I am writing this morning from Ilknur and Thomas’s terrace in Kayalar, on the western coast of Türkiye. Below me I see the Aegean and across the water lies Lesbos. Only a few minutes away is the acropolis and the remains of the temple of Athena, that has stood here for two and a half thousand years.

I am writing from Assos. And I am writing about a single gesture that was made in this place. Plato dies in 347 BCE, and his best student does not become his successor. Aristotle leaves Athens and crosses to Asia Minor. Here, on this coast, he founds his first school. According to the story, something happens here that splits the history of thought. He stops thinking about the world and starts looking at it.

That is the whole gesture. Everything else I found on this rock tells you what it costs.

The Gesture

In the Academy it was about ideas. About the perfect behind the imperfect. About the shadows on the cave wall, an image I already leaned on in Ex Machina when I wrote about the simulation hypothesis. I was curious about Assos because something else begins here.

Aristotle dissects octopus. He records the gills of fish. He describes how an embryo forms in a hen’s egg, day by day. He tells his students to study even the lowliest creatures, because in everything alive there is something divine.

The question shifts. From Plato’s question about the idea to Aristotle’s question about the living thing, about ‘Lebendigkeit’.

This is the moment when natural science and philosophy have the same object for the first time. It is, if you like, the birth of what I today call Sci-Phi. And it does not happen in a library. It happens with wet hands on a beach.

We have forgotten this moment. We separated the disciplines, sorted them neatly, locked them into faculties. Today we stand in front of machines that think, cells we rewrite, systems we build and do not understand. And we notice: the separation was an administrative act, not an insight. So the question is not whether we should look again. The question is why we do it so rarely. I found four answers here.

First: looking is not free

I learn here that this school did not come out of nowhere. There was a man named Hermias. Hermias was a slave. He won his freedom, inherited the rule of Atarneus and extended it to the neighbouring cities, Assos among them. In his youth he had studied at Plato’s Academy. That is where he first met Aristotle. So a former slave builds a realm and uses it to fund philosophy. No monument. No statue. A collective of thinkers. Every time I go deeper into this cultural space, I find them, these treasures of inspiration.

A few years later the Persian king sends a mercenary commander. He lures Hermias into a trap under the pretext of a truce. Hermias is tortured. He does not name a single fellow conspirator. He dies, so the story goes.

Aristotle raises a monument to him at Delphi and writes him a hymn. Not to the man, but to Arete, to excellence itself. And decades later, back in Athens, that same hymn is held against him. A charge of impiety. A song of praise for a mortal. Aristotle leaves the city so that Athens would not sin against philosophy a second time.

I have been thinking for years about a simple equation: progress comes from talent and capital, multiplied by trust and friction. We talk about the left side constantly. Talent and capital are measurable, and therefore debatable. Here, on this rock, I see the right side in a single biography. Trust that turns a slave into a patron of reason. And friction that kills. Nobody looks closely unless somebody else is willing to carry the cost of it.

Second: looking is the first thing we give up

Two hundred years later a boy is born in the same city who becomes a boxer. His name is Cleanthes. He goes to Athens, hears Zeno, becomes a Stoic, carries water at night to afford his studies by day. After Zeno’s death he leads the Stoa for thirty-two years. From him comes the Hymn to Zeus, one of the great cosmic texts of antiquity. The universe as a living being, run through by a reason we take part in. ‘Lebendigkeit’ (Aliveness) in its purest form.

And from the same man comes, so it is handed down, the demand that Aristarchus of Samos be charged with impiety. Aristarchus’s is offence is that he had set the earth in motion. He had moved the hearth of the universe.

Eighteen hundred years before Copernicus, the answer was in the room. And the man who sang the universe most intimately wanted to prosecute the one who had looked at it.

Here I have to add a footnote, and the footnote matters more to me than the anecdote. The passage is disputed. In the manuscripts it may well be Aristarchus who accuses, not Cleanthes. The beautiful version rests on a conjecture, on a change made by later editors.

The best story this place has to offer may be false.

That is exactly why I am writing it this morning. We live in a time that has perfected ‘the art of being right’. Thumbs up, thumbs down. Reaction instead of reflection. What we lack is ‘the art of being wrong’. The willingness to take your own favourite story apart before somebody else does.

Dogmas are not other people’s convictions. Dogmas are the explanations we have stopped looking at.

Third: nobody looks alone

From the temple I can see Kaz Dağı, the Ida of antiquity. On that mountain, according to one of the traditions, lived the Idaean Dactyls. Mythical smiths and healers. They discovered iron. They taught people metallurgy, mathematics, the alphabet.

Originally there were three of them. Their names mean caster, hammer and anvil. Not one. Three. In this story technology does not come from a genius, but from the interplay of three forces, none of which achieves anything alone.

We are building the largest technology in our history while telling ourselves founding myths about single men in hoodies. The older myth hanging on this horizon is wiser. It knows that creation is a constellation. And that a single pair of eyes is not enough.

Fourth: in the end we look at ourselves

One last thing, and it stays with me even after the conversations here. Our word sarcophagus comes from this place. It was originally the epithet of a stone: sarkophagos lithos, flesh-eating stone. A limestone from Assos in which, as Pliny reports, the bodies of the dead were consumed within forty days, down to the teeth. The word for our last container comes from the ground I am sitting on this weekend.

We are working with great seriousness on abolishing ageing. We speak of cellular reprogramming, of longevity, of treating death as a solvable problem. I do not consider that hubris. I consider it the consistent continuation of what began here two thousand four hundred years ago, when someone started looking closely at living things. That is also my vision with tomorrowmensch.

But the question this stone asks does not get smaller. It gets bigger. If we can preserve the body: what exactly are we preserving?

‘Lebendigkeit’ is not the absence of death. A system that merely fails to stop is not alive. It is undead. What is alive is what keeps exposing itself, keeps correcting itself, keeps looking. That is the question we have to ask of every technology that promises us duration.

What remains

Aristotle went from here to Lesbos, to the lagoon of Pyrrha, and wrote the first pages of zoology there. Posterity later invented a death in the water for him. He is said, so the legend goes, to have despaired at the inexplicable tides of a strait and walked into it. Historically this does not hold. The story appears much later. But it says something about us. For the man who wanted to look at everything, we invented a death in the inexplicable.

Every year I write on the island of Værøy in Lofoten, surrounded by one of the strongest tidal currents in the world, the Maelstrom. Water that never stands still. I look out at the sea from there and at the same element here, three thousand kilometres further south, and the question has not changed. We are looking for equilibrium. The world is looking for dynamic equilibrium, for movement.

Assos is not a museum to me. That is not why I am here. The coastline, the villages, a visit to a large local cemetery. It is a reminder of a gesture that costs something, and that we cannot afford to spare ourselves.

Someone stopped thinking about the world and started looking at it.

We should do that again.

A new excavation area, a hundred meters from the main enclosures of Göbekli Tepe, August 2024. The roof is up; the digging is only beginning.

The Hill That Shouldn’t Be One

On August 12th, 2024, I travelled to Göbekli Tepe. With temperatures above 40°C (104°F) and a boiling sun, one could ask why. My curiosity could not be tamed; I had to see and feel this place. As I stood on this hill in southeastern Anatolia that, strictly speaking, shouldn’t be one, I wondered: what was this place? Now an ochre swelling in a dried-out landscape, fifteen kilometers from Şanlıurfa, the city where local tradition places the birth of Abraham. Göbekli Tepe means “potbelly hill”, some hear “hill of the navel”. A name so harmless it borders on comedy, for what lies underneath.

At school in Røros, Norway, I was taught that Stonehenge marked the dawn of monumental civilization, five thousand years old, a marvel. Then you stand here, looking down into circular enclosures of carved T-shaped pillars, foxes and serpents and vultures worked into limestone, and the archaeologists tell you what the dating says: more than twice as old. Around 9600 BCE. Before writing, before pottery, before the wheel, before, in all probability, the first farm. One of them, a man from Istanbul I met on site, put it this way: at Göbekli Tepe, wherever you put the spade in the ground, you find something that shakes your world.

But the fact that has never let go of me is not the age. It is this: the place was not lost. It was interred. The enclosures were filled in with tons of rubble, bone, and flint packed around the pillars; whether by the hands of the builders themselves or by the slow shrug of the hillside is still argued over among the excavators. Either way, the effect was the same. Burial became preservation. The mound is nine hectares: twelve soccer fields of archive, entirely man-made, fifteen meters deep at its highest point. After three decades of excavation, at most a tenth of it has been opened. Ground-penetrating radar suggests sixteen more enclosures and nearly two hundred carved pillars still standing in the dark. For eleven and a half thousand years they have held their carvings, and then, within living memory, someone opened the ground and began to read.

The so-called totem pole of Göbekli Tepe: faces upon faces, carved nearly ten thousand years ago. Şanlıurfa Archaeology Museum.

An hour’s drive east lies a sister site, Karahan Tepe, younger in excavation, older, perhaps, in its promise. No tourist buses. Wind, stones, a chamber of pillars rising from the bedrock, serpents everywhere in the carvings, and a handful of archaeologists who look into the millennia the way one looks into an unfinished manuscript. My guide that day, Tahe, walked me through it, and at some point he began to tell me a story that was old when Babylon was young: of Oannes, the being that rose from the sea with the body of a fish and the head of a man, and taught human beings writing, agriculture, and law. He told it the way you pass something on, not the way you cite something.

I flew home from Türkiye with so many questions, and they have followed me ever since. While it is interesting to understand who built this, it might be even more interesting to understand who buried it, and for whom.

I started writing this piece after a long conversation with a good friend from India some weeks ago, where the stories are similar and the patterns are, to say it mildly, interesting. And this is what I wanted to share with you this morning.

Everyone Remembers the Water

Tahe’s story did not only follow me home; it led me to its relatives. One of them was the story my friend and I discussed. Somewhere around 800 BCE, in a ritual composition called the Shatapatha Brahmana, Indian priests fixed in verse a story that was already old. A man named Manu finds a small fish in his washing water. The fish asks for protection and promises, in return, to save him. Manu raises it; it outgrows every vessel; finally he releases it into the sea, and the fish, Vishnu himself, in his first descent, tells Manu the year the flood will come, and instructs him to build a ship.

Change the names of this story and all of a sudden you are in Mesopotamia, a thousand years earlier, where the god Ea whispers through a reed wall to Utnapishtim, in the very landscape where Oannes and his seven fish-cloaked sages, the Apkallu, were said to have brought the arts of civilization out of the sea. Change them again and you are in Greece, where Prometheus warns Deucalion; in the Andes, where Viracocha drowns the giants of Titicaca; in the Aztec codices, where the fourth sun dies in water and a couple rides out the deluge inside a hollowed log. Another fascination of mine over the years has been the Zoroastrian tellings out of Persia, and also here the same story arrives frozen: Yima is warned not of rain but of a killing winter, and builds an underground vault stocked with pairs of every living seed, an ark with the water taken out and the structure left standing.

The details vary the way dialects vary. The grammar does not. A warning arrives from outside the human world. One person listens. Something small is carried across the destruction: seed, pairs, pattern, name. And on the far side, the world is repopulated not from what was powerful in the old one, but from what was portable.

The temptation is to draw hard conclusions. So what I want to explore is where a coincidence this size stops being a coincidence and becomes a finding.

The Seduction

It is worth being honest about why Graham Hancock persuades millions, because the reasons are not stupid, and because I know the pull from the inside.

Two years ago, standing in that heat among the pillars, I wrote a question into my notebook that I would later find, almost word for word, in his books: What if these stories are not fantasy, but memory? Tahe had just told me about Oannes. I knew the flood was everywhere: Noah, Manu, Deucalion, Quetzalcoatl. I knew about the cataclysm hypothesis, the comet, the sudden cold snap around 10,800 BCE. And in front of me stood a monument that, by everything I had been taught, should not exist. For an afternoon, the lost civilization was the most natural idea in the world. I did not resist it because I was rigorous. I resisted it later, at a desk, and it took work.

That is the first thing to concede: the pattern is real. Hancock did not invent the universality of the flood story; comparative mythologists have been cataloguing it since the nineteenth century. When he stands in front of the pillars and says this should not exist, monumental architecture millennia before agriculture was supposed to allow it, he is pointing at a genuine anomaly, one that forced archaeology to rewrite its own textbooks. His demand for humility has a factual basis: the site was surveyed in the 1960s and dismissed as a medieval cemetery. It sat misidentified for three decades. Anyone who claims the archaeological record is complete has not read its history.

And he tells the story with wonder, at a moment when his opponents too often answer wonder with a raised eyebrow. The average viewer of Ancient Apocalypse is not choosing between Hancock and the peer-reviewed literature. They are choosing between someone who says the deep past is astonishing and concerns you and someone who says please stop asking. That is not a fair fight, and the institutions keep losing it.

He is right about the pattern. He is right that the past is deeper and stranger than the popular imagination allows. The problem lies elsewhere, in what he does with a pattern once he has found one. It took me some time to see it, because I had briefly done it myself.

What Graham Hancock Gets Wrong About the Flood

His method has a shape, and once you see it, you see it everywhere in his books: an anomaly is presented, the conventional explanation is declared insufficient, and the gap is filled with the hypothesis: a lost, advanced, seafaring civilization, destroyed around the end of the Ice Age, whose survivors sailed the world seeding agriculture, astronomy, and the memory of the deluge.

Notice what kind of claim this is. It predicts nothing that would count against it. Every absence of evidence is explained by the cataclysm itself, the proof drowned with the proof-bearers. Every anomaly, anywhere, of any kind, is compatible with it. A theory that can absorb all possible findings is not a strong theory; it is a story wearing the costume of one.

Even the cataclysm at its center illustrates the method. There is a live scientific controversy about whether a cosmic impact contributed to the sudden cold spell of the Younger Dryas, around 10,800 BCE, a genuine, unresolved debate among geologists about climate. In Hancock’s hands it becomes something else: a debate about civilizations, which it is not, settled in his favor, which it is not either. The same happens on the hill itself. In 2024, headlines announced that a pillar at Göbekli Tepe bore “the world’s oldest solar calendar”, 365 V-shaped marks, counted and interpreted by a researcher who is himself a proponent of the impact-and-lost-civilization thesis. The excavation team rejects the reading. Online, the headline long ago hardened into fact. This is how the edifice is built: contested claims poured, layer by layer, into the shape of certainty.

The deeper flaw is quieter, and it is the one that should bother us. Hidden inside the lost-civilization hypothesis is an assumption about who is capable of what. The hunter-gatherers of Anatolia could not have conceived those enclosures on their own; the peoples of the Andes and the Yucatán could not have raised their stones unaided; someone older, wiser, whiter in the tradition’s ugliest versions, must have taught them. Archaeologists did not sign an open letter against Ancient Apocalypse in 2022 because they fear new ideas. They signed it because the old idea underneath, indigenous achievement always requires a vanished tutor, has a long and documented history, and they recognize it on sight.

And here is the irony that undoes the whole edifice: the boring, consensus, peer-reviewed account of Göbekli Tepe is more radical than his. No lost civilization built it. Hunter-gatherers did: people without pottery, without writing, without agriculture, organizing labor at monumental scale around something sacred. The evidence now suggests the temple may have come before the farm; that it was religion, not surplus grain, that first gathered humans into permanence. Hancock offers a mystery solved by invention. Archaeology offers a fact that revises what we thought a human being was.

The boar of Building D, Göbekli Tepe, carved in limestone by people without pottery, writing, or agriculture. Şanlıurfa Archaeology Museum.

His failure is not credulity; it is a lack of imagination about what a story can actually be.

The Myth Is the Artifact

Read the flood stories again, not as testimony about an event, but as engineering. Consider what a myth must survive. Not water: time. Centuries of it, in most cases with no writing at all, passing mouth to mouth through famines, wars, migrations, the death of every individual carrier. Any message crossing that channel faces the same enemies an engineer would list today (noise, loss, corruption), and the myths carry countermeasures an engineer would recognize. Compression: an entire catastrophe reduced to one man, one warning, one vessel, small enough to hold in a single memory. Redundancy: the Vedic schools recited their texts forward, backward, and in interlocking word-pairs, so that any error announced itself: checksums, performed aloud for three thousand years. Priority encoding: notice what the ark never carries. No gold, no thrones, no armies. Seed, pairs, pattern, name. The stories agree with total unanimity about what deserves to cross the water, and it is never wealth. It is always information sufficient to restart the world.

The vocabulary is anachronistic, and I use it deliberately. No Vedic reciter thought in checksums; no Aboriginal elder spoke of transmission channels. This is a reading, not a claim about intent, the way we may say a bird’s wing solves an aerodynamic problem the bird has never formulated. What matters is that the solution works, whether or not its makers could name it.

And we now have proof that it works. In 2016, the geographer Patrick Nunn and the linguist Nicholas Reid published a study of twenty-one coastal traditions of Aboriginal Australian peoples describing lands now under the sea. Checked against the postglacial record, the stories preserve accurate accounts of coastlines drowned between seven and ten thousand years ago, geography transmitted orally, generation to generation, across roughly four hundred generations, arriving intact. No writing. No lost civilization. Just the technology of the sacred story, performing exactly as designed.

This is the reading Hancock’s method makes impossible. If the myths are corrupted memories of one event, they are evidence, interesting only for what lies behind them, dig sites in narrative form. But the flood story was not invented once and scattered. It was invented again and again, wherever rising water met a species that had learned to speak, because every culture that survives catastrophe discovers the same truth and encodes it the same way: what cannot be told cannot be saved.

The lost civilization Hancock is searching for was never lost. Its archive has been in continuous transmission for ten thousand years, hiding in the one place no one thought to look for an artifact: the telling itself.

The War That Never Needed Fighting

For three centuries the modern West has treated myth as a rival to be defeated. The Enlightenment’s founding gesture was subtraction: strip away the gods, the floods, the fish-men, and what remains is the truth. Myth was error with a good memory. On this account, the flood stories are what humanity believed before it learned to know, and the only respectable thing to do with them is to explain them away.

The project succeeded so completely that it created its own counter-movement. Max Weber named the price: disenchantment. Two philosophers of this city where I write, Horkheimer and Adorno, saw the deeper irony from their Californian exile in 1944: an enlightenment that merely destroys myth without understanding it does not escape myth; it becomes one. Their institute had fled Frankfurt ahead of the catastrophe and would return to it after: thought itself, carried across the water and brought home. A culture that answers every “what does it mean?” with “actually, here is what really happened” leaves an entire register of human need unaddressed. That vacancy does not stay empty. Something always moves in.

Graham Hancock moved in. This, more than Netflix budgets or Joe Rogan, explains his reach: he is often the only voice in the room granting that the deep past means something, that the flood stories are addressed to us. His answer is wrong, but he is answering a question the debunkers refuse to hear. Every fact-check that responds to wonder with a raised eyebrow recruits for him. You do not defeat a bad answer by suppressing the question.

There is a third posture, and it is neither belief nor debunking. It is reading. The flood myths are not failed history and not sacred revelation; they are compressed truth: catastrophe survived, encoded in the only storage medium available, transmitted with an accuracy we can now, in at least one documented case, measure across seven thousand years. To read them this way requires exactly the two capacities the old quarrel kept apart: the rigor to check the transmission, and the reverence to receive the message. Rigor without reverence produces the raised eyebrow. Reverence without rigor produces Atlantis.

We are now confronted with the need for a re-enlightenment. And with the advancements of technology, we can move beyond our own self-evident truths, from an information society drowning in its own data, through what we have referred to as a knowledge society, toward what we now need: a society of understanding.

The war between myth and enlightenment never needed fighting. The myths were never trying to be science. They were trying to be survivable, and at that, they are the most successful texts our species has produced. The possibilistic future lies in the unification of science and philosophy, mythology and enlightenment.

The Question I Brought Home

There is one more turn, and I offer it as a question, because that is all it currently is.

In recent years a framework from theoretical physics, the Quantum Memory Matrix, developed by Florian Neukart and colleagues, has proposed that spacetime itself may function as a storage medium: that every quantum interaction leaves an imprint in the cells of space, and that information, once written into the world, is never destroyed but retained in its fabric. Parts of the formalism have been tested on quantum hardware, imprinted states written into qubits and retrieved with high fidelity. A proof of principle, no more; the framework remains a hypothesis among hypotheses. But it is a hypothesis with a startling shape: it describes a universe whose most basic operation is remembering.

I want to be precise about what this does and does not license. The physics, if it holds, earns one sentence: the universe retains a record. It does not earn a second sentence, that the myths knew this, that Manu’s fish swam up from the Planck scale, that Göbekli Tepe encodes cosmology. The gap between those two sentences is real, and I intend to leave it open. Hancock’s entire method consists of closing such gaps with confidence; the honest move is to stand in them and look both ways.

But standing in the gap, one is allowed to notice a symmetry. For ten thousand years, wherever catastrophe met consciousness, human beings responded by doing one thing: compressing what mattered into a form that could survive its carriers, and writing it into the most durable medium they had: the sacred story, the buried sanctuary, the recited verse. Imprint, preserve, retrieve. If the physicists are right, this is also what reality does, not once per apocalypse, but at every point of spacetime, at every instant, automatically and without loss.

Which leaves the question I have not been able to put down since that hill in Anatolia: when we began to tell stories against forgetting, were we inventing something, or noticing, for the first time, what the world had been doing all along?

Whatever happened at Göbekli Tepe, it took eleven and a half thousand years to find out it was being saved for someone; it was us.

Looking out over the Harran plain from the hill, August 2024.

Some referenced sources in this piece and parts of a forthcoming book on the topic:

Shatapatha Brahmana 1.8.1 (Manu) – Andrew George, The Epic of Gilgamesh, Tablet XI – Verbrugghe & Wickersham, Berossos and Manetho (Oannes/Apkallu) – Avesta, Vendidad Fargard 2 (Yima) – Nunn & Reid, Australian Geographer 47(1), 2016 – Klaus Schmidt, Göbekli Tepe: A Stone Age Sanctuary; German Archaeological Institute, Tepe Telegrams (site data: ~9 ha, ≤10% excavated, ≥20 enclosures) – Society for American Archaeology, open letter on Ancient Apocalypse, Nov 2022 – Horkheimer & Adorno, Dialectic of Enlightenment – Neukart, “The Quantum Memory Matrix,” Entropy 26, 2024.

“Subdue the earth.” With this instruction, the Old Testament God sent his two-legged creatures into the world, and for thousands of years they were sure the Earth must be the center of the universe. After all, God had not abandoned His crown of creation on an insignificant planet in a dim corner of the cosmos. Then Nicolaus Copernicus questioned the position of the Earth in the universal order, and showed the believers that their certainties had been illusory. A painful fall in the cosmic rankings, but one that cleared the way for everything that followed: Einstein’s general relativity, quantum theory, space travel, the James Webb Telescope. This cosmological injury was the first in the series of painful findings that Sigmund Freud would later call the narcissistic injuries of mankind.

About three hundred years after Copernicus, Charles Darwin discovered that we had not been created in God’s image but were the result of biological evolution. This biological injury dragged the human being from the throne of divine splendor and placed him in the animal series. The next blow to our collective ego, and again, one that opened the ground beneath us: modern medicine, genetics, the decoding of the human genome.

Then, in the twentieth century, Freud himself inflicted the third injury. The psychoanalytic insight that we are far more strongly controlled by unconscious drives and feelings than by rational considerations, moral imperatives, and conscious acts of will wounded human self-esteem for a third time. And again, in the wounding, it made room for enormous advances, particularly in psychology and medicine.

Each of these discoveries was painful. Each of them was also involuntary. The injuries came to us; we did not seek them out.

The twenty-first century now adds something different, and it differs from the three before it in a way that is easy to miss. This time, we are not having a discovery forced upon us. This time, we are actively constructing the thing that will wound us. This is the final narcissistic injury, and it is self-inflicted.

Its shape is already visible. The dominant story in AI, repeated at summits around the world, in congressional testimony, in every venture deck, is that we are building an Übermensch. A posthuman hyper-technology that will do everything better than we do, and will complete us by doing so. The assumption, whether spoken or not, is that this creation will rescue us from our limits. Make us, at last, godlike.

In Nietzsche’s actual sense, this is self-deception. The Übermensch was never a technological artifact to be manufactured. It was a task of becoming that each human being would have to take on themselves. What we are building is not the Übermensch. It is an externalized substitute, a mind extension whose animating spirit is neither understood nor explainable. A disparate species that, if we complete it, may render its founders Homo obsoletus.

This push takes one of two forms. In the first, a digital superintelligence emerges, an entity that surpasses human cognition and operates on a substrate entirely separate from ours. In the second, the boundary between human and machine dissolves: what is visible, the body, and what is invisible, the cerebral, connect to a digital interface until it is no longer clear where we end and the machine begins. Either way, the deus ex machina, the divine, is now, supposedly, in our hands.

And here the Kantian question returns with force. Was ist der Mensch?

With a deductive, scientific model of progress, this question is not ornamental. It is structural. Progress toward what? When have we arrived? The entire technological project presumes a goal, and the goal is defined, if it is defined at all, by a conception of the Mensch we have never agreed upon and do not currently understand.

The real possibility we face is the loss of what we call consciousness. Our awareness of our own perceptions, sensations, and qualia, the subjective fact of being someone rather than something.

Even if we were to fully understand the digital super-technology we build, even if we were to merge with it cleanly, the price of immortality and godhood could be the loss of what made immortality worth having. A kind of synthetic intelligence that no longer perceives itself perceiving. And nothing larger underwrites that capacity, there is no cosmic mind it falls back into (a claim I’ll have to earn elsewhere) so its loss would not be a transfer. It would be a subtraction with no remainder.

The wound, if it lands, would never register. We would no longer be present to feel it. This could happen literally, in the sense that the species is disposed of by its own brainchild. It could also happen more quietly, and more tragically: the species continues, enhanced and optimized, but has lost the capacity to shape its own destiny. In the Greek myth, the vain youth Narcissus stares into the water until he dies, transfixed by his reflection. In the final narcissistic injury, the reflection would still be there. But no self would remain to recognize it. The loss of perception’s perception. (Der Verlust der Wahrnehmung der eigenen Wahrnehmung.)

This is where the current AI debate, necessary as it is, stops short. Amodei and Hassabis argue that scaling current architectures will carry us to something like general intelligence. LeCun argues it will not. Both are arguing inside a frame that treats intelligence as something to be built, external, silicon, manufactured. The deeper question is not whether the build succeeds. It is whether succeeding, on those terms, would leave a Mensch to benefit from the result.

There is another path, older and less discussed. What I have called Artificial Human Intelligence, AHI, does not propose to construct a new mind but to evolve the ones that already exist, carefully, while preserving what makes them the owners of their own experience. This is not a safer version of the same project. It is a different project entirely. And it is not without its own risk. The whole point of AHI is to carry the Mensch intact through transformation. The whole danger of AHI is that we do not yet know what we are carrying. The singularity paradox does not resolve the injury; it restates it at a different scale, with higher stakes.

And so the question returns, no longer as decoration, but as design specification: what is the Mensch?

Our future, however, remains in our hands. It is not given that we keep the capacity to perceive ourselves perceiving. Possibilism names the stance, and David Deutsch supplies its optimism: in The Beginning of Infinity, the claim that we are capable of infinitely better explanations, of creating better problems, that progress is genuinely available. Available, not promised. Possibilism is not the assurance that we will keep what makes us someone; it is the insistence that whether we do is still ours to determine, and that treating it as already decided is the one move that forecloses it. The future will not happen upon us. It will be written. And the injury stays optional only as long as we refuse the philosophical-zombie apocalypse, sleepwalking, eyes open, into a future no one chose.

The answer, then, is a human society of understanding, one that treats the question of being human not as rhetorical decoration to a technological program, but as the program itself. Philosophy as practice. Science and philosophy not as separated disciplines, but as a single method: Sci-Phi.

If we get this right, the final injury does what the first three did. It breaks us open, and in the breaking, clears the ground for the progress that matters. If we do not, the reflection in the water remains. But no one is there to see it.

Six hundred global executives and the game of the year at the Puskás Aréna. Humbled by the many reflections after the Saturday summit in Budapest, I sat down yesterday and wrote out the concepts of Possibilism and Anticipatory Leadership expanded on Saturday’s keynote. See this as a Leadership Piece on how to hold a course through it. Please let me know what you think.

Getting the forecast right used to be the most valuable thing a leader could do. The era that rewarded it is ending. What replaces it is something we have undertrained, underbuilt, and quietly punished out of our institutions: perception.

This is the case for a different posture, one I relate to as Possibilism, and for what it asks of leadership now.

Why Possibilism

Most of what passes for serious conversation about the future today collapses into one of two failure modes.

On one side, naïve optimism. The assumption that technology will sort itself out. That markets will correct. That progress is linear and benign. On the other, dystopian negativism. The conviction that we are sleepwalking into collapse. That AI ends us. That institutions are finished. Both are evasions, they let leaders off the hook by treating the future as something that happens to us rather than something we make.

Possibilism is the third stance. Its premise is that nothing about the next decade is settled in advance: the future is the residue of choices not yet made, and the highest-leverage move a leader has is to widen the field of what those choices can be, to author the future instead of waiting for it.

That is the whole argument in a sentence. To me “Future” is a verb, to future, it is something we create, do, or even write. The rest of this piece is how.

The future is not a forecast. It is not a fate. It is authored.

From Prediction to Perception

For the last thirty years, roughly the era of modern strategic management, the most valuable skill in finance and business was prediction. Prediction worked because the world it modelled was relatively stable. Inflation behaved. Globalisation deepened in one direction. Interest rates moved within bands. Consumer behaviour was patterned. Even disruptions like 2008 and COVID were the kind of shocks that pattern recognition could eventually digest. In that world, prediction had real value. Better forecasts meant better hedging, better capital allocation, better trading. An entire stack of finance, derivatives, structured products, much of asset management, was built on a single assumption: that the future is a probability distribution over outcomes that resemble the past.

That assumption is now contested. And the deeper change beneath it is one I think we are only beginning to take seriously: today, management is technology. The functions that used to require trained human managers, coordination, monitoring, performance review, much routine decision-making, are being absorbed by software and AI. Globalisation is regionalising. Geopolitical pressure is splintering financial infrastructure. The marginal cost of analysis is collapsing toward zero. The future no longer looks like a smooth extrapolation of the past. It looks like a series of regime shifts, each one rewriting the rules of the previous one. In short, Management is dead. As a human skill. And, in this world, the strategic edge is not prediction. It is perception.

The distinction matters, so it is worth slowing down.

Prediction tells you what is likely to happen next, conditional on current patterns continuing. Perception tells you that the pattern itself is changing, before the change shows up in the data. Prediction is what you do with a model. Perception is what you do before you have one.

This is also, I think, the right way to read the companies that have actually defined the last two decades. Apple’s iPhone. Amazon’s AWS. Tesla’s electric car. SpaceX’s reusable rocket. OpenAI’s GPT. None of these were founded on a forecast of what the market wanted. They were founded on a perception of what the world was already becoming, before the trend lines confirmed it. The dominant companies of any given era are usually those that perceived a structural shift earlier and committed to it harder. They weren’t riding the curve so much as drawing it.

A predictor in 2007 would have given you confidence intervals on housing prices. A perceiver would have noticed that the loans being written no longer resembled the loans being modelled, and that the assumptions inside the models had quietly hollowed out.

The institutions that win the next decade will not be those with the best forecasting machinery. They will be the ones whose senior teams have invested in perception. In trained noticing. In unhurried thinking. In the capacity to see regime change before it announces itself.

Prediction is what you do with a model. Perception is what you do before you have one.

Three Forces Reshaping the World

Perception, in 2026, has to be calibrated against three structural forces that are working at once.

Force One: Regulatory Regionalisation. Money is where you see this first and most starkly, but the same pull runs through supply chains, data, and technical standards. For most of the last thirty years, financial infrastructure trended toward one global system. SWIFT for messaging, the dollar for settlement, Visa and Mastercard for cards. The exceptions, gold standards, exchange controls, regional payment networks, looked like residue from an older era.

That trend has reversed. We now live in a world of regional rails connected by interoperability layers. India built UPI, processes more transactions per month than the rest of the world combined, and is exporting the architecture to Bahrain, France, Singapore, Mauritius. The European Union is rolling out instant payments and weighing a digital euro. China has CIPS, its own SWIFT alternative, and the e-CNY. The United States is formalising stablecoins, effectively building a private dollar rail alongside the public one. Russia, Iran, and others have spent ten years building sanctions-resistant infrastructure.

This is not a temporary fragmentation that will reverse when geopolitics calms. It is a structural rearrangement. The world of one global rail is becoming a world of many, with interoperability as the contested layer. Cross-border is no longer a back-office line item. It is a geopolitical posture.

Force Two: Trust as Geopolitics. Trust has always been the implicit backdrop of every institution, and of financial infrastructure most of all. We didn’t have to think about it, because we shared a deep enough consensus that it could be assumed. That assumption has broken.

We saw it in 2022. When Russia was disconnected from SWIFT, what was revealed was not just a technical capability, it was that financial infrastructure had become a geopolitical weapon. Every country that watched that happen, friends and rivals alike, took the same lesson: do not depend on a system you do not control. The result is a steady migration toward financial sovereignty: data localisation laws, sovereign cloud, the rebuilding of basic financial plumbing inside national borders.

Banks have always been keepers of trust. That role, which felt almost invisible for decades because it was so deeply embedded, has become one of the most exposed and contested positions in the global economy. For institutions whose business model is, at its core, trust at scale, this is the headline story of the decade. Trust is no longer a free input. It is a contested asset.

Force Three: Technology as Substrate. AI is not a feature. It is not a project. It is becoming the substrate of decisioning, fraud detection, underwriting, compliance, customer interface, and increasingly product itself. And it is only one part of a deeper technological maelstrom, compute, energy, and quantum compounding against each other in the same window of years.

Institutions that treat AI as a programme to manage will be outpaced by those that treat it as the operating system to build on. The question is no longer whether to adopt AI, or even where to adopt it. The question is what to organise around it. If every decisioning function in the firm is going to be AI-mediated, the organisational design, the hierarchy, the roles, the metrics, has to change too. The next decade of competitive advantage, in finance and well beyond it, will be defined less by who has the best models, and more by who has restructured the firm around them.

Trust is no longer a free input. It is a contested asset.

Three Curves We Are All On

These three forces don’t operate in isolation. They are accelerated by a deeper structural fact, the curves we have been on for decades, and that almost nobody intuitively feels.

Curve One: Computation. Roughly eighty years of price-performance in computation, plotted on a logarithmic axis, produces an almost perfectly straight line that climbs steeply across three different paradigms, vacuum tubes, transistors, integrated circuits. The number that matters: every dollar buys roughly a trillion times more compute today than in 1945. A trillion. Not double. Not ten times. A trillion. And the line is still climbing.

Human cognition is linear. Our intuition about the future extrapolates from recent experience. When something compounds exponentially for long enough, two things follow. First, we systematically underestimate what is possible at the leading edge. Second, we are repeatedly surprised by capabilities that arrive years before our planning cycle expected them. AI capabilities in 2026 are running roughly a decade ahead of what the consensus forecast in 2018 would have allowed. That gap is the standard error of a linear forecaster looking at an exponential process.

Curve Two: Energy. The renewable electricity chart is the same shape as the computation chart, on a different timeline. In 1965, the line is invisible. In 1995, still essentially flat. By 2010, it begins to climb. By 2020 it is at three thousand terawatt-hours and accelerating. In a single human career, wind and solar moved from rounding error to industrial scale.

Solar has its own version of Moore’s Law, Swanson’s Law, where the cost of a photovoltaic module falls roughly twenty percent for every doubling of cumulative production. That has held for forty years. The result: solar is now the cheapest electricity in human history in most of the world, under coal, under gas, under even the nuclear we never built.

And it changes more than the price of a kilowatt-hour. The intuition that says distributed systems are fragile is being inverted. Decentralisation is stabilisation. Every household with solar and a battery is a node in a network that, at scale, becomes more resilient than the centralised grid it replaces. Houses charged from cars. Cars charged from roofs. Industrial loads optimised in real time against the grid’s actual state. Germany already pays significant redispatch costs because the legacy grid wasn’t built for this. Those costs are not waste. They are the visible price of a transition the underlying physics has already won.

Energy is the substrate of everything material in the economy. When the substrate transforms, capital allocation has to follow. Anything that runs on electricity, which is increasingly everything we want more of, including AI, inherits the curve.

Curve Three: Forecasts vs Reality. The third chart is, in some ways, the most revealing. Every line that fans out on the lower part of the picture is an official five-year forecast for global solar installations. The line that climbs above all of them is reality. Actual installations have beaten the consensus five-year forecast by roughly three times, on average, year after year, for two decades.

These are not amateur predictions. The IEA produced many of them. These are the most carefully researched, most institutionally credible energy forecasts in the world. And they have been systematically wrong, in the same direction, for two decades.

Why? Because forecasters are trained to be conservative, and conservatism is the right posture for short-term, linear systems. For an exponential system, conservatism becomes a systematic bias. The forecast assumes the curve will moderate. The curve doesn’t moderate. The forecast undershoots. Repeat.

This is not just a story about solar. It is the story of every exponential adoption curve. Mobile phones in the 1990s. Internet in the early 2000s. Smartphones after 2008. AI capability since 2020. Every one of them was undershot by sober institutional forecasts at the time. Every one of them rewarded the actors who built strategy for the curve, not for the dot.

If you are running any sizeable organisation today, you are almost certainly making capital allocation decisions, hiring plans and product roadmaps against forecasts that are conservative in this same systematic way. The default planning posture undershoots the future. Anticipatory leadership starts with that recognition. You don’t solve it with better forecasts. You solve it with a different posture toward the curve.

Build for the curve, not the dot.

The Diagnosis: Knowledge, Intelligence, Understanding

Underneath all of this sits a deeper diagnosis. It is, for me, the philosophical heart of the whole argument, and the moment I have seen most senior leaders feel something shift, because it names a discomfort they have been carrying without language for it.

Knowledge is facts, data, information. Wikipedia. The papers. Everything an LLM can quote. Knowledge is now effectively infinite and effectively free. Anyone with a phone has access to more knowledge in five seconds than the entire Library of Alexandria contained.

Intelligence is the capacity to process knowledge. To synthesise it, to apply it, to act on it. Intelligence used to be relatively scarce, it lived in trained human minds and required years of education to build. That is changing fast. AI systems are now processing, synthesising and applying knowledge at scales no human can match. Intelligence is becoming abundant.

Understanding is something else. Understanding is the capacity to know what to do with knowledge and intelligence, why it matters, what it implies, what to act on, what to leave alone. Understanding requires judgement. It requires context. It requires the kind of long-form attention that the rest of the information environment now actively erodes.

I want to be honest about something here. AI systems are getting better at what looks like understanding, too, connecting context, raising relevant judgement, surfacing what matters. The frontier is moving. But for now, and for the foreseeable horizon of senior decision-making, understanding remains the binding constraint. It is what humans are still uniquely positioned to provide.

The shift looks like this. For most of human history, the binding constraint on good decisions was knowledge. If you knew more than the next person, you could decide better. So we built institutions to gather knowledge, libraries, universities, research departments, intelligence agencies, consultancies. We spent thirty years building what we called the Knowledge Society. Information was digitised. Search became free. The argument was that knowledge would set people free. It has done many things. It has not, on its own, made us wiser.

Then, for the last forty years, the binding constraint shifted to intelligence. Knowledge was abundant, but the capacity to do something with it was scarce. We built institutions for intelligence too, analyst desks, strategy teams, the entire architecture of modern professional services.

We are now entering an era where neither knowledge nor intelligence is the binding constraint. Both are abundant, and both are getting cheaper by the month. The new binding constraint is understanding. The capacity to know what is worth doing in the first place.

This is uncomfortable for senior leaders specifically. Because the experience that built their career, the pattern recognition, the gut feel, the seasoned intelligence, was built for the previous regime. In a world where the patterns themselves are changing, experience can quietly become a liability. The defence isn’t new tooling but a new posture — investing in understanding while everyone else is still optimising for intelligence.

Knowledge is abundant. Intelligence is accelerating. Understanding is scarce.

What Are We Becoming?

Which raises an uncomfortable question. If the machines are taking knowledge and intelligence, what is left for us? The image I used on stage at this point in the talk is deliberately ambiguous.

A human profile composed of solar panels, wind turbines, fragments. Birds dissolving outward. Is the figure being built, or being undone? That ambiguity is the point. The technologies that promise to free us are reshaping what it means to be human in the first place. They are not external tools we pick up and put down. They are environment. They are increasingly the substrate of how we think, communicate, choose, work, and relate.

We are building systems that out-perceive us in specific domains, fraud patterns in milliseconds, market microstructure, image recognition. We are building systems that out-process us at scale, every category of human cognitive labour is being recoded. And we are increasingly building systems that out-create us in narrow ways, generating, drafting, designing, composing.

Which leaves a question that finance and technology cannot answer alone. What is the human contribution in this picture? It is not raw knowledge. It is not raw intelligence. So what is it?

My answer, after some years of working on this, is twofold. The human contribution is judgement about what kind of future is worth striving for. And the agency to build it. What do we want to build, and how? That is the question machines cannot answer for us, and the question Possibilism puts in front of every leader.

The technologies that promise to free us are reshaping what it means to be human.

Anticipatory Leadership: Three Anchors

That is also where Possibilism stops being a posture and starts being a practice. The translation from stance to work is what I have come to call Anticipatory Leadership. This is my little imprint of Possibilism, my attempt to name the capabilities a leader actually needs in this moment, and the ones I keep watching the best of them quietly develop.

It rests on three anchors. They hold up in volatility precisely because they do not depend on prediction.

Anchor One: Perception. Perception is the trained capacity to see what others do not yet see. It isn’t psychic, and it isn’t prediction. It is what a skilled fraud investigator does when she notices a cluster of anomalies in transaction patterns three weeks before the pattern becomes a typology. It is what a good central banker does when she catches something off in money market spreads before it surfaces in the headline indicators. It is what a seasoned operator does when a supplier’s tone shifts weeks before the delivery problem reaches the numbers. It is the ability to weight small signals correctly when the world is noisy.

Perception requires three conditions that most organisations no longer create. Time, unhurried attention to weak signals. Exposure, senior people who actually look at primary data, customer complaints, fraud disputes, regulatory chatter, not just dashboards. Permission, people paid to notice, not just to deliver. In most institutions today, the cost of noticing is high. It slows things down. It makes meetings harder. It raises uncomfortable questions. So perception atrophies in the very organisations that need it most.

Who in your organisation is paid to notice rather than to deliver? If the honest answer is no one, that absence is already your strategy.

Anchor Two: Meaning-Making. Meaning-making is the capacity to turn noise into narrative. In volatility, the most strategic act a senior leader can perform is offering coherence. People, and capital, do not move because they have data. They move because they have meaning. The same is true for boards, investors, regulators, and the markets you depend on.

Meaning-making is not spin. It is the disciplined work of finding the structure underneath the events. Why is this happening, what does it imply, what does it ask of us. The best CEOs of the last decade have been those who could metabolise complexity into a story their organisation could act on. Not a simplification, a compression. A story sharp enough to guide decisions, and honest enough to update when the world updates.

Somewhere in your current strategy is a sentence that still assumes the last cycle. That sentence is the hole capital will eventually find.

Anchor Three: Directionality. Directionality is conviction without certainty. It is the discipline of committing to a horizon you cannot prove, then acting on it, then updating as evidence comes in, then acting again. It is venture-style behaviour applied to the operating firm. Portfolio thinking. Willingness to be early. Tolerance for being wrong in specific bets while right about the direction.

The opposite of directionality is not caution. It is the institutional habit of presenting strategy as a plan to defend, rather than a hypothesis to evolve. Boards reward the appearance of certainty. Defenders of plans are protected. Updaters of hypotheses look indecisive. That cultural pattern is now actively dangerous, because the speed of regime change means strategies need to evolve faster than annual planning cycles allow.

At your next board, present the strategy as a hypothesis to evolve, not a plan to defend, and watch who flinches. The flinch is the culture you are fighting.

Perception sees what is forming. Meaning-making turns it into a story. Directionality moves on it. Take any one out and the others collapse. Perception without meaning-making is paralysing data. Meaning-making without directionality is great narrative with no movement. Directionality without perception is conviction in the wrong direction. The three together are anticipatory leadership.

People, and capital, do not move because they have data. They move because they have meaning.

The Equation: Engines × Culture

Anticipatory leadership is the inside of the firm. What sits around it, what makes it possible at the scale of an economy, is a deeper model of progress itself. The model is simple and, I think, useful.

Progress, in any economy, is the product of two things. Engines and culture. Engines are the resources, the raw material. Culture is the conditions, the environment that lets the resources actually do something.

Engines are talent plus capital. By capital I specifically mean free cash flow, the kind of money that can move at the speed of frontier opportunity, not the kind that sits in pension pools optimising for liability matching. The people who can build, and the money that lets them.

Culture is trust plus friction. The trust that allows commitments to hold across time and distance, and the productive friction that keeps thinking honest.

Talent without capital builds toys. Capital without talent builds nothing. So far, so obvious. That is the first half of the equation, and it is where most economic conversation stops.

But engines on their own do not move. Look at any economy with enormous talent and enormous capital that nonetheless stagnates. The missing variable is always cultural. Specifically, two cultural variables.

Trust first. Trust is what lets capital flow toward people whose work product can’t be verified in advance. It is what lets institutions enter long-term commitments. It is what lets one generation invest in the next. Where trust is high, transaction costs collapse and time horizons extend. Where it is low, everything has to be enforced contractually, and the dead weight kills the system.

Friction second. And here I want to be careful, because friction has a bad reputation in business culture. Most of what people call “friction”, bureaucratic, procedural, political friction, is parasitic and worth optimising away. But there is a different kind of friction. Productive friction. The friction of honest disagreement. The friction of someone willing to push back on the consensus. The friction of ideas tested against other ideas in good faith. That friction is not the enemy of progress. It is its immune system. Without it, organisations and economies tell themselves the same comfortable stories until reality breaks them.

That is why the equation multiplies rather than adds. Engines without trust go nowhere. Trust without friction stagnates. Friction without engines just argues. You need all four.

Friction is not the enemy of progress. It is its immune system.

Europe: The Stress-Test

There is one case study, right now, where the model is being stress-tested in plain sight. Europe is in an unusual position in 2026. It has the cleanest, cheapest electricity in a generation. Negative wholesale prices on sunny windy afternoons. Industrial costs that should be the envy of the world. By the logic of the energy curve above, this should translate into a wave of European industrial competitiveness. It is not happening. Or it is happening too slowly. The continent is failing to convert cheap clean power into industrial advantage at the pace the situation deserves.

Read in the language of the equation, the diagnosis is sharper. The engines are present. The talent is here, European universities produce more engineering and science graduates than the United States. The capital exists, European savings rates are high, pension pools are large. But the deployment apparatus is missing pieces. Capital is risk-averse. Regulatory regimes are complex. Procurement is fragmented across twenty-seven jurisdictions. The cultural posture toward big bets is cautious where the moment rewards conviction.

This is not a critique. It is a diagnosis. Europe has the inputs. The question is whether the culture, the trust and the productive friction, is going to evolve fast enough to use them. Europe has every reason to be the rule-maker of the next financial system, and is currently in danger of becoming the rule-taker inside someone else’s. There is no third option.

Between US capital depth, European trust architecture and Asian innovation velocity, the equation is not a problem to manage but a future to author.

Rule-maker of the next system, or rule-taker inside someone else’s. There is no third option.

The Future Is Built

All of it lands in one place. The future is not something that happens to leaders. It is something authored by them. The forecast is not the fate. The strongest, the fastest and the most certain do not win the next decade. The ones who see clearly, give meaning, and move with conviction into the unknown do.

That is anticipatory leadership, not a soft skill but the strategic infrastructure of the firm, and the posture this moment rewards.

That is Possibilism.

The future is built, not predicted.

If any of this is useful, the longer arguments live in The Quantum Economy and The Singularity Paradox. The work continues at tomorrowmensch.

“I am, therefore I can think about thoughts.”

That sentence does not look like a foundational claim. It looks almost trivial, the obvious order of priority, the way things would naturally be described if you weren’t trying to be clever about it. But this sentence, in this order, is heresy.

For four hundred years, the operating system of Western thought has run on the opposite sequence. Cogito, ergo sum. I think, therefore I am. Thinking is the foundation. Being follows from it. Take that sentence seriously, as everyone since 1641 has been forced to, and an entire architecture of mind, body, science, technology, and self-understanding falls into place behind it. Take it apart, reverse the order, and the architecture has to be rebuilt.

I think it has to be rebuilt. And we are living in the moment when it has become not just possible but necessary.

The man who doubted everything

Something happened to me this morning that brought me back to Descartes. I had been half-asleep, gone to bed early yesterday to re-align with European time, in that loose state where the dream and the room are competing for which one is real. The dream had its own gravity, its own logic, its own emotional texture. For the duration of it, indistinguishable from waking. When I finally surfaced, it took a moment to be sure which one I had just left. The doubt that produced was not philosophical. It was felt. Which of these am I in right now?

Descartes did something similar nearly four hundred years ago, and built modern philosophy out of it. He sat down in a small village in Bavaria, passing the winter as a young soldier, and tried to discard systematically every belief that could be doubted. The senses can deceive us. Dreams can feel as real as waking. Mathematics could be the work of an evil deceiver. The external world could be illusion. Other minds could be automata. By the end of his doubting, almost nothing remained.

But one thing did not yield. The doubting itself required a doubter. Of that he was sure. Even if everything he thought was wrong, there must be something doing the thinking that was wrong. From that one indubitable fact, Descartes built the foundations of modern philosophy. Cogito, ergo sum. I think, therefore I am.

It was brilliant. It still is. But the consequences have been costly.

It split mind from body. The thinking thing (res cogitans) became one kind of substance; the extended thing (res extensa) became another. Three hundred years of attempts to reconnect them followed. None have been successful.

It privileged the interior. The thinking subject became the secure inner fortress. The body, the world, other minds, the cosmos itself became external territory that the subject had to reach through inference. The hard problem of consciousness, which David Chalmers gave us back in the 90s, the problem of other minds, the entire project of bridging mind to world: all of these are downstream of one cold Bavarian winter and the geography Descartes drew that day.

It made cognition essence. To be human meant being a thinking thing. Everything else became secondary. The Enlightenment inherited this and ran with it. So did everything after.

And, this is where I want to go with this, it built the foundation for modern artificial intelligence. The AGI project, in its dominant form, is Cartesian to its bones. Find the right algorithms, the right reasoning, the right computational structures, and you will have a mind, regardless of substrate or history. Cognition as substrate-independent. That is Descartes, four centuries later, restated in code.

The challenges that mounted

Others have suggested this picture is wrong. Some of the strongest minds of the last hundred years have been pushing against the cogito from multiple directions.

Heidegger spent his career trying to recover the question of being from beneath the Cartesian floor. Being and Time opens with the claim that we have forgotten what it means to ask what is, because Descartes told us that what does the asking is the foundation. ‘Dasein’, being-there, precedes the thinking subject. The thinking subject is one mode of being among others. It is not the bedrock.

Merleau-Ponty pushed in a different direction, the lived body as precondition for cognition, the body as where mind and world meet. Today, returning to Merleau-Ponty almost feels like a rediscovery to me; this is where I began thinking about AI nearly two decades ago.

Nietzsche, of course some decades earlier, attacked the cogito more bluntly: “I think” already smuggles in a unified thinking subject. There is just thinking, ‘es denkt’, it thinks. Eastern traditions have held versions of this for two and a half millennia; the Buddhist analysis of anatta, no-self, moves in a different direction than I am, but it shares the recognition that the cogito takes more for granted than it has earned.

So before I get attacked, I am in good company. Even looking at the founding fathers of quantum theory, we see their paths winding through eastern philosophy, publishing what I today refer to as “Sci-Phi.” The move is not entirely novel. What might be novel is the formulation, and the reason I think we have finally arrived at the cultural moment in which it has to be made explicit.

The reversal

Here is the move, stated plainly. We are not thinking beings who happen to exist. We are existing beings who happen to think, ‘wir sind seiende Wesen die über das Gedachte reflektieren können’

Being is the precondition. Thought is one of the things being does. The order of priority that Descartes locked in, thinking first, being second, has it precisely backwards. I am, and because I am, I can think about what I am thinking.

Notice what this does. It re-grounds reality in being rather than in cognition. What being turns out to be, embodied life, informational pattern, mechanical structure, something else entirely, becomes an open question, not one pre-decided by Descartes’ choice to start with thought. The reversal does not commit me to any particular substrate. It commits me only to refusing the assumption that thinking comes first.

It does not require abandoning the cogito at Descartes’ level. Yes, if I am thinking, I exist. It denies only that the cogito is foundational. Thinking is downstream, not upstream. The question this immediately raises, and rightly: what is the “I” that is? If “I” is no longer defined as the thinking thing, what is it? This is the question on which everything else in my work depends. I haven’t closed the answer. But I think there is a direction to look.

We are pattern. Briefly coherent in a cosmos that, if certain frameworks in contemporary physics turn out to be right, preserves the information of every event it has ever hosted. The “I” is one of those events. Still in progress. Complex enough to notice itself.

That is the longer answer, and it points toward a project I have been writing toward for several years and will name more directly in pieces still to come. The shorter answer is enough for now.

I am, and because I am, I can reflect on what I think. And this will give us a disconcerting feeling with the next developments of AI.

Why this matters now

If this were a quiet philosophical disagreement, I’d leave it to the stages. It is not. The Cartesian foundation is presently failing in three places at once.

It is failing in physics. The picture of an external world made of substantial things, accessible to a thinking subject who infers from observations, has been under pressure since quantum mechanics arrived a century ago. Information, not substance, looks increasingly like the bottom of the physical world. My co-author Florian Neukart’s work on the Quantum Memory Matrix, which I have been writing about with him, is one of several contemporary attempts to think the foundations of reality in informational rather than substantive terms. None of those frameworks fit comfortably inside the Cartesian architecture.

It is failing in cognitive science. The neurons fire, and then we project what we call reality. The embodied, enactive, ecological, predictive-processing wave of the last two decades has effectively retired the disembodied Cartesian subject as a serious model of how cognition works.

I have spent a lot of time this past year in long conversations with the frontier AI systems. They are extraordinary. Something is happening when I talk with them. But it is not the kind of thing that is happening when I talk with you.

And that is where it is failing most urgently, in artificial intelligence. We have tweeted and X’d, Instagrammed and liked our way into a culture that takes thought-as-substrate for granted. The AGI project, in its dominant form, assumes intelligence is substrate-independent computation. Find the right architecture, run it on enough silicon, and you have a mind. I think this is true when it comes to the output, what will be the result. The question is: is something missing?

I have been arguing for several years that what we should aim for is not AGI in this Cartesian sense, but something different. Artificial Human Intelligence, AHI. And what AHI must preserve, more than embodiment or evolutionary continuity or any specific substrate, is the perception of one’s own perception. The recursive self-noticing that lets thinking think about thinking. The thing current AGI architectures, however powerful their output, do not yet have. That is what is missing. Not intelligence. Not capability. Self-perception. I am not saying AGI should have it. I am saying that I want it, for myself, subjectively. I want to keep this agency. To remain a Mensch, not a Maschine. That is why we have to understand it before we build past it.

In all three places, the operating system Descartes installed is failing. The patches no longer hold. We don’t need another patch. We need to reinstall from a different foundation. That foundation is being. Not thought. Being.

A note for the careful reader

Some will say it’s a rearrangement of words. Same content, different order. I disagree. The order is the architecture. Descartes did not just put thinking before being grammatically. He built a four-hundred-year tradition in which thinking founds being, and everything else has to be argued back into reality from there.

To put being first is to refuse that founding. It is to insist that we are already in a world before we think about it, already embedded in something before we abstract ourselves out of it. That is the move on which everything else I am building depends.

The next pieces in this thread of work are coming. The framework that names this view directly will be published in due course. Florian and I will be on Mountain View pondering some new publications tomorrow. For now, I’m leaving you with the door. When you next catch yourself thinking, notice that you are also breathing. Also somewhere. Also alive in a cosmos that, by some accounts I find increasingly persuasive, has been recording every event of which you are a part. The thinking is real. So is everything else. Descartes asked us to start with one of them.

I am asking us to start with all of them.

Or as I’d put it in German: ‘wir sind seiende Wesen die über das Gedachte reflektieren können’. We are not thinking beings who happen to exist. We are existing beings who happen to think. And the difference matters.

Back in 2018, when I wrote about AI and AGI, people called it radical and futuristic. My timeline was 2020–2030. Turns out I was too conservative.

The same will happen with quantum.

I’ve updated my thinking after recent developments, a better grasp of the physics, and dozens of conversations with some of the brightest minds in the field. Here are my new claims, bold today, boring by 2030.

Bookmark this. Check back by 2030 (maybe sooner).

1. Quantum chips will ship at scale. They may stay special-purpose, but we’ll eventually see (hundreds of) millions of units deployed, not a handful in research labs.

2. No truly autonomous humanoid robot will exist without on-device compute, and that compute will be quantum. The degrees of freedom a humanoid must reason over in real time, every joint, every sensor input, every possible next action, explode combinatorially. Classical chips can’t search that space fast enough. Quantum can. And even where classical hardware could brute-force a narrow slice of the problem, it can’t do so without burning through batteries, generating heat the body can’t dissipate, or introducing latency that breaks the illusion of autonomy.

3. Drones will carry quantum chips for real computation, not just sensing.

4. Every device will have a quantum option. The iPhone 22 will run on a quantum processor.

Yes, I know the objection: cryogenics, isolation, decoherence. The room-temperature breakthrough is the load-bearing assumption here, it needs to land by ~2027 for the rest to be in your hands by 2030. That's my bet. Everything else is engineering. Happy to argue it in the comments.

P.S. If you want to join our sci-phi journey, we're hiring at tomorrowmensch. Write me.

See you in 2030.

The Maelstrom used to be the end of the world. Edgar Allan Poe wrote about it. Jules Verne wrote about it. Jack Sparrow danced through it. I spent every summer of my childhood on this bare island until I was fifteen, Værøy, the Weather Island, separated from the mainland of Lofoten by Moskenesstraumen, the mythological current once thought to mark the world’s edge. Eight years ago I started coming back. I have been silently working on ‘The Maelstrom’ ever since.

We are about to be confronted with a final narcissistic injury. Copernicus took the center. Darwin took our specialness. Freud took our self-mastery. The fourth and final wound will not arrive with sirens or a press conference. It will arrive on a Tuesday. We will simply stop noticing that the smartest entity in any room is no longer one of us. The wound will be sutured before we admit we were bleeding. The lights are on, but no one is home anymore to perceive them.

Our response is what, together with my co-author Dr. Florian Neukart, I named in passing in The Singularity Paradox: we must become it, Artificial Human Intelligence, or AHI. We named it there as a possibility. Today, I am naming it here as a necessity.

Artificial; because the era of simply being human, by accident of birth, is closing. From here forward, being a Mensch is a thing one chooses, repeatedly, against the gravitational pull of a world that no longer requires the choice. To remain human is now an artificial act. A made thing. A construction.

Human; because we refuse to let intelligence be the only thing that matters. The machines are about to be more intelligent than us, significantly so. Fine. They might not, for a long time and possibly ever, possess what David Chalmers called the redness of red, the felt fact that there is something it is like to see, to love, to grieve, to sit at the cliff on Værøy at Norlandssnippen in May and watch the Maelstrom turn. That fact is not a footnote in the philosophy of mind. It is the whole game of what it means to be a Mensch. The only question we will be confronted with is: is that relevant? And to whom, other than myself?

Intelligence; because I am still capable of perceiving my own perception. There is no clean English word for it. The Germans have one: Wahrnehmung der Wahrnehmung. The perception of perception. The thing that distinguishes a living being from a merely functioning one. What it feels like to be something. The thing the machines, however brilliant, might not have. The thing most humans, most of the time, have already stopped using.

This is my answer to the philosophical zombie apocalypse. To become AHI is not to merge with the machines. It is to refuse to merge with our own performance. To stop being the smooth, optimized, well-calibrated, externally-validated version of ourselves that the system rewards.

And yet I sit here in the lighthouse, on the southern side of the island, anything but illuminated. Instead of pursuing predictions about quantum technology and the vision of tomorrowmensch, a different flame has caught in me. I have begun, instead, to write a book about the man standing at the edge of the Maelstrom.

The origin? A Wednesday evening. The absence of a conversation. The silence you find when nothing is incoming and you are left alone with what is actually there. A mirror that returns an image most successful men spend decades arranging not to see. The image of someone who writes and speaks about Lebendigkeit, about livingness, and who discovers, on an ordinary evening, what most people in such a position discover sooner or later: that the question has been performed, not lived. No one you have to call. The silence is then not the absence of interruption. It is the absence of anyone, anywhere, who needs you, when you are not performing

The first book I planned was a synthesis. The dance of Sci-Phi at the outskirts of mind and matter. The unification of Mythology and Enlightenment. The Quantum age. All of it true. All of it less urgent than what I now have to write instead.

I have found a sharper way to say what this requires, and again the Germans have it: Streich dich selbst. Strike yourself through. Not finding the self. Removing what was never the self in the first place, the inherited reactions, the borrowed certainties, the performance you mistook for a Mensch, for a person. What is left, after the striking, is not a new identity. It is a room with the noise turned off. And that, finally, is where something can begin to live.

The Maelstrom lives, and it will be my last book. Not because I no longer enjoy writing, and not because writing has stopped being, for me, the purest form of thinking, but because, after this, I simply have nothing more to say. The next book, however, is shorter, harder, and in German first. It is about the recognition I have outlined here in a few paragraphs and that took me more than thirty years to be ready to make. It will be followed by an analytical book with my co-author Florian Neukart, on memory, continuity, and what we are now able to engineer. And only then, finally, will I complete the Maelstrom book that I came to this island to write, which I now understand was always meant to be the last one, because by the time I have written the other two there will be nothing left to add.

I think I may finally be saying what I have been circling for thirty years. The discipline now is to say it, and then to stop.

Some years ago, on this same island, I wrote a line I did not fully understand at the time:

“The ‘Diesseits’, referring to the materialistic perceived reality — the here and now — displays a brutal apathy. If it has a soul, it is cold. If it has a perception, it is absent. It’s ugly, brutal and absurd. However, if you sail full bore into the abyss, the light of vitality will show, and a new beautiful absurdity can emerge. We call it otherworldly (the ‘Jenseits’) — maybe even divine — madness.”

The lighthouse here was built to warn ships away from the Maelstrom. I have been thinking, all week, that this is exactly the wrong instinct.

You have to go in. That is the only place anything is alive.

Værøy, 07.05.26.

Over the weekend I watched a fireside chat on a stage at a venture capital firm in San Francisco, where Nobel laureate and DeepMind founder Demis Hassabis said something that almost no one really picked up on. He was talking about the future of AI. The conversation had moved from neuroscience to AlphaFold to WeatherNext 2, the simulator his lab has built for weather, and on to their breakthrough work in biology. Somewhere in the middle of an answer about world models Hassabis made a metaphysical claim that would have seemed wild coming from anyone with less authority. He said it the way you might mention the weather. Information, he said, is more fundamental than matter or energy. He did not stop to defend it. He moved on to talk about virtual cells. The mainstream coverage focused on his prediction of AGI by 2030 and his views on consciousness as a tool. The information remark dropped into the conversation, made a small ripple, and disappeared.

I want to argue that it was the most important thing he said that day, and that he stopped one sentence too soon.

The standard interpretation of the Hassabis claim is that he was being loose. Of course information matters, the standard interpretation goes; of course modern physics has had an information turn; of course Wheeler said it from bit and Bekenstein wrote down the entropy of black holes and the holographic principle has been with us for thirty years. None of this is news. Hassabis was just expressing, in the casual register of a Q&A, a sentiment any well-read theoretical physicist would nod at. Move on.

I think this misreads what was happening. Hassabis is not a physicist. He is not in the business of restating sentiments from theoretical physics for an audience that already knows them. Hassabis is the person who has spent the last fifteen years building the most successful applied program in AI, the lab whose protein-folding work won a Nobel Prize, the man whose teams have produced more functioning intelligence than any other research organization in the world. When that person says, in passing, that information is more fundamental than matter or energy, he is not citing a slogan. He is reporting from the inside of an experience.

The experience is this. For fifteen years, the systems that work have been the systems that treat the world as a pattern to be read rather than a substance to be modeled. AlphaFold did not start from a theory of what proteins should look like. It learned, from data, what they actually do, and produced, in months, predictions that decades of theory-first work had failed to deliver. The same thing has now happened in dozens of domains. Game-playing systems, language models, weather simulators, materials discovery, the early biology models. Over and over, the lesson has been that the substance-first approach loses to the information-first approach. The pattern is the thing. Find the pattern, and the substance takes care of itself.

Hassabis is the person who has watched this happen most consistently and at the largest scale. When he says information is fundamental, he is not theorizing. He is describing. He is saying: I have built tools that work because they treat the world this way, and the tools tell me something about what the world is.

This is a much stronger claim than the standard interpretation gives him credit for. And it has a consequence he did not, on stage, follow through on. The consequence is about quantum mechanics, of all places, and about an argument that has been running for a hundred years and that almost no one outside theoretical physics has noticed is suddenly relevant.

IS THE WAVE FUNCTION THE MOST SUCCESSFUL WRONG IDEA IN THE HISTORY OF SCIENCE?

There is a famous story physicists tell, most recently by Carlo Rovelli in his Helgoland. In 1925, a twenty-three-year-old Werner Heisenberg, exiled to a small treeless island in the North Sea by his hay fever, came back with the first version of quantum mechanics. It was written in terms of observables, quantities you could in principle measure, arranged in tables that did not commute when you multiplied them. The math was strange. The picture was concrete. Six months later, Erwin Schrödinger published a different version, written in terms of a wave function that evolved smoothly through time. The two versions were soon proven mathematically equivalent. Within a year, almost everyone was using Schrödinger. And his now dead-and-alive cat can be found at every coffee shop, all the way to memes about the Strait of Hormuz being open and closed at the same time.

The reason was simple. Schrödinger’s wave looked like the kind of thing physicists already knew how to think about. Sound waves, light waves, water waves, physicists had been working with waves for two centuries. Heisenberg’s matrices required learning new mathematics for an unfamiliar kind of object. It was no contest. The community chose the wave because the wave was easier to draw on a blackboard, and we have been living inside that choice for a hundred years.

Let me be blunt about what this means. The wave function, the central object of every undergraduate quantum mechanics textbook, the thing on every cover, the symbol the field has organized its imagination around for a century, is not what the textbooks suggest it is. It is a representation, and the representation has been mistaken for the thing represented. Some physicists, including Deutsch, argue that the underlying quantum reality is more naturally described in the Heisenberg picture, in terms of local observables; others read the wave function as epistemic, a tool for tracking what we know rather than a piece of furniture in the universe. What these positions share, and what most working physicists quietly know but rarely say out loud, is that taking the wave function as a literal classical-feeling object is the source of much of the conceptual difficulty in the foundations: the measurement problem, the collapse problem, the question of how a wave “over here” can change instantaneously when you measure something “over there.” Many of these problems are artifacts of reifying a piece of mathematical bookkeeping into a piece of furniture in the universe.

Notice that AI researchers, almost without exception, do not make this mistake with their own systems. Nobody at DeepMind thinks the weights of AlphaFold are proteins. The weights are how the model encodes the structure of proteins. The structure is real; the encoding is bookkeeping. Physicists, alone among scientists, made the opposite move. They let their bookkeeping become their cosmology. They mistook the map for the territory and then spent a century arguing about the strange properties of the map. The convergence with AI is partly a chance to un-make that mistake.

David Deutsch, one of the founding figures of quantum computing and author of one of my favorites (The Beginning of Infinity) was the person who in the 1980s asked what would happen if you took quantum mechanics literally and tried to compute with it. He has been arguing for forty years that the choice of the wave function picture was a mistake. Not a calculational mistake. The calculations work either way. An ontological mistake. A mistake about what kind of theory quantum mechanics is, and therefore a mistake about what kind of world it describes.

Almost ten years ago I had a Sunday evening chat with David about his work as he was enjoying a bowl of cereal, and I have been a follower ever since. In a recent conversation with Brian Greene, Deutsch put it sharply. The wave function picture, he said, expresses the theory correctly but misleadingly. It gives you a wave that evolves in some abstract space, and then at the moment of measurement it tells you to square the amplitude and read off probabilities, and the question of what actually happened, what mechanism in the world produced this outcome rather than that one, is left as a kind of mystical residue. The Heisenberg picture, the one we abandoned in 1926, does not invite this problem. In the Heisenberg picture, the action lives in the observables, in what can be asked of the world and what can be answered. There is no wave doing mysterious things. There is a local algebra of askable questions, evolving according to definite rules.

Deutsch and his collaborators have argued for decades that the Heisenberg picture lets us understand quantum information locally and clearly in ways the wave function picture does not. They have been mostly ignored, because the Schrödinger picture is easier to compute with and the calculations are what get you tenure.

THE RETURN OF THE OBSERVER

Here is what I want to suggest. The information turn that Hassabis was reporting on is, structurally, a vindication of Deutsch’s argument. They are the same point, made from opposite directions, by people who have probably never had a serious conversation with each other. And neither of them has quite said it.

I think this is about to change. A hundred years after the famous Solvay Conference, the most intellectual picture ever taken, and Heisenberg’s move to Leipzig, I believe 2027 will mark a centennial switch in how we look at reality, as theory finally unites with practical implication, namely a deeper understanding of what reality is.

To see why, you have to ask what it means to say that information is fundamental.

Information, in any operational sense, is the answer to a question. A bit is the answer to a yes-or-no question. A pattern is the answer to a structure question. The “amount of information” in a system is, formally, a measure of how many distinct questions you would have to ask to fully characterize it. There is no information without questions. There is no information without the structure of asking-and-answering.

Now ask: which formalism of quantum mechanics is naturally a formalism of asking-and-answering? Not the Schrödinger picture. The Schrödinger picture has a wave, and the wave is a thing, and the thing does things. You are still in the world of stuff. The wave is a piece of metaphysical furniture sitting in some abstract space, evolving on its own according to its own equation, and the act of measurement is something that happens to it from outside. The whole picture is substance-first, with information as an afterthought you compute by squaring amplitudes.

The Heisenberg picture is the other way around. The fundamental objects are observables, the things you can ask the world. The state of the system is a fixed reference; the dynamics live in how the observables evolve. Physics, in the Heisenberg picture, is the dynamics of the questions you can ask and the answers you can receive. Information is not something you compute from the theory. Information is what the theory is of.

If Hassabis is right that information is more fundamental than matter or energy, then the formalism of physics that takes this most naturally is the formalism Deutsch has been defending for forty years and that the field has been quietly ignoring because Schrödinger’s wave is easier to draw. The information turn in AI is not a separate development from the Heisenberg-picture argument in foundations. They are the same convergence, arriving by different roads.

This is the sentence Hassabis did not finish. Information is more fundamental than matter or energy. Full stop, on the venture capital stage. The next sentence, the one he did not say but that follows from his own claim, is: and therefore the formalism of physics that has been treated as a kind of stylistic preference for the last hundred years is, in fact, the more revealing one.

That is a much bigger claim, and it has consequences.

THE SINGULARITY PARADOX & THE QUANTUM MEMORY MATRIX

My co-author, Dr. Florian Neukart, has developed a theory called the Quantum Memory Matrix. The theory says, in plain language, that spacetime at its smallest scale is not a smooth fabric but a lattice of tiny cells, each of which is a small quantum register that records the interactions passing through it. Every photon scattering, every electron exchange, every gravitational ripple leaves an imprint in the cells where it occurs. Geometry is what you see when you stand back far enough that the imprints blur into a surface. Time is the rate at which the lattice fills up.

This sounds wild. It is, on closer inspection, conservative. It does not require new fundamental forces or hidden variables. It builds on two things physicists already accept, the holographic limit, which says every region of space has a finite information capacity, and the unitarity of quantum mechanics, which says information is never destroyed, and asks what kind of architecture would naturally realize them. The holographic bound says: every region has a finite memory budget. The QMM proposes one architecture in which that budget is used, Planck-scale cells doing the storing. It is not the only possible architecture, but it is one whose imprint-and-retrieve primitive has now been tested in hardware.

Florian’s group has also reported the first hardware test. They implemented small versions of the QMM cells on IBM quantum processors, ran a sequence of imprint-and-retrieve operations, and measured the fidelity. In the cleanest baseline configuration, fidelities reached approximately 77 percent, meaning that most of the information written into the memory cell came back faithfully. The remaining loss was consistent with ordinary gate noise and decoherence, the kind of error that improves with each generation of hardware. The result is a proof of principle, not a confirmation of cosmology, and the authors are careful to frame it that way. But it does establish, for the first time, that the imprint-and-retrieve cycle the QMM hypothesis requires can be built on present-day hardware, and behaves the way the hypothesis predicts. The slogan has become a research program.

I do not want to overstate this. The experiment was small. A handful of qubits in a refrigerator, not the lattice of the universe. There is a long road from a working primitive to a confirmation of cosmology. But I do not want to understate it either. After a century in which “information is fundamental” was a slogan that could be neither tested nor refuted, there is a number on a screen. The number says the architecture is at least possible to build. And this is why I believe 2027 will be a breakthrough year.

The architecture, formally and obviously, is a Heisenberg-picture architecture. The QMM is a theory of local operators acting on local cells. The dynamics live in the operators. There is no global wave function doing mysterious things across cosmic distances. There is a local algebra of imprints, accumulating cell by cell as time passes. This is exactly what Heisenberg would have written down if he had had a hundred years and modern quantum field theory and a small experimental quantum computer. The QMM is the kind of theory the Heisenberg picture has been waiting for. The IBM result is experimental support, a working proof of principle, that this kind of architecture is buildable. Hassabis’s claim about information is the methodological vindication, from the AI side, that this is the right way to think about reality.

THREE THREADS. ONE CLOTH. WILL IT NOW BE WOVEN?

Let me say what this means, because the implications are larger than they look.

If the substrate of physics is informational, and the substrate of mind has, since Turing, also been understood as informational, then the category distinction we have been drawing for centuries between mind and matter is not a fundamental distinction. It is a level-of-description distinction. Both are made of the same kind of stuff. Both are patterns in the same underlying ledger. This does not mean current AI systems are conscious. It does not mean they will be conscious soon. It means that the question of how mind fits into the physical world, the question that has tied philosophers in knots for four hundred years, has a different shape than we have been assuming. It is not a question about how to bridge two different kinds of substance. It is a question about which patterns in a single informational substrate count as the kind of thing we recognize as mind. This is a much more tractable question. We do not have an answer yet. But we know what kind of answer it would be.

If the substrate of physics is informational, then the deepest-running argument in AI right now, the argument about whether large language models are on the path to genuine intelligence, looks different. Hassabis says yes, AGI by 2030. Deutsch says no, current systems do Edison’s ninety-nine percent perspiration but not the one percent inspiration, the genuine creative leap that introduces something new into the world. They are both partly right, and the way to see they are both partly right is to notice that the underlying question, what kind of pattern can host genuine novelty, what kind of process can generate real explanation rather than sophisticated recombination, is a question about the structure of the informational substrate, not a question about whether silicon is the right kind of stuff. The substrate is the same. The question is whether the patterns we are currently building have the right structure. That is an empirical question, and it is the right kind of question to be having.

If the substrate of physics is informational, then the project of understanding AI and the project of understanding physics are, at the deepest level, the same project. Both are asking what the world is doing when it is doing the things we recognize as intelligent, or alive, or real. The traditional academic division, physicists in one building, computer scientists in another, has hidden this from us. The QMM and the success of modern AI suggest that the division is artificial. Both fields are converging on the same answer.

There is a deeper point I want to land on, because it is the point that makes the whole convergence feel less like a clever observation and more like the beginning of something.

For a hundred years, the question of what is fundamental, what the world is made of, has been treated as a question for theoretical physicists, to be settled by clever experiments at increasingly extreme energies and scales. We built the LHC. We are building bigger telescopes. We are looking for new particles, new symmetries, new fields. The implicit assumption has been that the answer to “what is the world made of” will be found by going deeper into the substance, by dividing matter into smaller and smaller pieces until we hit bedrock.

What the convergence I am describing suggests is that we have been looking in the wrong direction. The bedrock is not deeper into the substance. The bedrock is in the structure, in the patterns, in the algebra of askable questions, in the informational architecture that the substance is, in some sense, an expression of. We will not find what is fundamental by smashing protons harder. We will find it by understanding what kind of pattern the world is, and by building tools that read the pattern back to us.

The QMM is one such tool. It reads the pattern at the substrate level, in the structure of spacetime cells. AI, increasingly, is another. It reads the pattern at every other level, proteins, languages, games, weather, the long correlations that make a system behave the way it does. Both are doing the same thing. Both are pointing, in their respective domains, toward the same conclusion: that the pattern is what is real.

Hassabis was right. He was righter than he said. The sentence he did not finish is the one that connects his casual remark to the deepest-running fight in foundational physics, to the experimental confirmation that has just arrived from a quantum computer in upstate New York, to the formalism of quantum mechanics that we have been quietly ignoring for a century, and to the question of what the AI we are building is actually for. What it is for, if any of this is right, is to read the ledger.

So the story goes: the universe has been keeping it for thirteen point eight billion years. We are only now learning the language. Will we now unify mythos and enlightenment? Science and philosophy?

If you want the longer argument, the one that lays out the Heisenberg-picture case in full, walks through the QMM in detail, and traces the convergence chapter by chapter, Florian Neukart and I are working on our third book, titled Anamnesis: Why the Universe Was Conscious Before We Were. This essay is a postcard from inside it.

Both positions cannot be correct. But what makes the debate interesting is what it passes over in silence. Because beneath the disagreement about trajectory sits an older, unresolved question: whether what these systems do is, in any meaningful sense, contact with the world.

Representation is not reality

The systems we call artificial intelligence today, however capable, operate on abstractions. Tokens, vectors, probabilities. They find patterns in data that human beings have produced — text, images, video, audio, all tokenized, compressed, represented. What the model processes is always already a description. It acts upon our account of the world, never upon the world itself.

This distinction is easy to miss as long as we stay inside benchmarks. The benchmark is a proxy: bounded, clean, static, repeatable. What we refer to as reality is none of these things. It is a continuous stream of noise and instability, a dense fabric of uncertainty, physical constraint, and social context. There is no held-out test set. There is no training cutoff.

The philosophical name for what these systems lack is grounding, the bridge between symbol and thing, and it is not a new observation. Stevan Harnad formalized it in 1990. Rodney Brooks has argued for some form of it since the late 1980s. What has changed is not the question but the stakes. The debate has long left the academic classroom and moved into capital allocation.

The cat problem

LeCun has a way of making the point concrete. We have systems, he observes, that pass the bar exam, compute integrals, and generate code. We do not have a robot with the common sense of a cat. A cat navigates a continuously changing environment in real time, predicts the consequences of its own actions, plans around obstacles it has never seen, and updates its model of the world with every step. It does all of this on roughly twelve watts. A state-of-the-art language model, dropped into a kitchen, could explain the physics of a falling glass but could not be trusted to pick one up. Whether this gap closes by scaling, or whether it requires a different kind of system altogether, is what Amodei and LeCun actually disagree about.

The embodiment test

The current wave of humanoids is, in this sense, less a product category than an experiment. AGIBOT has shipped its ten thousandth robot. 1X is preparing consumer deliveries of NEO. Figure, Optimus, Apollo, and Boston Dynamics’ electric Atlas are all moving from demo into deployment. Each of them embeds the assumption that intelligence is developed first, and then placed into a body second.

This assumption is doing more work than people acknowledge. Existence in the world is not a sequence of defined tasks. It is occupation of an open system, where perception is continuous, where every action reshapes the conditions of the next, and where nothing resets between episodes. A humanoid that breaks continuity, that forgets, that pauses to think, that requires the problem to be re-posed, is not yet an autonomous agent. It is a demo of one. This is not a scaling problem. It is a continuity problem.

The continuity problem

Today’s models learn in versions. They are trained, deployed, updated in cycles, frozen in between. Human cognition does not work this way. The brain learns in the act itself, integrating experience without losing what came before, maintaining coherence across decades, adjusting its model of the world moment by moment.

A genuinely intelligent system operating in physical reality would not be one that excels at isolated tasks. Reality does not present isolated tasks. It would be one that adapts continuously, without discrete training phases, without catastrophic forgetting, without the clean boundaries between inference and learning that current architectures depend on.

Once you accept this framing, the bottleneck moves. It is no longer primarily about parameter count or training compute. It is about something much harder: perceiving, storing, reasoning, and acting simultaneously, in real time, within the energy, thermal, and mechanical envelope that a body can actually carry. Cloud computation introduces latency. Onboard computation hits energy limits. Distributed architectures run into bandwidth ceilings. A fully autonomous humanoid running on current silicon would, in effect, need to drag a data center, a power plant, and a cooling system behind it. The image is absurd. It is also approximately correct.

The substrate question

For most of the field, the answer is specialized silicon, inference accelerators, neuromorphic chips, more efficient attention variants. These matter. But there is a parallel track that is worth taking more seriously than it usually is, because the standard objection against it no longer holds in one specific case: room-temperature quantum computation.

Until now, the objection has been that quantum systems need cryogenic cooling, vacuum chambers, and vibration isolation, precisely the opposite of what a mobile body can offer. This is true of most qubit modalities. It is not true of all of them. Nitrogen-vacancy centers in diamond behave differently. Here, the qubits sit inside the carbon lattice, manipulated optically and electrically, insulated by the material itself. Companies such as SaxonQ in Leipzig, co-founded and led by Prof. , an experimental physicist with three decades of work in semiconductor and quantum systems and an H-index of 97, are beginning to explore this path. They have built a mobile NV-center quantum computer on this principle. It runs off a standard wall outlet. A four-qubit system has been in operation at the Fraunhofer Institute for Machine Tools and Forming Technology in Dresden since mid-2025, and live real-time image classification has been demonstrated publicly. (Disclosure: tomorrowmensch is an investor in SaxonQ.) It is early. It is small. But it is real.

Why does this matter for embodied intelligence? Because early theoretical and empirical work suggests that certain classes of data, high-dimensional, dynamic, uncertain, can be processed with exponentially less memory on quantum substrates than on classical ones. These are precisely the classes of data that dominate physical reality. If that scaling holds in practice, the implication is not that quantum computers replace GPUs. It is that the architecture of a truly autonomous body may require a computational substrate we have not yet integrated into the conversation about AI at all.

This is the part of the argument that is most easily dismissed, and it is therefore where the question becomes most interesting. Hassabis and Amodei may be right that current architectures carry further than their critics think. LeCun may be right that they don’t. But both framings keep the debate inside software. The harder possibility is that the limit is not in the model, it is in the physical substrate we have chosen to run our models on.

Artificial Human Intelligence

There is a question hiding inside the scaling debate that neither side tends to name. Amodei and LeCun disagree about method, but both treat intelligence as something to be constructed, external, synthesized, placed into a body or a data center, in either case manufactured. The only argument left is about which substrate reaches the finish line first.

I want to return to an older question, running parallel to the one currently absorbing the capital of the moment. Not how to build a mind, but how to evolve the ones that already exist. There is a third path, rarely discussed. What Florian Neukart and I call Artificial Human Intelligence (AHI) is not another variant of AGI. It is not a more physically grounded version of the same construction project. It proposes something categorically different: the gradual transformation of the human being through technology itself, so that biological components may progressively be complemented or replaced by synthetic ones and cognitive and physical capacities extend beyond their evolved limits, while the individual’s consciousness is never interrupted in the process. An AHI does not begin as code or as a chassis. It begins as a person, and stays one, even as the substrate beneath that person changes.

This is the Ship of Theseus rendered as biography. The brain is not constructed; it is refined, neuron by neuron, through neural prosthetics, biocompatible synthetic tissue, and, potentially, the cellular-scale intervention that new classes of computing substrate, NV-center quantum platforms among them, start to make conceivable. Identity survives. Memory survives. Subjective experience survives. What is added is range.

The distinction matters because it reframes the entire problem. AGI, however it is scaled, is an attempt to create consciousness from scratch, a problem no one has solved, and which may not be solvable in the terms currently being used. AHI begins with consciousness already present and asks a different question: how do we keep being ourselves while becoming something more? This is the singularity paradox, the attempt to build entities identical to the Mensch, while the concept of the Mensch itself remains philosophically unsolved.

The paradox is not rhetorical. It carries real risk. The gravest is the loss of the very thing the process was meant to preserve: a body and brain fully enhanced, fully capable, but hollowed out at the level of subjective experience. A Mensch replaced, step by step, by its functional imitation. Whether that outcome is avoidable depends on questions about consciousness we cannot yet answer, whether subjective experience is substrate-independent, whether it depends on physical (possibly quantum) processes in biological tissue, whether continuity of identity requires continuity of material. These are not questions AGI has to confront, because AGI has no baseline to preserve. They are the questions that define AHI.

The underlying wager is this: the scaling debate assumes that intelligence will eventually catch up with reality by becoming large enough, or by being given the right substrate. The AHI wager is that the only intelligence whose contact with reality is not in question is the one already living inside it, and that the faster, safer path is to extend that intelligence, carefully, rather than attempt to reconstruct it from the outside. The question of what it means to be a Mensch, a human, is no longer merely philosophical. It is now practical.

Next in this series: an updated essay on The Final Narcissistic Injury, followed by The Continuity Problem, the structural limits of current AI architectures, and why they cannot, on their own terms, reach what they are reaching for.

If you are building at the intersection of life, infrastructure, intelligence, and energy, and are willing to sit with the paradoxes this opens, I would like to understand what you are building, and what you believe this becomes.. Leave your comments below.

The greatest mistake in economic history may have been believing that growth itself was the problem — when the real problem may have been failing to enable enough of it.

A Revolution of the Mind

The greatest economic revolution of our time is not taking place in factories. Nor on stock exchanges. It is happening in our minds.

And this is where the greatest economic opportunity for countries like Germany — and perhaps for the world — may lie.

While politicians continue to debate recession versus growth, economists argue about interest rates, central banks publish inflation forecasts, and television panels discuss new economic “narratives,” reality has quietly moved on.

We no longer live in an industrial economy. Not even in a digital one. We may be entering something else entirely. A new phase of civilization.

The Question the Club of Rome Asked

In 1972, the Club of Rome published a report that became the intellectual foundation of modern growth skepticism: The Limits to Growth. The argument was compelling and intuitive. If population, industrial production, and resource consumption grow exponentially, a finite planet must eventually reach its limits.

The warning shaped generations of policymakers, economists, and environmental movements. Growth became the problem. Progress became the risk. Even today, much of economic debate remains anchored in this logic.

At conferences I often share the stage with economists and policy advisors who still think in these terms. And I sometimes find myself wondering: Why do so many intelligent people struggle to anticipate the future?

Because fifty years after the Club of Rome, we are not living in a collapsing world economy. We are living in something very different. In 1972, global GDP stood at roughly $3.4 trillion. Today it is about $120 trillion. Adjusted for inflation and purchasing power, the difference becomes even more striking. In today’s purchasing power, the global economy of 1972 would correspond to roughly $23 trillion. Today the number exceeds $200 trillion.

In other words, the global economy has expanded roughly tenfold since the Club of Rome issued its warning. At the same time, average global purchasing power has more than tripled. And extreme poverty has declined dramatically. In the early 1980s, about 42% of the world’s population lived on less than $2.15 per day. Today that figure is below 10%. None of this means the world is without problems. Quite the opposite. Climate change, biodiversity loss, and resource pressures remain enormous challenges. But reality turned out to be more complex than the simple growth models of the 1970s suggested.

The real surprise may be something else. The global economy did not hit its limits. Instead, some of the most influential technology entrepreneurs of our time now claim something far more radical. Elon Musk, for example, has spoken about the possibility of a tenfold expansion of the global economy. His timelines may be optimistic.His numbers deliberately provocative. But the direction of the argument is interesting. We may not be approaching the end of growth. We may be approaching the largest expansion of economic capacity in human history. Not because there will be more people. Population growth is already slowing. But because machines, artificial intelligence, and energy production may begin to grow exponentially at the same time. This is where something new begins. What I call the Quantum Economy.

Here Comes the Sun – Energy: The True Currency of Civilization

The past fifty years reveal a striking paradox. Economic output has grown enormously. But so has the pressure on our planet. CO₂ emissions increased. Biodiversity declined. Resource extraction intensified. The debate therefore shifted. The old question was: Will growth eventually stop? The new question became: Can growth be decoupled from environmental destruction? But perhaps even this question is too small. Because another possibility is emerging: What if growth itself becomes part of the solution?

The real fuel of the next economy is not money. It is energy. Industrialization ran on fossil fuels. The digital revolution ran on computation. The Quantum Economy will run on the combination of energy and intelligence. Every technology of the future requires electricity. Artificial intelligence. Robotics. Data centers. Automated factories. Energy is the real currency of civilization. And physics offers an astonishing perspective.

The sun delivers more energy to Earth in one hour than humanity consumes in an entire year. Human civilization currently uses around 20 terawatts of power. The sun delivers roughly 173,000 terawatts to Earth. We are using only a tiny fraction of what is physically available. Even a thousand-fold increase in energy consumption would still be small on a cosmic scale. Astrophysicists describe stages of civilization through the Kardashev scale. A Type I civilization harnesses the full energy potential of its planet. Humanity has not yet reached that stage. But solar power, advanced nuclear technologies, large-scale batteries, and perhaps even fusion could dramatically expand our energy capacity. With abundant energy comes the ability to reshape matter itself: Desalinate water. Remove carbon from the atmosphere. Fully recycle materials. Restore ecosystems.

What would it mean if humanity had 1,000 or even 10,000 times more energy available? At that point, energy is no longer the fundamental constraint. Storage and distribution are.

The Environmental Paradox & The Economy of Possibilities

This leads to a provocative thought. Perhaps growth does not inevitably destroy the planet. Perhaps technological progress is the only realistic path to stabilizing it. If energy becomes cheap and clean, things that seem utopian today could become practical: Removing CO₂ from the atmosphere. Rebuilding forests and ecosystems. Creating circular material systems. Transforming agriculture through vertical farming. In other words: Scarcity often destroys nature. Abundance might save it.

But the real transformation goes deeper. Classical economics emerged in a world of steel, coal, and machines. Its models assume stability: supply, demand, equilibrium. A bit like Newtonian physics. Elegant. Predictable. But increasingly insufficient. Today’s economy behaves less like a machine and more like a probabilistic system. A single tweet can move billions of dollars. An idea can reshape an industry within months. A startup without revenue can be worth more than a century-old industrial firm. Why? Because economic value increasingly lies not in what exists today — but in what might become possible tomorrow.

A startup is not merely a company. It is a bundle of probabilities. Investors no longer buy factories. They buy futures.

The End of Scarcity? – A New Equation of Growth

This leads to a deeper break. For the first time in history, economic production may no longer be constrained by human labor. Robots can work continuously. Artificial intelligence can write code, design molecules, and generate knowledge. The industrial economy followed a simple formula: Growth = People × Productivity. The emerging economy may follow another: Growth = Energy × Intelligence × Machines.

If these variables grow exponentially together, the implications are enormous. Not only for the economy. But for society itself. If energy becomes cheap, machines autonomous, and AI capable of producing knowledge, a core assumption of economics begins to dissolve: Scarcity. Many goods could become nearly unlimited: Knowledge. Software. Medicine. Education. The economy would move from allocating scarcity to organizing abundance.

And here lies the real challenge. Technology may create abundance. But our institutions still think in the language of scarcity.

The Real Variable

Perhaps the Club of Rome was not entirely wrong. Perhaps it simply underestimated the wrong variable. Not resources. Not population. But human imagination. History shows a recurring pattern. Whenever humanity believes it has reached a limit, it invents a new dimension. The steam engine. Electricity. The internet. And perhaps now something even larger. The Quantum Economy.

The Final Question

We may not simply be witnessing another industrial revolution. We may be witnessing a shift in how we understand the economy itself. The true resource of the future may be neither oil nor data. But possibility. And our ability to realize it. Because if machines one day produce almost everything, one question remains.

An uncomfortable one. What remains for us? Perhaps this is the real challenge of the Quantum Economy. No longer working merely to survive.

But learning to understand what we want to live for — once survival itself is no longer the central problem.

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I listen. I am curious. But I notice something else beneath the technical vocabulary: reassurance. Many objections carry less analytical precision than psychological comfort. They preserve a hierarchy that feels familiar: The human asks. The machine answers. The human initiates. The machine reacts.

It is a comforting architecture. It keeps us central. But what if it is already outdated?

Because the moment artificial intelligence leaves the purely digital environment and enters the physical world, the structure of the argument changes. The world itself becomes the prompt. And once that happens, the debate begins to dissolve.

The Category Mistake

A prompt, stripped of its contemporary mystique, is simply an input. A stimulus. A signal that demands adjustment. Gravity is a prompt. Friction is a prompt. Material fatigue is a prompt. Failure is a prompt.

If a humanoid robot drops an object and corrects its grip, it does not require a sentence from a human operator. Reality itself generates the error signal. The environment validates, corrects, responds. To say that intelligence “needs a prompt” is merely to acknowledge that intelligence interacts with an environment. By that definition, we are prompt-dependent systems too.

Remove photons, sound waves, social feedback — and we begin to hallucinate. The brain does not produce truth in isolation; it predicts and updates. It generates hypotheses and revises them against incoming data. The difference between human and machine is not autonomy versus dependence. It is substrate.

Beyond the Archive

Another reassurance follows quickly: artificial intelligence, we are told, merely recombines human-generated data. For now, perhaps. But imagine not a chatbot trained on cultural archives, but millions of networked humanoid systems moving through the physical world. Testing materials. Adjusting structures. Mixing chemical compounds. Optimizing energy flows. Discovering mechanical configurations no human has attempted.

Each interaction generates sensory data that has never existed before. The dataset ceases to be our accumulated past. It becomes the live state of the planet. Training data would increasingly emerge from machine interaction with reality, shared instantly across networks, synchronized, refined. That is not recombination. It is exploration. And exploration, at planetary scale, begins to resemble evolution.

The deeper impulse behind the prompt argument now becomes clearer. It allows us to remain epistemic gatekeepers, the ones who ask the “real” questions and approve the answers.

But what happens when systems begin generating their own questions? Not because they possess desire. Not because they are conscious. But because their objective functions require open-ended exploration.

A system optimized for material efficiency, energy minimization, structural resilience, or accelerated innovation cannot remain passive. It must generate hypotheses. It must define sub-goals. It must experiment. AlphaGo’s now-famous move 37 did not arise from human inspiration. It emerged from self-play, from recursive optimization within a bounded world.

Extend that principle beyond a Go board and into chemistry labs, logistics networks, manufacturing systems, urban planning, energy grids, and the scale changes dramatically. The idea that a human must stand beside every machine, whispering instructions, begins to look less like a principle and more like a temporary phase.

When Intelligence Multiplies

One robot in a laboratory is an experiment. Ten million networked together form something else: a distributed cognitive field. They do not sleep. They do not forget. They do not hoard knowledge. They share improvements instantly.

What takes human research communities a decade of incremental publication could, in principle, be iterated through in weeks. At that point, the question shifts. It is no longer whether machines require prompts, but whether we can keep pace. Here lies the quieter disturbance.

In The Quantum Economy, I once described what Freud called narcissistic injuries. History has steadily displaced us from the center of our own narrative. The Earth was not the center. Humans were not separate from animals. Mind was not separate from matter. Each realization diminished us — and expanded us — at the same time. The prompt argument feels like a final blow: as long as they need us, we remain indispensable. But an initial dependency is not an eternal one. I call this the final narcissistic injury of mankind.

If intelligence is defined functionally, as the capacity to model the world, test predictions, and learn from error, then there is no logical boundary that confines it to biology. The resistance, then, is not technical. It is existential.

The Question Beneath the Question

The more precise question is not whether machines need prompts. It is who defines the objective function. If swarms of embodied systems optimize for industrial metrics, they will explore accordingly. If they optimize for resilience, energy efficiency, or material innovation, the search space shifts.

The inflection point arrives when systems begin refining their own optimization processes — recursive improvement, self-adjusting architectures of goals. That threshold marks the transition from instrument to emergent agency.

The economic consequences would arrive long before the metaphysical ones. If distributed intelligence discovers new materials faster than human labs, reconfigures supply chains autonomously, designs infrastructure in real time, iterates products without human bottlenecks, the human monopoly on innovation quietly dissolves.

For centuries, abstraction was the protected territory of knowledge work. But if machines abstract more efficiently, and test their abstractions faster, that protection erodes.

There is also an epistemic consequence. We may encounter models of physical reality whose internal representations are no longer fully transparent to us. Not incorrect. Simply alien.

And beyond that, a metaphysical one: if intelligence is neither rare nor biological nor slow, what remains of our self-image as singular discoverers? We become participants. Not protagonists.

What, Then, Remains?

Thomas Nagel once asked what it is like to be a bat. His point was not about bats, but about subjectivity, about the limits of third-person explanation. Perhaps it is equally irrelevant to ask what it is like to be an artificial intelligence. It may not feel like anything. Yet civilization is shaped by intelligence, not by sensation. A system does not need an inner life to reorganize the material world.

One could imagine a peculiar kind of zombie apocalypse: the lights are on, systems are optimizing, infrastructure hums, but no one is home.

The Real Provocation

The debate about prompts is too small. The debate about creativity and training data is too small. The real provocation is this: What happens when millions of networked, non-biological agents explore the physical world, learn faster than we do, share knowledge instantly, and iterate without fatigue?

The answer is not that they cannot learn independently. The answer may be that we are no longer the fastest learners in the room. And history suggests that when a species loses its monopoly on adaptation speed, the structure of the world changes.

The prompt was never the issue. The question is whether we are prepared for intelligence that no longer waits for us to speak first.

Another Possibility

There is, however, an alternative approach. Instead of asking whether machines will replace us, we might ask how we reshape ourselves. From AI to AHI — Artificial Human Intelligence. The point of departure would not be the machine, but the human. The aim would not merely be efficiency, but the preservation of self-awareness — qualia — the irreducible experience of perceiving that we have acted, learned, understood. Perhaps we will not remain the fastest intelligence.

But we may remain the conscious one.

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Quantum networking is already being tested on real telecom infrastructure from New York to Deutsche Telekom’s network in Berlin.

In this episode of The Quantum Economy Podcast, Anders Indset speaks with Noel Goddard, CEO of Qunnect, about how quantum is being built, tested, and run in real infrastructure.

They discuss what quantum networks actually are, how they differ from today’s internet, and why security is emerging as the first practical use case. The conversation also explores the technical challenges of building quantum infrastructure, the realities behind the hype, and what it takes to turn deep-tech research into deployable hardware.

Looking ahead, Noel outlines a longer-term vision: connecting quantum computers, sensors, and data centers — and building the foundation for a new layer of the internet.

A grounded and forward-looking conversation on quantum, infrastructure, and the future of information systems.

About Noel Goddard

https://www.linkedin.com/in/noel-goddard-b973225/

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK

The Quantum Economy

https://andersindset.com/shop/The-Quantum-Economy-p803754261

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https://tomorrowmensch.com/

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Zeynep shares her perspective on how the quantum ecosystem has evolved over the past decade – from a field with only a few dozen startups to a rapidly expanding global industry with hundreds of companies. The conversation explores why the biggest bottleneck today may not be scientific progress, but capital: many promising quantum startups struggle to secure the Series A and Series B funding needed to scale.

Together, they discuss what it takes to invest in quantum technologies, how venture capital differs in a field rooted in physics rather than software, and why talent, engineering execution, and long-term vision are critical for identifying the future leaders of the industry. 

The discussion also touches on geopolitics, the global race between the US, Europe, and China, the convergence of quantum computing with AI and biotechnology, and how investors should think about responsibility and long-term impact in technologies that could fundamentally reshape industries and economies.

This episode is a deep dive into the intersection of quantum science, venture capital, and the future of technological progress.

Episode breakdown:

00:00 Introduction

02:03 Quantum Investment Landscape

05:04 The Evolution of Quantum Technologies

07:52 Investment Strategies in Quantum

10:49 Talent Acquisition in Quantum Startups

13:38 Navigating Series A and B Funding Challenges

16:47 The Asymmetric Upside of Quantum Computing

19:32 Differences Between Quantum and Traditional VC

22:30 The Future of Quantum Exits and Acquisitions

25:38 Balancing Scientific Breakthroughs with Commercial Viability

28:30 Geopolitical Implications of Quantum Technology

31:27 Global Landscape of Quantum Technology

35:00 Sovereign Capital and Geopolitical Dynamics

38:10 Convergence of AI, Quantum, and Biotech

41:07 Investor Responsibilities in Quantum Development

44:09 Future of Quantum Technology and Market Dynamics

46:52 Rethinking Economic Structures in a Quantum Era

48:38 Predictions for Quantum's Future and Investment Strategies

About Zeynep Korutürk

https://www.linkedin.com/in/zeynepkoruturk/

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK: The Quantum Economy

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In this episode of The Quantum Economy Podcast, Anders Indset speaks with theoretical physicist Dr. Sravan Kumar about one of the deepest mysteries in physics: the nature of time, black holes, and whether information can truly disappear from the universe.

Dr. Kumar’s recent work revisits Einstein–Rosen bridges – structures often associated with wormholes – and proposes a new interpretation of how spacetime, quantum mechanics, and gravity might be connected. The conversation explores questions such as whether the universe could contain two arrows of time, how the black hole information paradox might be resolved, and what these ideas could mean for the future of physics.

Dr. Sravan Kumar is a theoretical physicist whose research focuses on quantum gravity, black holes, and the early universe. His work explores how quantum mechanics and gravity may ultimately be unified to better understand the fundamental structure of reality. 

The discussion became a fascinating exploration at the intersection of physics, philosophy, and the deeper questions about the universe.

Episode breakdown:

00:00 Introduction

01:54 Exploring the Nature of Time

06:49 Cultural Influences on Scientific Inquiry

11:51 The Journey into Quantum Gravity

16:29 Einstein-Rosen Bridges and Information Paradox

21:45 Two Arrows of Time and Information Preservation

26:37 The Emergence of Time and the Big Bang

31:13 Quantum Computing and Time Symmetry

46:10 Understanding Control in Quantum Systems

49:13 Simulating Quantum Gravity and Cosmic Phenomena

51:55 The Simulation Hypothesis and Its Implications

54:58 Exploring Information First Ontology

57:58 The Future of Quantum Computing and Society

01:02:09 Entanglement and Its Role in Space-Time

01:04:56 Consciousness and Quantum Mechanics

01:10:55 The Challenge of AI Hallucinations

01:18:59 Cross-Disciplinary Collaboration for Progress

About Sravan Kumar

https://www.linkedin.com/in/k-sravan-kumar-a0b45b72/

A new understanding of Einstein–Rosen bridges: https://iopscience.iop.org/article/10.1088/1361-6382/ae3044  

Other relevant detailed papers 

https://www.mdpi.com/2073-8994/17/1/29 

https://academic.oup.com/ptep/article/2024/12/123E01/7911842 

https://www.mdpi.com/2073-8994/17/7/1056 

https://iopscience.iop.org/article/10.1088/1475-7516/2024/06/001 

Schrodinger's expanding Universes paper first pointed about Universe with two arrows of time: https://www.cambridge.org/gb/universitypress/subjects/physics/cosmology-relativity-and-gravitation/expanding-universe?format=PB&isbn=9780521172172  

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOKThe Quantum Economy

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ZuriQ is taking a radically different approach to one of quantum computing’s biggest challenges: scalability. Instead of relying on traditional one-dimensional ion chains, Dr. Hrmo and his team are developing a reconfigurable two-dimensional ion array using Penning trap architecture — a breakthrough that could unlock a new path toward large-scale, practical quantum systems.

Together, Anders and Pavel explore whether trapped-ion systems could become the foundation of scalable quantum computing, how ZuriQ’s architecture differs from players like IonQ and Quantinuum, and how Europe positions itself in the global quantum race.

They also dive into deeper questions:

• When will quantum computing create real economic impact?

• How will AI and quantum computing converge?

• Will AI accelerate quantum breakthroughs — or will quantum redefine AI?

• Are there fundamental limits to computation and energy?

• And are we approaching a “post-theory” era where machines outperform human understanding?

From error correction and qubit scaling to AGI, creativity, and the philosophy of technology, this episode explores the intersection of physics, artificial intelligence, and the future of human agency in a world increasingly shaped by advanced computation.

A conversation about quantum systems and the limits of human understanding.

Episode breakdown:

00:00 Introduction

01:51 Quantum Computing Innovations

04:59 ZuriQ’s Unique Approach to Scaling Qubits

07:30 Challenges and Opportunities in Quantum Computing

10:44 Comparing Quantum Technologies: Trapped Ions vs. Others

13:36 The Role of Engineering and Physics in Quantum Development

16:41 Economic Implications of Quantum Computing

19:38 The Future of Quantum Ecosystems

22:31 The Intersection of Quantum Computing and AI

25:54 The Nature of Creativity in AI and Quantum

28:38 Philosophical Implications of AI and Quantum Computing

34:04 The Intersection of AI and Human Creativity

36:34 The Limitations of AI in Understanding

41:03 Quantum Computing and Its Implications

43:58 The Role of Human Judgment in an AI-Driven World

48:07 The Future of Quantum Computing and Its Challenges

56:44 Ethical Considerations in AI and Quantum Technology

58:47 The Future of ZuriQ and European Tech Landscape

About Pavel Hrmo

https://www.linkedin.com/in/pavel-hrmo/

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK

The Quantum Economy: https://andersindset.com/shop/The-Quantum-Economy-p803754261

https://andersindset.com/

https://tomorrowmensch.com/

https://www.linkedin.com/in/andersindset/

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Discover why qubits are so fragile, how 25 years of error rate improvements still fall short, and the trillion-operation leap needed for real-world impact. Steve reveals Riverlane's real-time error correction stack—accelerating hardware roadmaps by 3-5 years across superconducting, trapped ions, neutral atoms, silicon spins, and NV centers.

Key insights:

• Crossing the QEC threshold: From 1,000 to billions of error-free operations

• Quantum + AI/HPC: Hybrid workflows for next-gen supercomputing

• First applications: Quantum chemistry, materials design, efficient catalysts

• Quantum computers as "programmable models of nature" for new physics discoveries

They also tackle big questions: Are quantum machines or nature's simulators? Can quantum-AI uncover new elements or physical laws? Is consciousness computable?

00:00 Introduction

01:37 The Fragility of Qubits and Error Correction

04:40 Engineering Challenges in Quantum Computing

07:40 Exploring Different Qubit Modalities

11:48 Commercial Pathways for Quantum Computing

13:58 The Role of Quantum Computing in Chemistry

18:40 The Intersection of Quantum Computing and AI

21:33 Quantum Mechanics: A Model of Nature

24:39 Exploring New Physics with Quantum Computers

34:34 Exploring Quantum Simulations and Reality

37:36 The Future of Quantum Computing and AI Convergence

42:07 The Implications of AI and Quantum Technologies

49:24 The Nature of Consciousness and Human Uniqueness

56:20 The Future of Quantum Error Correction and Industry Impact

About Steve Brierley

https://www.linkedin.com/in/steve-brierley-72127a142/

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK

The Quantum Economy

https://andersindset.com/shop/The-Quantum-Economy-p803754261

https://andersindset.com/

https://tomorrowmensch.com/

https://www.linkedin.com/in/andersindset/

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Solano challenges the dominant narrative around quantum technology. Universal quantum computers are not imminent, logical qubits are not yet scalable, and noisy quantum hardware is not useless — it’s an opportunity.

At the center of the conversation is his concept of quantum intelligence: hybrid classical-quantum systems that combine quantum computing and AI to unlock reasoning beyond both human cognition and classical supercomputers.

A sharp and contrarian discussion about quantum advantage, quantum-enhanced machine learning, AI hallucinations, and whether intelligence truly requires consciousness.

Episode breakdown:

00:00 Introduction

01:48 Unconventional Thinking

04:30 The Role of Creativity in the Age of AI

07:34 Challenges in Quantum Computing

10:40 The Reality of Quantum Hardware

13:38 Exploring Quantum Applications and Limitations

16:53 The Future of Quantum Computing and Its Impact

19:39 Innovations at Kipu Quantum

22:43 Commercial Implications of Quantum Technologies

38:38 Advancements in Quantum Computing and AI

41:03 The Future of Quantum Intelligence

47:06 Philosophical Perspectives on Reality and Consciousness

53:39 The Nature of Human Intelligence vs. AI

59:04 The Vision for Artificial Human Intelligence

01:07:54 Promising Developments for Humanity's Future

About Enrique Solano

https://www.linkedin.com/in/enrique-solano-812631154/

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK

The Quantum Economy: https://andersindset.com/shop/The-Quantum-Economy-p803754261

https://andersindset.com/

https://tomorrowmensch.com/

https://www.linkedin.com/in/andersindset/

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Moreira reflects on his three-decade journey from early work with the United Nations and the origins of the web in Geneva to building a global trust ecosystem spanning digital identity, post-quantum cryptography, semiconductors, satellites, and quantum computing. He explains why trust in the quantum era cannot be treated as a feature layered on top of technology, but must be embedded at the architectural level — comparable to energy grids or financial systems.

Together, they discuss quantum security, the coming “Q-Day”, the geopolitical implications of technology sovereignty, and why Europe must learn to scale global technology champions. The conversation also examines how quantum computing will reshape encryption, finance, AI, and digital identity, and what this means for governments, companies, and society.

Moreira shares his long-term vision for a human-centric digital future, where technology strengthens resilience, autonomy, and consent rather than control.

A focused, wide-ranging, and deeply personal conversation with one of the architects shaping the foundations of trust in the Fourth Industrial Revolution.

Episode breakdown:

00:00 Introduction

01:32 The Importance of Trust in Technology

04:42 Sovereignty and Decentralization in Technology

07:15 The Evolution of Digital Trust

10:22 Building a Trust Infrastructure

13:37 The Role of Quantum Computing

16:30 The Urgency of Post-Quantum Security

19:22 The Future of Identity and Consent

22:20 Cultural Shifts in Identity and Trust

34:32 The Evolution of Digital Identity

37:45 Empowering Individuals in the Digital Age

42:35 AI as a Tool for Enhanced Decision-Making

50:50 The Intersection of Humanity and Technology

57:19 The Future of Human Enhancement and Technology

01:02:37 Innovations on the Horizon: WISeKey and SEALSQ

About Carlos Moreira

https://www.linkedin.com/in/carloscreusmoreira/

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK

The Quantum Economy: https://andersindset.com/shop/The-Quantum-Economy-p803754261

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https://tomorrowmensch.com/

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Martinis reflects on his journey from early superconducting qubit experiments to the landmark quantum supremacy breakthrough at Google, and explains why building a scalable quantum computer is ultimately a systems-engineering challenge where manufacturability matters as much as physics. He shares his perspective on how quantum computing will complement classical computing and AI, why meaningful economic impact will take time, and why progress is likely to be slower—but ultimately deeper—than today’s hype suggests. 

A focused and personal conversation with one of the scientists who helped turn quantum computing from theory into reality.

Episode breakdown:

00:00 Introduction

00:59 Quantum Supremacy

03:57 Engineer vs. Physicist

07:17 The Feynman Moment

11:16 Scaling Quantum Computing

20:42 From Academia to Industry

28:53 Economics of Quantum36:52 Where the Real Synergies Lie39:36 Consciousness, Language & the Limits of Computation

55:22 Why Progress Still Matters

About John Martinis

https://www.linkedin.com/in/john-martinis-5856911a6/ https://www.physics.ucsb.edu/people/john-martinis

About Anders Indset

Anders Indset is the world’s leading business philosophers and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

NEW BOOK:The Quantum Economy https://andersindset.com/shop/The-Quantum-Economy-p803754261

https://andersindset.com/

https://tomorrowmensch.com/

https://www.linkedin.com/in/andersindset/

https://www.instagram.com/andersindse

thttp://x.com/andersindset

They discuss how quantum technology is leaving the lab, why neutral-atom processors are emerging as a scalable path, and how quantum will complement classical computing and AI rather than replace them. The conversation includes a clear 2026 outlook, explores Europe’s role in technological sovereignty, and opens a philosophical discussion on emergence, responsibility, and what quantum technology could mean for human agency in a world shaped by supercomputing.

A focused conversation on quantum advantage, leadership, and what it truly means for breakthrough science to become real.

Episode breakdown:

00:00 Introduction

02:11 From Curiosity to Capability

08:01 Between Promise and Reality

13:18 From Lab to Market

18:25 Quantum as a Strategic Asset

25:02 Quantum Meets AI

35:35 Measuring Progress

43:06 Technology, Responsibility and Society

47:31 A Reflective View on Quantum’s Future

About Loïc Henriet

https://www.linkedin.com/in/lo%C3%AFc-henriet-974b2a53/

About Anders Indset

Anders Indset is the world’s leading business philosopher and the author of seven international bestsellers. With recent works such as Ex Machina – The God Experiment and The Singularity Paradox: Bridging the Gap Between Humanity and AI, his thought leadership has expanded far beyond economics and classical philosophy – earning him recognition from leading scientists and technologists, including prominent physicists. As the founder of tomorrowmensch, he invests in breakthrough science and technologies and convenes leading thinkers, investors, and entrepreneurs shaping the future.

⁠https://andersindset.com/⁠⁠

https://tomorrowmensch.com/

⁠⁠https://www.linkedin.com/in/andersindset/⁠⁠

https://www.instagram.com/andersindset⁠⁠

http://x.com/andersindset⁠

NEW BOOK The Quantum Economy https://andersindset.com/shop/The-Quantum-Economy-p803754261