreting the "squiggles" registered by inked points onto long rolls of papers as they responded finely to the electric emanations of the patients' brains. The lengths of paper were subsequently folded into bound volumes.

This technician could open any of those records and read them, understanding all they implied, as easily as we read any page printed in our own language, and she was teaching her young assistants to do the same. In other words, the direct electric emanations from half a dozen different areas of the patient's brain simultaneously, with their respective periods of excitement and calm, had clear meaning for her, and she could read like a book any of the volumes in the large library of records of brain activity that were assembled on the shelves of her office. If we can imagine these inked lines of the EEC squiggles as an extremely primitive and crude form of what might ultimately evolve as a form of direct brain-to-brain communication, we believe we have a plausible model on which to base our speculations about our descendant species-after-next. Such instantaneous communication could easily suffuse an entire group and make possible intelligent mass action of an order that we can no longer imagine, or even speculate about.

The question that remains is: Why such a brain? What possible environmental circumstance could ever evoke it? And the answer is that once a higher intelligence appears on the natural scene, it makes its own environment. It is a matter of common observation among ourselves that every human being leaves a mark of his or her own personality upon surroundings. A housewife's individuality can almost be read by the condition in which we find her house—the order or disorder in which it is kept, the way it is furnished and decorated, the implements and equipment she uses. A man's fields or garden, office or workshop or den, also reveal much about him. It would seem that something of the brain and perhaps of the whole nervous system of each of us is displayed in the environments we make for ourselves. Even the little bowerbird reveals his individuality in the small objects he uses to decorate his bower and in his arrangement of them. And so we feel we are justified in assuming that as a brain evolves in complexity, it will surely be to the accompaniment of an increasingly complex ambience.

Human beings originally lived in the same "nature" as all other animals, and many still live very closely with it. If we camp in a forest, we do not actually need our superior mental equipment—that other creatures live out their lives in that forest is evidence of this. But most of us no longer live in natural settings, and even those who do, modify them with such artifacts as fire, weapons, and tools.

Today, all of mankind, some to a smaller but most to a larger extent, make our own habitats, and our man-made environment becomes more and more complex. Moreover, in the process of adjusting to our increasingly artificial surroundings, we become less and less fitted to live in natural ones, and so the course upon which we are embarked is far more likely to continue than to be reversed. For Homo neocorticus we can project a habitat of, to us, incredible complexity, and we can imagine that this will provide the spur that could eventually produce the Group-brained neocorticus, whom we could no longer designate as Homo.

At this point we pass our project over to our reader to use his or her imagination to visualize a meeting between Homo sapiens and Group-brained neocorticus, or its prototype as it may exist somewhere in the vastness of the universe.

'eh?

 

 UPDATE

 

 A Link to more AGI stuff I posted last year.

 

Stay tuned... 

The "Accelerationists" vs the "Doomers."

AI For Good?

 

Pending book release. Pre-pub excerpt from The Atlantic.

The Secret to Understanding AI
“Imagine the tech without the tech companies.”
By Josh Tyrangiel

In the before times—before machines could hallucinate, before compute was a noun—it was not uncommon to go several weeks without someone telling me the world was about to end. Similarly, a whole season might pass without anyone assuring me that it was also, simultaneously, about to become perfect.

That particular luxury died on November 30, 2022, when OpenAI released ChatGPT to the public. What followed was less a news cycle than a weather event—a tropical depression that would not budge. Within weeks, millions of people had their first experience with generative AI. Within months, every major technology company had announced its own version of a large language model, or a partnership, or a pivot. Venture capital arrived drooling. Most people in tech think about money, but AI-profit projections are different—like CFO fan fiction, written in Excel. In 2023, the McKinsey Global Institute estimated that $4.4 trillion in annual corporate profits could be up for grabs from generative AI alone. Morgan Stanley estimated $40 trillion more in operational efficiencies. The words artificial intelligence went from obscurity to a constant hum, present in every earnings call, every school-board meeting, and far too many arguments at dinner tables.

Yet for all of the noise, a simple question stayed unanswered: What exactly was this new technology going to do for people? Not for corporations or the billionaires who aspired to become trillionaires, but for people with mortgages and sick parents and children struggling to learn things…

May 12th release date.

AMAZON BLURB
In contrast to the wave of noisy polemics around AI, AI For Good explores how, in practice, it can actually improve our lives and tells the stories of everyday citizens at the forefront of this new “AI entrepreneurship.”

AI is often framed as a force of radical transformation, either catapulting us into a utopian future or dragging us toward existential ruin. But this book tells a different story. It’s not about high-profile tech CEOs who want to use AI to “break shit,” but about a bunch of smart pragmatists using AI to make the world better.

Josh Tyrangiel’s journey into AI began with a late-night YouTube video featuring General Gustave Perna, the retired four-star general who orchestrated the distribution of Covid vaccines during Operation Warp Speed. Perna’s success—and the end of the pandemic—depended on AI’s practical ability to synthesize and standardize vast amounts of logistical data. AI wasn’t the hero of the story—it was the tool that helped real people get things done.

This book follows those people, who make up a kind of AI counterculture. It explores AI’s quiet revolution in government services, medicine, education, and human connection—places where it’s being used to amplify human judgment rather than replace it. It tells the stories of teachers, doctors, and bureaucrats who often stumbled into AI as a means to solve specific, tangible problems, often with no prior software expertise.

While the loudest voices in AI debate doomsday scenarios and trillion-dollar market opportunities, this book focuses on those working in the messy, incremental, but deeply impactful space of AI practice. However, there is one big caveat—success is not guaranteed. Change is hard. Institutions move slowly. But even in failure there are lessons for everyone who’s interested in using AI—carefully, thoughtfully—to build a better world today.

I have too many books in play at the moment (about 8), but I'll be adding this to the list when it's released.

 

SOME OTHER READS JUST ADDED TO THE STASH

  

 

Dispatches from Grief is intensely personal for this "Girl Dad."

ERRATUM: SCIENTIFIC AMERICAN

 

The greatest pitfall in the search for extraterrestrial life—according to science fiction, anyway—is foolhardy researchers somehow bringing aliens to Earth to wreak havoc.

But after decades of exploring our seemingly sterile solar system, real-world scientists today are much more concerned with the opposite problem: The possibility that Earth’s life will escape our planet to contaminate other worlds, sabotaging the quest to find any genuine “second genesis” of biology around the sun. Imagine that a multibillion-dollar robotic mission found wriggling microbes on Mars and that follow-up studies then revealing those “aliens” had DNA and other biomolecular machinery that showed they were emigrants from Earth.

Astrobiologically speaking, we would have met the enemy—and it would be us. Taking a cue from sci-fi, you might call such life-forms “Klingons,” for their presumptive hitchhike to the Red Planet as stowaways in spacecraft sent from Earth.

“Planetary protection” is the term scientists use for efforts to prevent otherworldly invasions of all sorts; to date, most of it has focused on Mars, but the practice applies to all potentially habitable environments within reach of our spacecraft. In the 1970s, for example, NASA did its best to keep its twin Viking landers Klingon-free before launching them to Mars. And if the NASA-led international Mars Sample Return effort ever manages to bring its precious payload back to Earth, the agency will be tasked with quarantining those specimens as if they contain extreme biohazards rather than lifeless bits of rock and soil…

Imagine my surprise. apropos of some prior riffs on astrophysics and exobiology.

 

OFF-TOPIC, CHEERS... 

More shortly... 

The AI freakout. Are concerns overblown?

  

Charlie Warzel of The Atlantic converses with Anil Dash.

44 minutes very well spent.

Wikipedia cite

Cool guy. Quite personable. 

Would have liked a good bit more on the power dynamics thing, though.

AI: the Possible vs the Probable

Tristan Harris cuts to The Chase

 

"Wisdom Traditions?" "Philosophy?" Define "philosophy.'"

 

So, I punted to Google's new native "AI" jus' fer grins. BTW, some prior riffs on AI.

 

 

I was pleased by that. "Knowledge" and "Wisdom" differ. The former is necessary but insufficient for the latter. Given that my 1998 grad degree is in "Ethics & Policy Studies," I know just a thing or two about the core elements of "applied philosopy."

 

Another material facet of all of this.

 

Click here.

When Jensen Huang, the chief executive of the chipmaker Nvidia, met with Donald Trump in the White House last week, he had reason to be cheerful. Most of Nvidia’s chips, which are widely used to train generative artificial-intelligence models, are manufactured in Asia. Earlier this year, it pledged to increase production in the United States, and on Wednesday Trump announced that chip companies that promise to build products in the United States would be exempt from some hefty new tariffs on semiconductors that his Administration is preparing to impose. The next day, Nvidia’s stock hit a new all-time high, and its market capitalization reached $4.4 trillion, making it the world’s most valuable company, ahead of Microsoft, which is also heavily involved in A.I.

Welcome to the A.I. boom, or should I say the A.I. bubble? It has been more than a quarter of a century since the bursting of the great dot-com bubble, during which hundreds of unprofitable internet startups issued stock on the Nasdaq, and the share prices of many tech companies rose into the stratosphere. In March and April of 2000, tech stocks plummeted; subsequently many, but by no means all, of the internet startups went out of business. There has been some discussion on Wall Street in the past few months about whether the current surge in tech is following a similar trajectory. In a research paper entitled “25 Years On; Lessons from the Bursting of the Technology Bubble,” which was published in March, a team of investment analysts from Goldman Sachs argued that it wasn’t: “While enthusiasm for technology stocks has risen sharply in recent years, this has not represented a bubble because the price appreciation has been justified by strong profit fundamentals.” The analysts pointed to the earnings power of the so-called Magnificent Seven companies: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla. Between the first quarter of 2022 and the first quarter of this year, Nvidia’s revenues quintupled, and its after-tax profits rose more than tenfold.

The Goldman paper also provided a salutary history lesson...

MORE ON AGI CONCERNS

 

There sre now dozens of these critical AGI videos on YouTube alone. 

 

Briefly back to Econ stuff (pertaining to just OpenAI):

 

OpenAI astounded the tech industry for the second time this week by launching its newest flagship model, GPT-5, just days after releasing two new freely available models under an open source license.

OpenAI CEO Sam Altman went so far as to call GPT-5 “the best model in the world.” That may be pride or hyperbole, as TechCrunch’s Maxwell Zeff reports that GPT-5 only slightly outperforms other leading AI models from Anthropic, Google DeepMind, and xAI on some key benchmarks, and slightly lags on others.

Still, it’s a model that performs well for a wide variety of uses, particularly coding. And, as Altman pointed out, one area where it is undoubtedly competing well is price. “Very happy with the pricing we are able to deliver!” he tweeted.

The top-level GPT-5 API costs $1.25 per 1 million tokens of input, and $10 per 1 million tokens for output (plus $0.125 per 1 million tokens for cached input). This pricing mirrors Google’s Gemini 2.5 Pro basic subscription, which is also popular for coding-related tasks. Google, however, charges more if inputs/outputs cross a heavy threshold of 200,000 prompts, meaning its most consumption-heavy customers end up paying more…

"Tokens?"

 

 Lordy. Wafts of the Crypto bamboozlement ensue.

 

UPDATE

Much of the euphoria and dread swirling around today’s artificial-intelligence technologies can be traced back to January, 2020, when a team of researchers at OpenAI published a thirty-page report titled “Scaling Laws for Neural Language Models.” The team was led by the A.I. researcher Jared Kaplan, and included Dario Amodei, who is now the C.E.O. of Anthropic. They investigated a fairly nerdy question: What happens to the performance of language models when you increase their size and the intensity of their training? ...

From The New Yorker by Cal Newport. Interesting piece. GPT 5 is getting a lot of pushback. 

 

MORE CONSIDERATIONS

 

Chapter 1 
The Artificial Intelligence of the Ethics of Artificial Intelligence  
An Introductory Overview for Law and Regulation  
Joanna J. Bryson 

For many decades, artificial intelligence (AI) has been a schizophrenic field pursuing two different goals: an improved understanding of computer science through the use of the psychological sciences; and an improved understanding of the psychological sciences through the use of computer science. Although apparently orthogonal, these goals have been seen as complementary since progress on one often informs or even advances the other. Indeed, we have found two factors that have proven to unify the two pursuits. First, the costs of computation and indeed what is actually computable are facts of nature that constrain both natural and artificial intelligence. Second, given the constraints of computability and the costs of computation, greater intelligence relies on the reuse of prior computation. Therefore, to the extent that both natural and artificial intelligence are able to reuse the findings of prior computation, both pursuits can be advanced at once.

Neither of the dual pursuits of AI entirely readied researchers for the now glaringly evident ethical importance of the field. Intelligence is a key component of nearly every human social endeavor, and our social endeavors constitute most activities for which we have explicit, conscious awareness. Social endeavors are also the purview of law and, more generally, of politics and diplomacy. In short, everything humans deliberately do has been altered by the digital revolution, as well as much of what we do unthinkingly. Often this alteration is in terms of how we can do what we do—for example, how we check the spelling of a document; book travel; recall when we last contacted a particular employee, client, or politician; plan our budgets; influence voters from other countries; decide what movie to watch; earn money from performing artistically; discover sexual or life partners; and so on. But what makes the impact ubiquitous is that everything we have done, or chosen not to do, is at least in theory knowable. This awareness fundamentally alters our society because it alters not only how we can act directly, but also how and how well we can know and regulate ourselves and each other. 

A great deal has been written about AI ethics recently. But unfortunately many of these discussions have not focused either on the science of what is computable or on the social science of how ready access to more information and more (but mechanical) computational power has altered human lives and behavior. Rather, a great deal of these studies focus on AI as a thought experiment or “intuition pump” through which we can better understand the human condition or the nature of ethical obligation. In this Handbook, the focus is on the law—the day-to-day means by which we regulate our societies and defend our liberties …

Dubber, Markus D.; Pasquale, Frank; Das, Sunit (2020). Oxford Handbook of Ethics of AI (OXFORD HANDBOOKS SERIES) (Function). Kindle Edition.  

Just delving into this. Pretty interesting, right off. 

 

TOBY ORD INTERVIEW

 

 I've cited Toby Ord before.

 

ETHICS OF AI, ANOTHER CITE

Every task we apply our conscious minds to—and a great deal of what we do implicitly—we do using our intelligence. Artificial intelligence therefore can affect everything we are aware of doing and a great deal we have always done without intent. As mentioned earlier, even fairly trivial and ubiquitous AI has recently demonstrated that human language contains our implicit biases, and further that those biases in many cases reflect our lived realities. In reusing and reframing our previous computation, AI allows us to see truths we had not previously known about ourselves, including how we transmit stereotypes, but it does not automatically or magically improve us without effort. Caliskan, Bryson, and Narayanan discuss the outcome of the famous study showing that, given otherwise-identical resumes, individuals with stereotypically African American names were half as likely to be invited to a job interview as individuals with European American names. Smart corporations are now using carefully programmed AI to avoid implicit biases at the early stages of human resources processes so they can select diverse CVs into a short list. This demonstrates that AI can—with explicit care and intention—be used to avoid perpetuating the mistakes of the past. 

The idea of having “autonomous” AI systems “value-aligned” is therefore likely to be misguided. While it is certainly necessary to acknowledge and understand the extent to which implicit values and expectations must be embedded in any artifact, designing for such embedding is not sufficient to create a system that is autonomously moral. Indeed, if a system cannot be made accountable, it may also not in itself be held as a moral agent. The issue should not be embedding our intended (or asserted) values in our machines, but rather ensuring that our machines allow firstly the expression of the mutable intentions of their human operators, and secondly transparency for the accountability of those intentions, in order to ensure or at least govern the operators’ morality. 

Only through correctly expressing our intentions should AI incidentally telegraph our values. Individual liberty, including freedom of opinion and thought, are absolutely critical not only to human well-being but also to a robust and creative society. Allowing values to be enforced by the enfolding curtains of interconnected technology invites gross excesses by powerful actors against those they consider vulnerable, a threat, or just unimportant. Even supposing a power that is demonstrably benign, allowing it the mechanisms for technological autocracy creates a niche that may facilitate a less-benign power—whether through a change of hands, corruption of the original power, or corruption of the systems communicating its will. Finally, who or what is a powerful actor is also altered by ICT, where clandestine networks can assemble—or be assembled—out of small numbers of anonymous individuals acting in a well-coordinated way, even across borders.

Theoretical biology tells us that where there is greater communication, there is a higher probability of cooperation. Cooperation has nearly entirely positive connotations, but it is in many senses almost neutral—nearly all human endeavors involve cooperation, and while these generally benefit many humans, some are destructive to many others. Further, the essence of cooperation is moving some portion of autonomy from the individual to a group. The extent of autonomy an entity has is the extent to which it determines its own actions. Individual and group autonomy must to some extent trade off, though there are means of organizing groups that offer more or less liberty for their constituent parts. [Dubber, et al, Ch 1.]  

A lot to consider in this book.