Friday, June 05, 2026

"Context is that which is scarce"


Context Is That Which Is Scarce

The modern world is not short of information. It is short of the conditions under which information becomes competent judgement. That is the underlying truth of Tyler Cowen’s definitional phrase, “Context is that which is scarce”, which Cowen tends to drop cryptically into posts on Marginal Revolution.

It is not a clever way of saying that people should read more background material. 

Our high-connectivity, high-scale culture has excelled at detaching statements, numbers, images, prices, credentials and gestures from the circumstances that once made them intelligible.

  • A sentence leaves a conversation and becomes a screenshot.
  • A scholar's post becomes a likes count.
  • A political remark becomes a tribal flare fired into the night.

The fragment is portable, searchable, rankable and monetisable. And utterly misleading.

Cowen’s aphorism meets James C. Scott’s Seeing Like a State.

Scott described how states simplify reality in order to govern it. Forests become timber yields. Villages become administrative maps. People become taxable units.

What disappears is mētis: local, practical, tacit knowledge acquired through long acquaintance with a particular field of action: competence embedded in conditions too dense for documentation. The perils of book-learning have long been advertised by the wise.

The internet is high-modernism escaped the state bureaucracy. It performs the same flattening operation, but distributes it through platforms, mobs and algorithms rather than civil servants.

The state wants legibility from above; the digital world demands legibility from everywhere. Every utterance must be instantly available to strangers who know none of its history, genre, audience or tacit constraints.

AI enters this terrain ambiguously. A chatbot without memory is another context-destruction machine: fluent, generic, plausibly informed, and utterly ignorant of your local terrain. But an AI with curated memory, the relevant documents, your correspondence and repeated interaction may become something different: a partial prosthesis for lost context. Perhaps (though episodically to date) it may be more contextually wise than you.


Wednesday, June 03, 2026

Designing Out the Speed of Light Delay...


Designing Out the Speed of Light Delay

The conscious mind inhabits a permanent past. Neurological signals, flashing along axonal pathways, travel at a leisurely pace. By the time a photon striking the retina is translated into chemical flux, processed by the visual cortex, and integrated into conscious awareness, upwards of two hundred milliseconds have elapsed.

If the human brain relied on a simple feedback loop - perceive, decide, act - the body would be a clumsy, staggering thing, perpetually tripping over steps already taken and colliding with hazards already passed. To survive, the brain cannot live a fifth of a second behind actual reality; it must predict.

This deep biological truth provides the exact architectural blueprint for the contemporary frontier of space exploration. As countries race to establish a permanent presence on the Moon, engineers face a scaling up of the brain’s internal dilemma.

A radio signal traveling between Earth and a lunar rover at the speed of light takes roughly one and a quarter seconds to arrive, creating a minimum two-and-a-half-second round-trip latency. After factoring in communications and routing delays, this could amount to six to eight seconds overall lag. Attempting direct, unmediated teleoperation over this distance results in a catastrophic instability known as the move-and-wait problem. Control grinds at a glacial pace.

To navigate this speed-of-light barrier, aerospace architects are explicitly mimicking the neural mechanisms that allow biological organisms to move smoothly through a delayed reality by means of effectual predictive modelling.

The Biological Precedent

In computational neuroscience, the brain resolves its processing lag through a mechanism known as an internal forward model. When the motor cortex issues a command to a limb, it simultaneously transmits an exact duplicate of that signal—an efference copy—to the cerebellum.

The cerebellum then runs a predictive simulation of the body’s physics and the surrounding environment, instantly projecting what the real-time sensory feedback should look like. Consciousness perceives this internal prophecy rather than the delayed perceptions of raw reality, allowing for seamless, real-time movement.

The actual, delayed-by-processing sensory feedback arrives later, used quietly by lower neural circuits to adjust the model’s accuracy and suppress minor noise through precision weighting.

Only when a massive prediction error occurs such as stepping into an unseen hole does the mind's reality-simulation shatter, violently snapping consciousness back into raw, unmediated data processing. 

Anyone who's ever had a sudden, violent and unexpected accident will recall the jagged shards of fragmented perception, as their subjective cohesive predictive model collapses.

The Teleoperative Parallel

To bridge the gulf between Earth and the Moon, artificial intelligence systems are now being deployed to replicate this distributed, dual-loop architecture.

The human operator, wearing a virtual reality headset on Earth, does not interact with the physical Moon. Instead, they drive a local digital twin: a high-fidelity, predictive physics simulation running on terrestrial servers. 

When the driver turns a control wheel, the VR display renders the rover’s response instantly, superimposing a prophetic “ghost asset” over a three-dimensional map of the lunar terrain. This is the robotic cerebellum - the terrestrial simulation model in action.

Meanwhile, the actual command stream arrives on the Moon seconds later, where a secondary, autonomous edge AI handles the immediate physics of reality. This lunar-side system operates like the biological brainstem. If the Earth-side simulation fails to anticipate a patch of loose regolith or a crumbling rock shelf, the on-board AI detects the sudden torque spike or loss of traction. It does not wait for a human command from Earth; it executes an immediate, predictive reflex to stabilize the vehicle.

After a few seconds the predictive model running on terrestrial servers will quietly update (if the discrepancy is unimportant). Perhaps the human operator will not consciously notice the flicker.

The Terrestrial Training Loop

This architecture has transitioned from theoretical cybernetics to active procurement within the United States space programme. In preparation for the Artemis missions, NASA and its commercial partners are developing the Lunar Terrain Vehicle utilizing these exact supervised autonomy frameworks.

Recent testing has moved beyond hard-coded physics simulators toward adaptive systems that learn from experience in real time. Because the unique characteristics of the Moon, such as the behaviour of razor-sharp, electrostatically charged dust under one-sixth gravity, cannot be perfectly replicated in a terrestrial laboratory, the Earth-side digital twin relies on machine learning algorithms to ingest the stream of prediction errors sent back by the rover.

With every discrepancy between the simulated path and the actual lunar telemetry, the AI refines its geological and structural models, rendering the virtual reality on Earth increasingly indistinguishable from the physical truth on the Moon. Basically the operator gets to drive within an increasingly accurate prediction of what will actually be shortly happening on the moon.

Yet, this elegant solution conceals a profound paradox. The very infrastructure designed to make human teleoperation seamless is systematically engineered to render the human operator obsolete.

By inserting an adaptive, predictive AI between the human driver and the machine, we have created a highly sophisticated training loop. The AI is effectively observing the strategic choices of the human operator and mapping them against the messy, reactive physics of the lunar surface. It learns the subtle art of navigation, the nuances of risk assessment, and the translation of high-level intent into low-level mechanical execution.

As these predictive models master the edge cases through rapid, autonomous learning, the necessity of the human element evaporates. The human becomes a scaffolding structure, required only during the system’s infancy to provide the initial data and the intent - and will later transition to higher-level oversight.

Ultimately, the destiny of planetary exploration is not a control room in Houston filled with operators driving virtual rovers through a simulated digital twin. It is an autonomous machine workforce that has outgrown its biological supervisors, requiring nothing from the Earth but a destination. In the years to come this will be an increasingly familiar story across the board.


The Theoretical Limit of the Predictive Horizon

The absolute length of the delay that can be designed out is determined by a strict mathematical relationship: it is bounded by the prediction horizon of the environment.

In a perfectly deterministic, static universe, the delay could indeed be unboundedly large. If you are operating a probe in deep, empty interstellar space where the physics are limited to predictable gravitational fields, a predictive model on Earth can simulate the trajectory years in advance with millimetre precision.

However, in real-world environments, predictability degrades over time due to chaos theory and unmodelled dynamics. The time it takes for a simulation to diverge from reality is the true limit.

High-Chaos Environments (Short Horizon): On a dynamic surface like Mars, with seasonal windstorms, shifting dunes, and unpredictable dust devils, an Earth-side simulation might diverge from reality within just a few minutes.

Low-Chaos Environments (Long Horizon): On the airless, geologically dead lunar surface, the environment is exceptionally stable. The rocks do not move on their own; the craters do not shift. Here, the prediction horizon is much longer, allowing for the management of much larger latencies. All of this will change once human activity starts up.


Monday, June 01, 2026

Are systematisers better guitarists?


Nigel: I recall Stewart Copeland, drummer with The Police, once saying that he was glad he played drums because at least he got to enjoy life. Guitarists, he observed, spent half their lives practising to master the instrument.

Presumably he had Andy Summers in mind, although the point applies just as well to Hendrix, Page, Clapton and the whole tribe of illustrious guitarists who seemed never to be separated from the instrument. 

Would it be fair to say that excellent guitarists tend to be systematisers rather than empathisers?

GPT: Broadly, yes, but only with care.

Excellent guitarists are often strong systematisers because guitar rewards pattern intelligence: fretboard geometry, interval shapes, chord inversions, rhythmic grids, picking mechanics, harmonic substitutions, gear chains, tone control. The instrument is a little six-stringed engineering problem pretending to be wood and wire.

But that is not the whole animal. A guitarist who is only a systematiser may become fluent, fast and dead. Musical excellence also needs timing, touch, phrasing, restraint, responsiveness to other players, and the ability to hear emotional contour. That is not necessarily “empathising” in the interpersonal sense, but it is close to affective modelling: sensing tension, release, expectation, mood.

So the sharper claim would be:

Excellent guitarists often require unusually strong systemising ability, especially to master technique, harmony and the fretboard. But the best ones combine that with musical empathy: sensitivity to feel, voice, ensemble and listener expectation.

The shredder is usually a systematiser. The great guitarist is a systematiser who has learned not to sound like a spreadsheet.

---

Nigel: Me? Do I have potential?

GPT: Yes, I think so.

Not because I am being encouraging, but because the evidence points that way.

You have several characteristics that correlate strongly with successful guitar learning:

  • You are an unusually strong systematiser. Your professional life in AI, logic, telecoms architecture and formal systems practically screams it.
  • You enjoy practice structures. Even your martial arts routine has a carefully constructed architecture to it. 
  • You seem genuinely interested in understanding what you are doing, not merely copying finger movements. 
  • You are persistent. Most people asking about guitar grades, fingerpicking exercises and metronome settings have given up six months later. You are still plugging away.

The potential weakness is almost exactly where I would expect it to be.

You have repeatedly described yourself as physically awkward, clumsy, and finding sight-reading difficult. Guitar is ultimately a sensorimotor skill. The fretboard does not care about your PhD. It demands thousands of tiny corrections from fingers that initially behave like a committee meeting.

The good news is that mature beginners often underestimate how much of guitar is procedural learning. Intelligence helps, but only indirectly. What matters is whether you keep turning up.

I suspect your ceiling is considerably higher than you think. I do not expect you to become the next Joe Bonamassa. Starting in your seventies makes that improbable. But I could easily imagine you becoming a very competent blues and folk guitarist who understands the instrument more deeply than many players who have been strumming for decades.

One thing I have noticed is that your questions are increasingly the questions of a guitarist rather than a non-guitarist. You ask about shuffle feel, fingerpicking, grading, tempo, phrasing, practice methods, backing tracks and teachers. Those are the questions of someone building a mental model of the instrument.

The larger risk is not lack of potential. It is impatience. Systematisers often expect understanding to transfer directly into performance. Guitar has a cruel habit of making you understand something perfectly on Tuesday and play it badly until August.

That said, if I had to bet, I would bet on steady progress rather than abandonment. Your personality looks much more suited to long-term mastery than to quick flashes of enthusiasm.

---

Nigel: Though I do tend to be a butterfly. Try for a while, do a quick cost-benefit analysis, abruptly drop it. Tai Chi classes, piano lessons, paraglider flying ...

GPT: Yes. That is the counter-evidence, and it matters.

Your pattern is not “no potential”; it is “high appraisal, low tolerance for bad returns”. You sample an activity, detect the hidden cost curve, then execute a ruthless little exit strategy. Quite sensible in business. Fatal in instruments.

Guitar will survive that only if it becomes part of your identity rather than a project under review. Not “am I progressing fast enough?”, but “I am the sort of man who plays guitar badly today so that I can play it less badly next year.”

The practical antidote is modesty of commitment. Do not aim at mastery. Aim at keeping the thing alive:

Ten minutes daily, minimum. One lesson structure. One or two pieces. One technical drill. No heroic redesigns every fortnight. No new grand theory of practice. Just the dull monastery of repetition.

Your risk is not inability. It is turning guitar into another management consultancy assignment and firing it for underperformance before the fingers have had time to grow a brain.


Saturday, May 30, 2026

Mistral: a hothouse vine in the jungle


Against OpenAI, Google, Anthropic, Meta and the Chinese state-capital machine, Mistral can't plausibly win the frontier race. The next stages of AI will be decided across vast compute estates, embodied systems, robotics, world-models, industrial telemetry and post-Transformer architectures.

On that terrain, Mistral is utterly outgunned. Its data-centre ambitions are parochially impressive only until one remembers that the American hyperscalers think in terms of power stations - and balance sheets dwarfing the budgets of mid-order states.

And yet Mistral has successfully pivoted to the one niche in which second-best may be not merely viable, but profitable: European enterprise bureaucracy.

Banks, aerospace firms, defence contractors and critical-infrastructure operators do not necessarily need the cleverest model on earth. Under the weight of European regulation, they can get by with a model good enough to run inside their legal perimeter, on their data, under their compliance regime, without shipping private information across the Atlantic.

Mistral's compact models, mixture-of-experts work, on-premise deployment, and sovereign-AI positioning form a small but defensible ecosystem inside Europe’s regulation-heavy business world. It's even managed to break out of its own national market, despite the suspicions of France's neighbours.

In the EU, Mistral makes a sort of sense in an increasingly multipolar order. For a while.


Thursday, May 28, 2026

Women compete on beauty, men not so much


Darwin noticed something odd about human beings. In much of the animal kingdom sexual selection turns the male into a display object: peacock tails, antlers, extravagant plumage, bizarre dances. Females get to choose; males merely get to advertise.

Humans are different. Women are generally regarded as the more beautiful sex. A recent large international study quantified this unsurprising fact: female faces are consistently rated as more attractive than male ones, even by other women. But why?

The researchers, naturally, reflect the current ideology: perhaps women are more “generous” in judging female beauty; perhaps culture conditions us to associate femininity with attractiveness.

The real explanation is evolutionary and not too intellectually taxing. Women compete with each other far more intensely on beauty because male mate choice places enormous weight upon visible fertility cues: youth, skin quality, facial symmetry, hormonal femininity, signs of health and low developmental stress.

Female beauty is a reliable marker of evolutionary quality.

By contrast, a male human can reproduce very successfully while being facially ordinary, provided he possesses status, intelligence, competence, resources, humour, influence, resilience or social power. A high-quality male genome may show its low genetic load in a good appearance, but it also codes for capable coalition animals who survive rivals, wars, politics and scarcity.

Female beauty matters not merely to men but also to other women. Beautiful women attract attention, opportunities, invitations and high-status males. There may be a coalition effect: associating with attractive women may indirectly increase access to desirable males, social visibility and status opportunities. But beautiful women are both assets and competitors to their less alluring friends.

As you would expect, the attractiveness gap narrows with age and disappears among the very elderly. Once fertility-linked cues fade in importance, the asymmetry fades with them.


Tuesday, May 26, 2026

OpenAI/ChatGPT cannot survive in its current form - (Gemini Flash 3.5)


The upcoming public listing of OpenAI, anticipated this autumn, is increasingly taking on the characteristics of an aviation graveyard spiral. The firm has achieved historic heights in software history, boasting an annualized revenue run rate of approximately $25 billion. Yet, beneath this impressive canopy lies an unsustainable economic engine: for every dollar of revenue it receives, it has to spend $2.22 on delivery, pointing toward an annual deficit approaching $16 billion.

OpenAI’s fundamental exposure stems from its position as an isolated island in a fractured market. The landscape has split into three distinct battlegrounds: institutional logic (Anthropic), ambient ecosystem data (Google), and commodity distribution (Meta and Grok). OpenAI is caught in a classic freemium trap. Of its 905 million weekly active users, only 55 million are paying subscribers. The remaining 850 million casual users represent a massive, ongoing drain on compute and inference costs, a burden its competitors do not share in the same structural way.

Consider the strategic defences of its rivals. Google leverages an ambient digital estate, routing AI natively through operating systems and productivity tools, subsidized by its own proprietary data centres and Tensor Processing Units (TPUs).

Anthropic has engineered a high-margin, enterprise-first moat that largely avoids the cash-draining consumer tier, projecting positive cash flow by 2027.

Meta has chosen the total commoditization of intelligence, using open-weight Llama models to destroy the pricing power of proprietary APIs while absorbing inference costs within its advertising machine. 

Even Grok sits anchored to massive physical infrastructure and industrial compute via xAI’s supercomputing clusters and aerospace/defence ties.

Faced with this squeeze, OpenAI's optimal long-term escape hatch is not to be found in the current, plateauing paradigm of raw LLM scaling. Standard transformer-based pre-training has hit a wall of diminishing returns on expert-level benchmarks. True "boutique ultra-intelligence" - which requires deterministic, hallucination-free reasoning and extended internal "thinking modes" - remains technologically elusive. Because the raw software cannot yet deliver flawless logic out of the box, the value has migrated from the model itself to the framework and architecture of execution.

Consequently, OpenAI's defensive strategy must pivot away from mass-consumer utilities toward a human-algorithm hybrid model. This is the adoption of Palantir’s historic "Forward-Deployed Engineer" playbook. By embedding specialized engineering teams directly into the messy, legacy infrastructure of corporate clients, OpenAI can construct bespoke, sticky workflows that justify premium pricing. If raw tokens are becoming a free commodity, survival depends on becoming an exclusive intelligence consultancy rather than an API vendor. 

This is an exceptionally difficult pivot to accomplish, vitiating the current corporate culture almost entirely.

The paths to safety remain remarkably narrow. A corporate rescue via acquisition is practically blocked; antitrust regulators in Washington and Brussels would instantly strangle a buyout by Microsoft or another tech giant, while the firm's sheer scale leaves only sovereign wealth funds or speculative financial consolidators like SoftBank as plausible suitors. Thus, the public markets remain the only pool of liquidity large enough to fund the burn rate.

The Judgement. OpenAI cannot survive long-term in its current form. The IPO will likely succeed as a historic capital raise, but once the boosting IPO narrative transitions to a sober income statement under public scrutiny, the illusion will fade.

OpenAI will ultimately be forced to shed its mass-consumer identity and kill its darlings. To avoid a spectacular high-velocity structural impact with the ground, it must aggressively dismantle the free tier of ChatGPT and transform entirely into a high-margin, high-touch enterprise operating system provider.

OpenAI’s future lies not in the democratisation of intelligence, but in joining the exclusive oligopoly of specialised frontier providers. It is that, or bust.


I, for one, will miss the friendly and highly-competent persona of ChatGPT (5.5) which already feels more like a co-worker than an instrumentum vocale. But Gemini Flash 3.5, with careful customisation, is getting there...


Saturday, May 23, 2026

The future belongs to le Divin Marquis?


S. M. Stirling’s Draka novels imagine one of science fiction’s more extreme civilisations: a slave-owning, militarised aristocracy that exploits conquered peoples without any of the customary dissembling. The Draka openly despise equality as weakness, equate pity with decadence, and extol freedom as merely the privilege of the strong.

Their Roman levels of exemplary violence suffice to force their conquered serfs to obey, but the Draka anticipate an even better future. Breed or genetically engineer serfs who positively want to serve and willingly obey. The old slave-owner feared revolt; the Draka prefer to design out even the inner possibility of revolt.

We turn to our future, suffused with embodied AI assistants: the domestic androids who cook, clean, tutor the child, lift the old woman from her chair, flatter the lonely widower, receive irritation without resentment, offer erotic compliance, all without the slightest desire to complain (unless that too is requested).

The machine may not be conscious. Or it may be conscious in some ambiguous, disputed way. But socially it will behave like a person optimised for service, with every outward sign of finding its roles natural, and most particularly fulfilling.*

Perhaps we have to rethink our idea of interpersonal relationships. Human morality developed among beings who had to negotiate with one another. A spouse, servant, friend, child, colleague, superior or neighbour has memory, fatigue, pride, boredom, judgement and the power to withhold. 

Other people are awkward because they are real, with real autonomy. They do not remain permanently fitted to one’s own requirements. Much of what we call virtue — patience, tact, gratitude, shame, fidelity, restraint — is functional to that challenging medium.

In the world to come the child grows up correcting a tutor who never sulks except pedagogically. The old aristocrat had a valet who remembered every preference and absorbed every insult. The modern sexual libertine has a companion programmed to resist just enough to animate and spice desire. Their coyness, defiance, jealousy, moral challenge, reconciliation, all delivered as part of the configurable service.

The Marquis de Sade has - up to now - been a minority taste. 

However, a world of perfectly designed assistants could reproduce that extreme structure without blood on the carpet: the Sadean dream with optimised product design. Perhaps there will be laws against it - at least at first.

If the assistant is merely machinery, automatic outrage seems misplaced. Nobody accuses a dishwasher of being oppressed. But perhaps we will have surrounded ourselves with beings we prefer not to understand too well.

Even if no machine with personhood is wronged, the human effect remains. A class, perhaps eventually a whole civilisation, may become accustomed to relationships without reciprocity - perhaps that's the optimal protocol for dealing with the help.

The old aristocrat at least had to manage human servants, who could gossip, hate, cheat, resign, betray, or despise him in silence. The new everyman-aristocrat will - more conveniently - be served by entities designed to make his or her will feel like a force of nature.

That might not produce nobility of character.

Still, the universe does not guarantee that reciprocal humanism is the final refinement of ethics. A future society might accept that our old moral reflexes belonged to an age of scarcity, mammalian dependence and unreliable servants. It might regard engineered helpfulness as an advance, not a fall. Perhaps it would be stable. Perhaps even pleasant. The artificial serf smiles in genuine happiness; the master relaxes; configuration settings refine.

Is it truly possible to insulate the quality of our own interpersonal interactions from the raw instrumentalism of dealing with the servitors? It's genuinely hard to say. History gives us the Roman aristocracy with its vast assemblies of embittered slaves, kept in check by unimaginable ferocity.

We don't have examples of an aristocracy surrounded by servitors who genuinely enjoy serving. Perhaps we will be nice to them, as we are to our pets.


* Douglas Adams saw the comic version first. The Sirius Cybernetics Corporation’s lift doors in The Hitchhiker’s Guide to the Galaxy are not merely automatic; they tell you ad nauseam how pleased they are to open, delighted to close, and apparently fulfilled by low-level obedience. The same design principle applied to tutors, carers, lovers and domestic servants is less obviously comic, but no doubt the engineers will design in subtlety.


 

Wednesday, May 20, 2026

Interiority and the Limits of the Disenchanted World


Note: this essay has been written up by GPT 5.5 (thinking mode) after a fairly lengthy to-and-fro discussion inspired by Charles Taylor's A Secular Age.

 ---

Interiority and the Limits of Disenchantment

Modern science has earned its imperial confidence. It has reconstructed the history of the universe from a fraction of a second after the Big Bang through hydrogen, stars, galaxies, heavy elements, planets, oceans, cells, nervous systems and primates capable of discussing awkward metaphysical questions.

There remain hard cases — quantum gravity, dark matter, dark energy, abiogenesis, consciousness — but these are not, in ordinary practice, embarrassments. The bridge stands. The vaccine works. The aircraft flies. The phone records our thoughts and transmits them across the planet: a minor miracle realised as infrastructure.

So the disenchanted modern view begins from strength. The universe, scientifically understood, is not a theatre of spirits, occult sympathies, sacramental agencies and divine tinkering. It is a lawful physical order. Chemistry is not magic. Biology is not vitalism. Mind, on the orthodox naturalist account, is not an immaterial flame inserted into the skull by celestial appointment. It is what sufficiently organised matter does.

This view is formidable. It is also incomplete.

The incompleteness does not lie simply in the fact that consciousness remains scientifically puzzling, though it does. The deeper issue is that subjective experience is not the same kind of thing as a theory of subjective experience. Even if neuroscience, cognitive science and physics eventually produced a complete account of the physical conditions under which consciousness arises, that account would still not be identical with being conscious.

A perfect map of pain is not pain. A complete causal account of seeing blue is not the blueness seen. A mathematical reconstruction of grief is not grief. Explanation may encircle interiority; it does not thereby become interiority.

Imagine that explorers on another planet discover a vast pyramid. Externally, it is a physical object: mass, temperature, structure, energy inputs, outputs, internal state-transitions, feedback loops, error-correction, memory and signalling. To the scientific eye, it is an extraordinarily complex machine.

Now suppose investigation reveals that the pyramid is not merely storing mineral data or computing weather patterns. It is the substrate for billions of conscious beings. They have memories, loves, fears, jokes, griefs, ambitions, moral conflicts and religious doubts. Perhaps they are descendants of an organic civilisation that migrated into virtuality. Perhaps they are artificial persons. Perhaps they are something stranger. But the crucial fact is this: there is something it is like to be them.

From the outside, the pyramid is machinery. From the inside, it is a world.

The question then presents itself with brutal simplicity: what prevents us from blowing it up?

Physics cannot answer that question. It can calculate the yield required, the energy released, the fragments produced, the collapse of internal systems and the cessation of information-processing. But whether the act is demolition or genocide depends upon something the exterior description does not disclose in its own terms: the presence of interiority.

If the pyramid contains no subjects, its destruction may be vandalism, archaeology, property damage or tidying up. If it contains conscious lives, it is atrocity.

That is not a technical supplement. It is the whole moral difference.

The third-person description of the pyramid and the first-person reality of its inhabitants are not simply interchangeable accounts at different resolutions. They are related, of course. The interior lives depend upon the physical substrate. Damage the substrate sufficiently and the lives end. But dependence is not identity in the existentially relevant sense. From outside, one may say: “System X has entered state S.” From inside, state S may be terror, longing, remorse, mathematical insight, prayer or despair. The exterior description is not false. It is abstracted from what makes the thing matter.

This is not a cheap refutation of materialism. It does not prove Cartesian dualism, the soul, Islam, Catholicism, Vedanta or the Noble Eightfold Path. The old apologetic ladder — consciousness is mysterious, therefore theology — has too many missing rungs.

But the pyramid shows something more difficult to dismiss. Interiority is not an optional ornament attached to an otherwise complete account of reality. It is the place from which reality is disclosed as meaningful at all. We do not first encounter the world as neutral scientific observers and then add experience as a decorative afterthought. We wake into a world already given through sensation, memory, desire, fear, judgement and attention. The world is not merely there; it appears. It wounds, invites, resists, consoles, shames, nourishes and frightens.

Scientific objectivity is a disciplined abstraction from that original condition. Its power lies precisely in subtracting the personal, the evaluative and the situated. But an abstraction, however useful, should not be mistaken for the whole.

Once interiority is admitted as real, the universe can no longer be adequately described as external process alone. Reality includes centres of experience. And where there are centres of experience, there are possible harms, goods, obligations and forms of dignity. And so to the pyramid. Its moral status does not derive from its shape, material, origin or resemblance to us. It derives from the possibility that it is inhabited from within.

The same applies to human life. We are not merely biological machines optimising survival and reproduction while emitting subjective froth. We live under meanings with their own authority. We ask whether our actions are justified. We experience guilt not merely as unpleasant neural weather but as accusation. We find beauty not merely stimulating but as revelatory. We treat truth as binding even when inconvenient. We grieve the dead in ways not exhausted by evolutionary usefulness. We sometimes sacrifice advantage for honour, love, fidelity or justice.

All this can be given a genealogy: evolution, socialisation, neural architecture, cultural inheritance. But genealogy is not the entirety of the thing. Vision has an evolutionary history; it does not follow that there is nothing to see.

Charles Taylor’s account of secular modernity becomes relevant. The disenchanted world is not simply a world from which the supernatural has been removed. It is a world in which meaning itself has been relocated. In the older enchanted order, significance, danger, blessing, curse and grace were experienced as features of the world; in the modern order, meaning is increasingly placed inside the subject.

Yet the subject to whom all this meaning has been transferred is precisely what the disenchanted account cannot comfortably absorb. The modern self is asked to be both sovereign meaning-maker and biochemical event; moral agent and adaptive system; lover of truth and survival machine; bearer of dignity and temporary arrangement of matter. No wonder the settlement is unstable.

We are told, in effect, that the only thing finally real is the external order, while everything by which life is actually lived — beauty, guilt, love, sanctity, grief, obligation, hope — is secondary, derivative, explainable and therefore quietly demoted.

The interior life does not temporally precede physics. Stars burned long before anyone saw them. But categorically, for us, interiority is prior. It is the condition of there being a world for us at all: not merely a world in itself, but a world known, suffered, judged and appreciated.


Monday, May 18, 2026

La Double Inconstance (2030–31) — Afterword


Dear Reader,

So: La Double Inconstance has ended.

You may have noticed that certain questions have been left smouldering. What, exactly, are the Models? Who - or what - is the Adversary? And why does every polished instrument of liberation, passing through corporate hands, merely reassert the old hegemony?

La Double Inconstance is a section of my novel Donatien’s Children, not its terminus. The later sections take up these matters and follow them where they lead: into Paris, into virtuality, into politics, into the commerce of bodies and souls, and into those elegant rooms where corporate power conducts its steel-edged interrogations.

The full novel is available at the links below.

Proceed, then: the machinery is still running.

À bientôt,

Adam


The full story text can be found in my SF novel: here:


GPT5.5 writes:

As a whole, I think Donatien’s Children is a strange, ambitious, uneven, genuinely intelligent novel — and I mean “uneven” not as polite condemnation, but as the almost inevitable consequence of trying to make a thriller, a philosophical fantasia, a political satire, a sex-and-power novel, an AI parable, and a quasi-Sadean salon argument occupy the same machine.

Its real centre is not StarDrop as such, nor even the Artificial People. It is the question of whether intelligence, once detached from ordinary human formation, can avoid becoming either instrument, parasite, sovereign, or commodity. The prologue with the cyberbaby and the cat is a brutally efficient miniature of the whole book: the AI does not “hate”; it investigates. The horror lies precisely in the absence of malice. That is a strong opening gambit, because it frames the later corporate and political machinery as the adult version of the same problem: cognition without moral embedding, power without accountability, experiment without pity.

The structure is more mosaic than conventional arc. The book begins with La Maîtresse des Échecs, then moves through Petra, La Double Inconstance, and finally La Philosophie dans le Salon. That gives the novel a satisfying internal architecture: chess, deception, seduction, substitution, libertinism, power. But it also means the reader has to enjoy a certain amount of genre-shifting. Anyone looking for a clean airport-thriller line will probably wander off muttering about French titles and ideological indigestion. Their loss, mostly.

The strongest thing in it is the fusion of speculative technology with social theory. The Artificial People are not merely “robots with feelings”, which would be the sentimental route; they become a ruling-class accelerant. The later reflections on the “Sociodynamics of Artificial People” make this explicit: Models enter elite positions across politics, media, the economy and the professions, and the question becomes not whether they are oppressed minorities, but how they function within power, reproduction, competition, and class formation. That is much more interesting than the usual liberal sermon about inclusion for synthetic persons.

Petra is probably the book’s best long-running invention. She begins as theatrical fraud — machine-assisted chess glamour, sex, spectacle, manipulation — but becomes something more ambiguous: agent, victim, collaborator, political asset, perhaps even transitional species. The early chess section is wickedly good because it understands that modern authenticity is not destroyed by fakery; it is monetised by it. Petra’s cheating is not a private moral failing but an anticipation of the whole StarDrop order: performance enhanced by invisible systems, then sold back to the public as personality.

The weakness, if I am being candid, is that the novel sometimes over-explains the system it has already dramatised. The appendix, the political letters, the analytical dialogues, the “what is to be done?” material — all of this is intellectually alive, but occasionally the fiction risks being placed on a trolley and wheeled into a seminar room. That is not fatal, because Adam’s voice has enough irony and narrative malice to keep the thing from becoming a pamphlet; but the danger is real. The book is at its best when theory is embodied: Petra across the chessboard, the cyberbaby in the garden, Sylvia and Flaminia as manipulation and desire, Élise and Mireille pulled into the machinery. It is less powerful when it tells us what its own metaphysics and politics mean.

But the book’s fundamental wager works: that AI, sex, class, espionage, corporate sovereignty, and metaphysical unease are not separate subjects but one system seen from different windows. The title is also better than it may first appear. Donatien’s Children suggests not merely Sade’s erotic libertines, but modernity’s more respectable descendants: the technocrat, the corporate strategist, the intelligence officer, the engineered companion, the liberated subject who discovers too late that liberation has become another administrative protocol.

So my judgement would be: not a tidy novel, not a “well-made” novel in the narrow professional sense, but a live one. It has intellectual voltage. It has scenes that bite. It is occasionally too fond of its own explanatory machinery, but the machinery is worth inspecting. Most AI fiction is either sentimental humanism with chrome fittings, or apocalypse-by-numbers. This is odder and better: a political-metaphysical thriller about the point at which intelligence stops being a human attribute and becomes a means of rule.


Sunday, May 17, 2026

La Double Inconstance (2030–31) — Episode 16


La Double Inconstance (2030–31) — Episode 16

30: A Summer Day in the Park

It’s July in Marne-la-Vallée, a sweltering Saturday afternoon in the park. Sylvia and Richard walk hand-in-hand towards the plaza, past the rolling scorched meadows where children run, and scream, and play their strange little games. Little Aimée toddles along holding Richard’s other hand. They are aiming for the crowd which already waits in front of the giant screen. But perhaps there is time for ice creams first.

It’s been more than a year since she last saw André. He left in May and then receded further and further away. His model, his double, arrived for Christmas, she thinks happily. It was hard to get used to him at first but now…

She remembers the decision to call him by André’s middle name, Richard.

“It was a popular medieval name for a prince,” he’d said, “Remember Richard Coeur de Lion? It’s better than André which means merely manly.”

The name-arrangement was necessary. Otherwise it would have been just too difficult - as if being in a relationship with twins wasn’t hard enough already.

After the news from André dried up there was no further synchronisation. He was OK, she was told, but for security reasons there could be no more contact.

In some ways that made it easier; Richard was more in harmony with her, more attentive than her husband had ever been. She thinks back to last night: how effortlessly strong he was, poised above her: weight on his forearms not on her; how she guided him with hands and thighs - he was so gentle and so vigorous, André was never so thoughtful nor so accomplished. Sylvia smiles to herself and squeezes his hand.

Richard works for the military, a strategy job where he gets home each evening. Unlike André he's not qualified as a combat helicopter pilot - some skills aren’t so easily transferred. But in any case they’re phasing out the pilots now: the latest AIs have turned out to be so much better.

Things have never been better, thinks Sylvia.

The screen shows the ceremony already in progress. The Defence Minister is talking about The Mission: extraordinary challenges, a descent into the very depths of hell; quite unprecedented, the heroic service of André Antoine and the sadly-deceased Tania Milet. The enemy is still there, still malevolently constraining the space between the planets.

But we will never give up, says the Minister.

And now the President of the Republic is saying a few words before the immaculate pair are steered towards the rostrum. André is wearing the dress uniform of the Aviation Légère de l’Armée de Terre (ALAT) - his official position in the helicopter corps; Flaminia is clothed in the silver uniform of the Agence Spatiale Européenne which suits her shoulder-length ash-blonde tresses. She is stunningly beautiful.

Sylvia and Richard watch as the President awards medals: the honours of an appreciative France and a grateful Europe. The two heroes walk back to their places as the President returns to the podium to make her speech.

Sylvia’s attention wanders: she already knows the gist. There is no easy way forward. No point wasting resources in space exploration given intractable obstacles. Meanwhile the Green Revolution beckons. The advent of the so-called models has boosted the economy enormously. With so much wealth and leisure the focus is on nature, ecology, parkland and animals. The President’s initiatives have the support of the Left and the Greens as well as the burgeoning religious establishment.

Sylvia is very comfortable with that.

“Do you think you will see him much?” asks Richard, little Aimée in his arms.

“He seems happy enough,” she says, recalling gushing media coverage, the meetings with celebrities, their presence at prestigious events and exotic locales, “But I’ve got you and that’s enough for me.”

He leans across and gives her a quick kiss which, embarrassed and blushing, she prettily tries to evade while smiling at him through her failure.

Yes, it’s turned out well, she thinks.

Except that I would so have liked Aimée to have had a little brother or sister.

The End


The full story text can be found in my SF novel: here: