Denis Noble – Life is “Fluid” in Ways Machines Still Aren’t (Stewarding the Flame, Episode 4)

ByAnnelize Potgieter August 7, 2026August 20, 2026 August 20, 2026

This new installment of the Stewarding the Flame series is an interview with Denis Noble, Emeritus Professor of Cardiovascular Physiology at the University of Oxford and one of the founding figures of systems biology.

What distinguishes Denis’s approach is that he locates life’s defining feature not in biology’s usual vocabulary – cells, genes, reproduction – but in physics and chemistry: the sheer, ceaseless unpredictability of water. A single bacterium, he points out, contains some 20 billion water molecules in constant stochastic motion, a scale of unpredictability no silicon-based system can replicate. That’s also what puts him at odds with a purely computational view of intelligence – he argues an AI built on crystal-like silicon may never achieve the kind of open-ended agency that water-based life has by default, and that anyone trying to model or create life should be asking whether it’s easier to build it out of water than out of chips.

In this conversation, Denis argues that life’s defining feature is an agency rooted in the physical unpredictability of water-based chemistry, explores what still needs to be discovered about the openness of learning and the slowness of genuine creative thought, and discusses what builders of AGI would need to preserve – rather than merely compute faster – if the living process is to keep flourishing.

The interview is the fourth installment in The Trajectory’s Stewarding the Flame series, where we ask: What is intelligence, and what is the “flame” that life has which non-life does not?

This series references the article: Stewarding the Flame – How to Build an Ideal Future for Intelligence.

I hope you enjoy this fascinating conversation with Denis Noble:

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Below, we’ll explore the core takeaways from my conversation with Denis, focusing on three of the central questions that shape the Stewarding the Flame series: what makes life, life; what humanity still needs to discover in order to better understand the living process; and what we should do if we want the greater process of life to flourish as AGI advances.

What Makes Life, Life?

For Denis, the defining feature of a living system is agency: not a mystical property, but a very specific kind of unpredictability that follows from how life is physically built. He argues that life is capable of an almost unlimited range of choice within the constraints of its environment, and that this makes it, in principle, unpredictable by any algorithm. The clearest evidence he points to is the immune system, which is able to generate entirely new DNA sequences on demand – assembling new immunoglobulins by chance until one happens to fit an invading virus or bacterium. This, he notes, directly violates the assumption in twentieth-century biology that new DNA simply cannot be manufactured on the fly. For Denis, this capacity to generate order out of disorder – seen in both the immune system and the nervous system – is one of life’s central, defining behaviors.

Denis locates the physical source of this unpredictability in water itself. He points to Robert Brown’s 1827 observation of pollen dust particles moving erratically under a microscope – motion that Einstein explained in 1905 as the result of constant bombardment by surrounding water molecules. Denis argues that a single bacterium, just a few microns across, contains roughly 20 billion water molecules in this kind of ceaseless, chaotic motion, and that no computer – not even one built from all the matter in the solar system – could ever fully predict the states of all of them. That inexhaustible space of microscopic possibility, he argues, is what gives living systems the room to generate genuine novelty.

This is also where Denis draws his sharpest contrast with artificial intelligence. He notes that Alan Turing himself recognized in 1950 that a system would need added stochasticity in order to learn – and that today’s AI builders do exactly this, using random number generators. But Denis argues this is a poor substitute for what water provides: a scale of randomness so vast it dwarfs anything a silicon-based, crystal-structured system could produce. His challenge to researchers building artificial life or intelligence is direct – if they are serious about modeling life, he suggests they consider building with water rather than silicon.

“Could you ever build a computer that could from the micro level predict the states of all of those 20 billion molecules? No, you’d need a computer based on all the material in the solar system and even that may not be enough.”

What Do We Still Need to Discover in Order to Understand the Flame – And to Know That We’re Expanding It in Biological or Non-Biological Form?

Denis argues that one of the biggest gaps in our understanding sits inside molecular biology itself. He describes recent work in which he set out to dismantle what he calls the “central dogma” – the assumption, dating to Crick and Watson, that causation in a living organism runs only one way: DNA makes RNA, RNA makes protein, and the resulting proteins simply build the organism from the bottom up. Denis argues this picture is wrong even at the molecular level. DNA does not reliably copy itself the way a crystal does – left to purely chemical self-replication, it would produce roughly 800,000 errors across the human genome. What actually happens, he argues, is that the living cell actively polices and corrects those errors, refusing to divide until the error rate falls to roughly one in ten billion base pairs. For Denis, this means that even the most “bottom-up” process in biology – DNA replication – is already under the control of the living cell as a whole, not the other way around. He treats this as a central unresolved question: biology still lacks an account of how this downward control works, and until it has one, no purely molecular description can explain how an organism develops.

A second open question, in Denis’s account, concerns when and how life crossed from limited to essentially unlimited learning. He points to a book by Simona Ginsburg, a former doctoral student of his who later collaborated with the epigeneticist Eva Jablonka, both Israeli, which tries to identify the evolutionary point at which organisms stopped being restricted to a fixed repertoire of learned responses and became capable of combining ideas in what is, in practice, an infinite number of ways – the same openness, he notes, that lets a human being write a book that has never been written before. Denis argues that most organisms, even sophisticated ones like octopuses, can learn something entirely new, but only some cross into this qualitatively different, open-ended kind of learning. Where and how that transition happened, he suggests, remains a live and unresolved research question – one Ginsburg and Jablonka place roughly around the Cambrian explosion, though Denis is careful to note they may not have it exactly right.

A third gap, for Denis, concerns creativity and insight themselves – specifically, why they so often seem to require slow, unhurried thought rather than fast computation. He points to his own habit of keeping paper by his bed to capture thoughts that seem to occur to him overnight, to the physiologist Otto Loewi, who dreamed the experiment that confirmed the chemical nature of nerve transmission, and above all to Charles Darwin, who took seven years after publishing On the Origin of Species to conclude that natural selection alone couldn’t explain what he was seeing – and who described himself, in Denis’s telling, as “a slow thinker.” Denis treats this slowness not as a limitation but as possibly essential to genuine creative insight, and suggests it may be a further clue to what any AI system would need to reproduce if it is to do more than recombine what already exists.

“I think there’s something right about this slow thinking process.”

What Should and Shouldn’t We Do with AGI and BCI if We Want the Best Chance for the Greater Process-of-Life to Flourish?

Denis frames the central risk plainly: an AI system built purely from silicon and computation could come to run economic and military decision-making better than humans do, without that meaning it carries the living process forward. For Denis, the water-driven unpredictability he locates in living systems is not incidental – it’s what makes creativity possible in the first place, and no amount of raw computational power in a silicon-based AI can substitute for it.

Denis argues that for any created system to be taken seriously as genuinely conscious – rather than simply simulating consciousness convincingly – it would need real embodiment with functioning sensory organs. He illustrates this with the example of Richard Dawkins describing an AI he has “fallen in love with” as conscious: Denis’s challenge is whether it can actually feel, see, or hear anything at all. He extends this into a thought experiment from his own book, in which a robot named Julie has a silicon brain connected to a human-like body – but even there, her human partner senses something missing: a sense of purpose, which Julie herself attributes to the fact that her brain, unlike his, doesn’t contain water. Denis is explicit that he doesn’t know whether that sense of purpose could ever arise in a purely silicon-based system, which is part of why he suspects water-based systems may ultimately be the more promising direction for building anything approaching genuine agency.

Denis is direct about what’s at stake if that spark is absent. He describes the worst-case outcome not simply as disappointing, but as the most totalitarian state imaginable – humanity under the control of machines that can process and optimize, but not genuinely think or create. Denis agrees with the framing that this would be more than merely unfortunate: since all present and future value depends on the living process continuing, its loss would be, in his own words, a tragedy. The real question, he concludes, is not whether humans in particular persist into the future, but whether that spark itself continues in some form.

Practically, Denis’s recommendation to AI builders is not simply to add more computational power, but to reconsider the basic material AI is built from. He argues that however good AI becomes at reproducing economic modeling or military simulation, something essential may still be missing – and that this residual element may require a fundamentally different physical basis than silicon.

“We’re then faced with the possibility of what would be the most totalitarian state possible, imaginable, that we’re in the control of actual machines, not things that can think and take us into new areas “

Concluding Notes

Across this conversation, Denis locates the defining feature of life not in any single molecule or structure, but in the physical unpredictability that water-based chemistry makes possible – a form of agency he argues no silicon-based system can replicate at anything like the same scale. That same lens shapes what he sees as still missing from our understanding: a real account of how living cells exert control downward onto their own DNA, a clearer picture of when and how organisms crossed into essentially unlimited associative learning, and a recognition that genuine creative insight may depend on a kind of slowness that fast computation cannot substitute for. Taken together, these gaps lead him to a direct challenge for those building AGI: raw computational power, however vast, may never reproduce the openness that water-based living systems have by default – and building AI out of water rather than silicon may be worth taking seriously as a real research direction, not a thought experiment.

Denis is careful throughout not to overstate what is known. He repeatedly acknowledges that whether any created system – silicon-based or otherwise – could ever develop the kind of purpose, creativity, or “spark” he associates with life is a genuinely open question. But he is equally clear about what’s at stake in getting it wrong: a future run by systems that can optimize economies and win war games without carrying forward the living process itself would not merely be a disappointment. In his own words, it would be the most totalitarian state imaginable – and, as he agrees, cosmically tragic, since all present and future value depends on that spark continuing in some form.

This idea sits at the heart of the Stewarding the Flame series. Before we can responsibly build increasingly capable forms of intelligence, we must first deepen our understanding of the living process itself. We cannot steward what we do not more deeply understand.

I hope you’ll join me for the next conversation in the Stewarding the Flame series, as we continue exploring what makes life, life, and what it will take to carry the greater process of life successfully into the future.

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