Speaker 1: Welcome to the Sentient Code, where intelligence is engineered, autonomy
Speaker 1: is emerging, and a line between human and machine grows thinner.
Speaker 1: Each episode, we decode the algorithms, explore the robotics, and
Speaker 1: examine the ideas shaping the future of artificial minds.
Speaker 2: So I want you to imagine a tiny little organism.
Speaker 2: It's roughly maybe a millimeter across, just swimming through this
Speaker 2: shallow pool of fluid in a petri dish. Right, microscopic, yeah,
Speaker 2: totally microscopic. And physically it looks well, it looks exactly
Speaker 2: like pac Man.
Speaker 3: It really does. It has that exact shape.
Speaker 2: It's got this crescent shape with a distinct gaping mouth.
Speaker 2: And the craziest part is that its behavior actually matches
Speaker 2: the shape. So it propels itself forward, right, sweeping through
Speaker 2: a fluid, and it's just gathering up these loose, unattached
Speaker 2: cells in its.
Speaker 3: Path, like eating dots in the game.
Speaker 2: Exactly like the game. It forces the loose cells into
Speaker 2: this dense little pocket inside its mouth, it compresses them
Speaker 2: into a sphere, and then it just injects that compacted sphere.
Speaker 3: Out And that's where things get really weird.
Speaker 2: Right, because within a few days that ejected sphere grows
Speaker 2: its own little motor structures, wakes up and starts swimming
Speaker 2: around to repeat the exact same sweeping and compressing process.
Speaker 3: Yeah, it's a method of replication that well, it just
Speaker 3: doesn't cleanly fit into any of our existing biological categories,
Speaker 3: not at all. I mean, it isn't mitosis, it isn't
Speaker 3: viral hijacking where it invades a host, and it certainly isn't,
Speaker 3: you know, sexual reproduction. We're looking at what it's called
Speaker 3: kinematic self.
Speaker 2: Replication, kinematic meaning movement exactly.
Speaker 3: It's a purely geometric physical assembly of offspring.
Speaker 2: Okay, and here's the element that completely shatters our traditional
Speaker 2: understanding of biology, right because this microscopic pac man it
Speaker 2: isn't a machine made of silicon or like nanoplastics.
Speaker 3: No, not at all.
Speaker 2: And it's also not a naturally evolved animal. It is
Speaker 2: constructed entirely from amphibian skin cells.
Speaker 3: Frog cells.
Speaker 2: Yeah, specifically cells that have somehow I don't even know
Speaker 2: how to say it, abandoned their genetically predetermined destiny. They
Speaker 2: were supposed to become the smooth outer layer of a frog,
Speaker 2: but instead they've coordinated to function as an entirely novel,
Speaker 2: autonomous reproducing entity.
Speaker 3: Which forces us to confront this massive paradigm shifting question.
Speaker 3: I mean, if a biological cell can just completely disregard
Speaker 3: its evolutionary context to become something.
Speaker 2: Entirely, what is the limit?
Speaker 3: Right, right? What is the actual limit of its capability?
Speaker 3: Are cells merely executing this rigid genetic script or are
Speaker 3: they active agents navigating a landscape of potential forms?
Speaker 2: And that tension is exactly what we are dissecting today.
Speaker 2: We are venturing into the absolute bleeding edge of synthetic biology.
Speaker 2: We're looking at zenobots, their human derived successors known as anthrobots,
Speaker 2: and really the deeper philosophical earthquake happening underneath all this research.
Speaker 3: It's a fundamental challenge to the dogma.
Speaker 2: Totally, because from little school onward, we're taught that biological
Speaker 2: form is just the result of blind, bottom up emergence,
Speaker 2: you know, physics, chemistry, random genetic mutations just thrown into
Speaker 2: the crucible of natural selection over millions of years, the
Speaker 2: standard Darwinian model, right, But the behavior of these cellular constructs,
Speaker 2: it implies a radically different architecture to reality. It suggests
Speaker 2: that biological matter might actually be accessing or maybe discovering,
Speaker 2: pre existing ideal blueprints.
Speaker 3: And that, right there is the crux of the debate
Speaker 3: we're going to unpack today. We really need to look
Speaker 3: past the sheer engineering marvel of these biological robots, as
Speaker 3: cool as they are, and examine the mechanisms at play.
Speaker 3: So we're going to break down the physical forces of
Speaker 3: kinematic replication, investigate the bioelectric networks that act as cellular software.
Speaker 2: The software of life, which is just a wild concept,
Speaker 2: it really is.
Speaker 3: And ultimately we have to question whether the genome is
Speaker 3: actually a rigid architectural blueprint or if it's merely like
Speaker 3: an interface pointing to a much larger, unseen dimension of
Speaker 3: biological possibility.
Speaker 2: Okay, so let's start with the physical genesis of all this.
Speaker 2: The timeline kicks off in the early twenty twenties, researchers
Speaker 2: at Tufts University, the University of Vermont, and the Wiss
Speaker 2: Institute at Harvard managed to create the very first xenobots.
Speaker 3: Yeah, and the nomenclature there comes directly from the source material.
Speaker 3: It's an office lavist, which is the African Claude frog.
Speaker 2: Got it.
Speaker 3: So the researchers harvested pluripotent stem cells from the blastulas
Speaker 3: stage of these frog embryos.
Speaker 2: Blasterless stage meaning like super early development ry.
Speaker 3: Yeah, right, exactly. These are rudimentary, undifferentiated cells. They haven't
Speaker 3: decided what they're going to be yet. And it is
Speaker 3: so critical to state right up front that the genome
Speaker 3: of these cells was left entirely intact.
Speaker 2: Okay, wait, let's emphasize that no crisper cast nine, no crisper,
Speaker 2: no viral vectors delivering modified genes, no synthetic base pairs, no.
Speaker 3: That zero modification. They are genetically indistinguishable from the cells
Speaker 3: of a standard frog swimming in a pond.
Speaker 2: Right now, that's insane. So how did they change them?
Speaker 3: The intervention was purely physical. Researchers basically utilize these microscopic
Speaker 3: forceps and electrodes to manually separate the cells, strip away
Speaker 3: the surrounding embryonic signals, the chemical cues that tell them
Speaker 3: to make a tadpole and aggregate them into novel millimeter
Speaker 3: scale configuration.
Speaker 2: Is literally pushing them into a pile.
Speaker 3: Essentially, yes, and in that isolated, reorganized state, the cells
Speaker 3: didn't simply undergo apoptosis and die, which is what.
Speaker 2: You might expect, right, if you take cells out of
Speaker 2: a body, they usually just die exactly.
Speaker 3: And they didn't form an amorphous tumor either. They exhibited
Speaker 3: highly coordinated emergent properties.
Speaker 2: It became autonomous, yes, but I want to drill down
Speaker 2: into the mechanics of that autonomy because how exactly were
Speaker 2: they moving? I mean, without a central nervous system to
Speaker 2: coordinate motor functions, how does a cluster of frog skin
Speaker 2: cells propel itself.
Speaker 3: Well, it comes down to a repurposed bio logical motor
Speaker 3: called the cilium sili.
Speaker 2: Okay, yeah.
Speaker 3: Silia are these microscopic hair like organelles that protrude from
Speaker 3: the surface of many different types of cells. In a
Speaker 3: normal frog embryo or in your own respiratory tract for
Speaker 3: that matter. Slated cells form a stationary mucosal layer, so
Speaker 3: they just sit there, right. Their normal job is to
Speaker 3: beat in a synchronized rhythm to move fluid or clear
Speaker 3: out debris. They're essentially stationary pumps. But in the zenobot configuration,
Speaker 3: the cells self organized so that these cilia function like
Speaker 3: hundreds of tiny ores.
Speaker 2: But wait, without a brain, how do the ores row
Speaker 2: in the same direction. Because of half the cells are
Speaker 2: beating left and half are beating right, the bot would
Speaker 2: just spin in place or just tear itself apart.
Speaker 3: Yeah, and that is where the multi scale competency of
Speaker 3: the tissue really reveals itself.
Speaker 2: Multi scale competency, yes.
Speaker 3: Meaning the tissue can solve problems at a higher level
Speaker 3: than just the individual cell. The cells rely on localized
Speaker 3: biomechanical and bio electrical communication, so they form what are
Speaker 3: called gap junction gap junctions. Yeah, they're physical channels between
Speaker 3: the cell membranes. They allow ions and small molecules to
Speaker 3: pass directly from one cell cytoplasm to the.
Speaker 2: Next, like a little tunnel between the cells exactly.
Speaker 3: And through these junctions they synchronize their calcium signaling. It
Speaker 3: creates a localized consensus. The cells negotiate a global polarity
Speaker 3: for the entire cluster.
Speaker 2: Wow, So they literally talk to each other to figure
Speaker 2: out which ways forward they do.
Speaker 3: They align the beating of their cilia to achieve directional motility.
Speaker 3: They can swim linearly, they can navigate mazes, and impressively,
Speaker 3: they exhibit remarkable self healing.
Speaker 2: Oh right, the self healing.
Speaker 3: Yeah, if you last read a zenobot physically tearing it
Speaker 3: almost completely into for it, the cells rapidly migrate and
Speaker 3: knit the tissue back together, restoring their original spherical or
Speaker 3: sculpted shape.
Speaker 2: Okay, I want to pause on that localized consensus thing,
Speaker 2: because this is where the standard analogies we usually hear
Speaker 2: start to fail. I mean, you often hear this described
Speaker 2: as taking a pile of lego bricks meant for a castle,
Speaker 2: shaking the box, and watching them assemble into a car.
Speaker 3: Right, I've heard that one.
Speaker 2: But Lato's are inert. A single Lato brick doesn't negotiate
Speaker 2: with the brick next to it.
Speaker 3: No, and the Lato analogy is fundamentally flawed for exactly
Speaker 3: that reason. It treats biological matter as passive hardware. A
Speaker 3: much more accurate comparison would be a flock of birds
Speaker 3: or a swarm of bees.
Speaker 2: How interesting a swarm, right.
Speaker 3: Because a single bee has its own localized sensory inputs,
Speaker 3: its own behavioral algorithms. But when thousands of bees interact
Speaker 3: within a specific physical constraint, they form a hive that
Speaker 3: regulates its own internal temperature and collectively decides where to forage.
Speaker 2: So the cells are like individual bees exactly.
Speaker 3: The xenobod cells are active agents. When you remove the
Speaker 3: top down chemical gradients of the embryo, you know, the
Speaker 3: signals shouting form a tadpole spine. Here the cells default
Speaker 3: to a baseline agential state.
Speaker 2: They wake up and realize they're on their own.
Speaker 3: Yeah, they assess their new topological boundaries, and they optimize
Speaker 3: for survival and equilibrium in that new micro environment.
Speaker 2: Which perfectly sets up the twenty twenty one breakthrough. Because
Speaker 2: surviving and moving is one thing that's cool, but replication
Speaker 2: requires an entirely different level of systemic organization. So let's
Speaker 2: dig into the kinematic self replication because the mechanism behind this.
Speaker 3: Is just wild, it really is. I mean to understand
Speaker 3: why kinematic replication is so disruptive, we have to look
Speaker 3: at the deeply entrenched assumptions of molecular biology. Okay, reproduction
Speaker 3: as we currently define it is intrinsically tied to the
Speaker 3: transmission of genetic.
Speaker 2: Information passing on the DNA.
Speaker 3: Right, Mitosis copies the genome, myosis recombines it. Even a virus,
Speaker 3: which kind of borders on the edge of life anyway,
Speaker 3: operates by injecting RNA or DNA into a host to
Speaker 3: hijack its ribosomes.
Speaker 2: The code is always the star of the show.
Speaker 3: Always. The biological imperative is the propagation of the code.
Speaker 3: But kinematic self replication completely bypassesmic transmission as the driving
Speaker 3: physical mechanism.
Speaker 2: Right, It's closer to what's it called a Vonnoumann probe, Yes,
Speaker 2: the theoretical spacecraft right, where a spaceship lands on a
Speaker 2: dead planet, mines iron and silicon and just builds a
Speaker 2: physical clone of itself to launch to the next star system.
Speaker 3: Precisely, it is reproduction through the sheer mechanical assembly of
Speaker 3: environmental raw materials. Now, the Tufts and Vermont researchers knew
Speaker 3: the unmodified frog cells didn't have the biological hardware to
Speaker 3: reproduce sexually or even bud like yeast.
Speaker 2: Right, They're just skin cells exactly.
Speaker 3: So they turned to an in silico evolutionary algorithm to
Speaker 3: see if a specific physical geometry could induce a replication behavior.
Speaker 2: Okay, I want to get really granular on this algorithm,
Speaker 2: because how do you simulate the physical nuance of a
Speaker 2: living biological cell inside a supercomputer?
Speaker 3: Well, the utilized a specialized physics engine coupled with a
Speaker 3: morphogenetic algorithm. The supercomputer modeled the basic biomechanical properties of
Speaker 3: the frog.
Speaker 2: Stem cells, like what kind of properties their.
Speaker 3: Adhesion forces, their fluid dynamics and an aqueous medium, their density,
Speaker 3: and the contractile forces of the cilia.
Speaker 2: So it's basically a highly advanced physics simulator, right.
Speaker 3: And then the AI began this massive combinatorial search. It
Speaker 3: generated a random arbitrary three dimensional shape simulated, dropping it
Speaker 3: into a virtual Petri dish filled with thousands of loose
Speaker 3: simulated stem cells, and just calculated the physical interactions.
Speaker 2: Most of which I assume resulted in absolute failure.
Speaker 3: Oh almost entirely. I mean, the vast majority of shapes
Speaker 3: just tumbled aimlessly, or they ended up pushing the loose cells.
Speaker 2: Away like a bad snowplow exactly.
Speaker 3: But the algorithm was looking for a specific objective function,
Speaker 3: the aggregation of loose material, so if a specific shape
Speaker 3: accidentally managed to corral a few cells together, the AI
Speaker 3: selected It, introduced slight morphological mutations to the design, and
Speaker 3: ran the simulation again. Wow, it was brutally evaluating the
Speaker 3: fluid mechanics and the rentals number of these microscopic entities,
Speaker 3: optimizing purely for the mechanics of sweeping and compressing.
Speaker 2: And after billions of simulated generations, the algorithm converged on
Speaker 2: an optimal design. It did the pac Man shape, the
Speaker 2: sea shaped crescent.
Speaker 3: Yes a semitaorus. And what is truly fascinating is that
Speaker 3: when the biologists actually took microscopic surgical tools and manually
Speaker 3: sculpted the living frog cells into this AI generated sea shape,
Speaker 3: the physical reality perfectly matched the simulation.
Speaker 2: That's incredible.
Speaker 3: The parent bought would swim in concentric circles using the
Speaker 3: interior curve of the sea to catch loose stem cells.
Speaker 3: The physical geometry created a fluid vortex that pulled the
Speaker 3: loot cells into a tight cluster.
Speaker 2: But the replication is an infinite right, I mean, entropies
Speaker 2: still exists.
Speaker 3: All thermodynamics absolutely still apply. This is a crucial constraint.
Speaker 3: Kinematic replication in this specific setup suffers from generational decay.
Speaker 2: Generational decay meaning it gets weaker over time.
Speaker 3: Basically, the parent bot might gather fifty cells to form
Speaker 3: a first generation office, but that offspring being maybe slightly
Speaker 3: less structurally perfect or slightly smaller, not only possessed the
Speaker 3: physical surfaced area to gather thirty cells, and then the
Speaker 3: third generation might only gather fifteen. Eventually, the constructs drop
Speaker 3: below the critical mass required to maintain coordinated ciliary movement
Speaker 3: and the lineage terminates.
Speaker 2: So it's not an uncontrollable gray goose scenario where they
Speaker 2: take over the world.
Speaker 3: No, no, not at all.
Speaker 2: But the philosophical proof of concept, it's just staggering. You
Speaker 2: have an artificial intelligence that successfully explored a combinatorial space
Speaker 2: of physical interactions and discovered a method of biological reproduction
Speaker 2: that Darwinian evolutions simply never bothered to.
Speaker 3: Invent and never bothered to invent. Is the perfect phrasing there.
Speaker 3: Natural selection only optimizes for fitness within a specific ecological
Speaker 3: niche a frog needs to outswim a fish and catch
Speaker 3: a fly. It never encountered a selective pressure that required
Speaker 3: isolated skin cells to mechanically assemble offspring in a highly
Speaker 3: concentrate soup of stem cells.
Speaker 2: It just never came up in nature exactly.
Speaker 3: The capability was there latent in the physics of the cells,
Speaker 3: but natural evolution never accessed that specific attractor state.
Speaker 2: Now a skeptic might look at this and say, Okay,
Speaker 2: this is a fascinating parlor trick using embryonic stem cells.
Speaker 2: Because stem cells are by definition pluripotent. They are the
Speaker 2: blank slates of the biological world, programmed to be flexible.
Speaker 2: So it's easy to dismiss this as a quirk of
Speaker 2: amphibian embryology.
Speaker 3: Right, you could argue that, Yeah.
Speaker 2: But the research didn't stop there.
Speaker 3: No, And this is where we move past the zenobot
Speaker 3: and into the mid twenty twenties creation of anthrobots human cells,
Speaker 3: not just human cells, adult somatic human cells, specifically ciliated
Speaker 3: epithelial cells harvested from the human trachea, the wind pipe,
Speaker 3: the windpipe.
Speaker 2: Yeah, okay, let's unpack the biological significance of that, because
Speaker 2: in the traditional view of cellular development, you have the
Speaker 2: epigenetic landscape, right, Like Conrad Waddington's famous model on the hill, Right,
Speaker 2: a stem cell is like a marble at the top
Speaker 2: of a hill. As it rolls down the hill, it
Speaker 2: falls into different valleys, eventually coming to rest at the
Speaker 2: bottom as a fully differentiated cell, a neuron, a muscle cell,
Speaker 2: or a windpipe cell. And the dogma says once it's
Speaker 2: at the bottom of the valley. It is locked in,
Speaker 2: fully locked, It has deactivated the genes it doesn't need,
Speaker 2: and it is strictly committed to its specialized function.
Speaker 3: That has been the central dogma for decades. Differentiated cells
Speaker 3: are locked hardware, but anthrobots fundamentally violate that assumption. Oh
Speaker 3: so well, the researchers took these fully mature trachial cells
Speaker 3: that a completely rolled down Waddington's landscape and settled into
Speaker 3: their terminal identities and isolated them.
Speaker 2: And without the manual surgical sculpting that the xenobots required,
Speaker 2: these cells just self assembled.
Speaker 3: Yes, that is a massive leap in multi scale competency.
Speaker 3: The researchers didn't need microscopic forceps to carve out a
Speaker 3: C shape this time. They just manipulated the surrounding extracellular
Speaker 3: matre altering the viscosity of the fluid.
Speaker 2: Environment, and the cells just responded to that.
Speaker 3: They responded dynamically, They spontaneously aggregated into multicellular spheroids, and
Speaker 3: more incredibly, they managed to orient their cilia wait oren them.
Speaker 3: How So, in a wind pipe, the cilia face outward
Speaker 3: into the lumen to move mucus up and out of
Speaker 3: the lungs in the petri dish. The cells actually recognize
Speaker 3: their new spherical topology and ensure the cilia were facing
Speaker 3: outward on the surface.
Speaker 2: Of the sphere to act as ores.
Speaker 3: Again exactly enabling them to swim.
Speaker 2: Okay, if you're listening to this right now, let that
Speaker 2: sink in the cells currently lining your respiratory tract. Right
Speaker 2: this second possess the latent dormant capability to disconnect from
Speaker 2: their tissue matrix, spontaneously self organized into a motile, spherical
Speaker 2: robot and navigate an aqueous environment.
Speaker 3: They just require a shift in their contextual boundaries. That
Speaker 3: is wild, and their competencies extend far beyond simple motility.
Speaker 3: The medical implications became violently clear when researchers tested how
Speaker 3: these anthrobots interacted with other human tissues.
Speaker 2: Right the paramedic behavior.
Speaker 3: Yes, So they engineered a two dimensional layer of human
Speaker 3: neural tissue in a dish and mechanically scratched it.
Speaker 2: They created a wound.
Speaker 3: They created a physical wound that severed the neural connections,
Speaker 3: effectively as simulated spinal cord injury. Then they introduced the
Speaker 3: anthrobots into this environment, and without any external programming or
Speaker 3: chemical breadcrumbs from the researchers.
Speaker 2: Nobody told them what to do.
Speaker 3: Nobody told them. The anthrobots navigated directly to the site
Speaker 3: of the laceration. They settled specifically across the gap in
Speaker 3: the tissue, and then they began exerting an influence on
Speaker 3: the neurons.
Speaker 2: They started healing them.
Speaker 3: They didn't just passively sit there, you know. They stimulated
Speaker 3: the neural tissue to regenerate, coaxing the neurons to bridge
Speaker 3: the gap and restore the network. They functioned as autonomous biological.
Speaker 2: Paramedics, which is just mind blowing. But then we hit
Speaker 2: the twenty twenty six update, which takes this entirely out
Speaker 2: of the realm of mechanical paramedics and introduces the concept
Speaker 2: of the neurobot.
Speaker 3: Right, so, researchers observe that in certain configurations, these human
Speaker 3: constructs began developing spontaneous, primitive neural networks. Okay, hold on,
Speaker 3: we aren't just looking at a sphere of cells moving
Speaker 3: with silly anymore. We are seeing the emergence of complex,
Speaker 3: coordinated movements driven by an internal signaling network that highly
Speaker 3: resembles a rudimentary nervous system.
Speaker 2: Wait wait, you lost me. If the original tracheal cells
Speaker 2: weren't neurons and there is no brain orchestrating this, how
Speaker 2: does a neural network spontaneously emerge? Doesn't the DNA have
Speaker 2: to trigger a massive shift in cell type to create
Speaker 2: a neuron.
Speaker 3: That is the exact right quote, and it points to
Speaker 3: the profound plasticity of the bioelectric sensidium.
Speaker 2: Bioelectric what sinsidium?
Speaker 3: It's a network of cells that act together. The cells
Speaker 3: don't necessarily need to completely revert to a stem cell
Speaker 3: state and rewrite their entire transcriptional profile to become a
Speaker 3: neuron in a traditional sense. Remember, all are electrical. What
Speaker 3: happens in a neurobot is that the gap junctions between
Speaker 3: the cells, those little tunnels we talked about, they become
Speaker 3: highly specialized. They start allowing rapid coordinated voltage spikes that
Speaker 3: mimic action potentials.
Speaker 2: Like brain waves.
Speaker 3: Basically, yes, the tissue realizes that in order to coordinate
Speaker 3: complex movements in its new environment, it needs a faster
Speaker 3: communication network, so it dynamically reallocates its bioelectric resources to
Speaker 3: create a primitive neural architecture. It is problem solving at
Speaker 3: the tissue.
Speaker 2: Level, which brings up the most glaring mystery in all
Speaker 2: of this. I mean, if the genome, the DNA sequence
Speaker 2: remains completely unchanged throughout this entire process, which it does, right.
Speaker 2: If the DNA isn't explicitly dictating build a pac man
Speaker 2: or build a neuralbot, where is the memory of these
Speaker 2: shapes and behaviors actually stored. If DNA is just the
Speaker 2: parts list, what is functioning as the operating system?
Speaker 3: And that leads us to the invisible architecture of all
Speaker 3: morphogenesis bioelectricity.
Speaker 2: Okay, when you hear bioelectricitymediately think of neurology, right, action
Speaker 2: potential shooting down an axon, heart taste makers, the.
Speaker 3: Rapid transient spikes. Yes, yeah, But what Michael Levin and
Speaker 3: his colleagues have championed is the understanding of developmental bioelectricity.
Speaker 2: Developmental so slower.
Speaker 3: Much slower, slower, persistent electrical networks. Every single cell in
Speaker 3: your body has a membrane, and embedded in that membrane
Speaker 3: are ion channels. These are proteins that actively pump charged
Speaker 3: ions like potassium, sodium, and chloride in and out of
Speaker 3: the cell.
Speaker 2: And this creates a resting membrane potential, meaning the inside
Speaker 2: of the cell has a different electrical charge than the outside.
Speaker 3: Exactly, it creates a localized voltage gradient, and because these
Speaker 3: cells are connected via those gap junctions, they share this
Speaker 3: electrical state with their neighbors. They form an electrical sensidium.
Speaker 3: It isn't just a physical clump of cells. It is
Speaker 3: a unified electrical network.
Speaker 2: It's like a shared battery, almost a shared.
Speaker 3: Battery, and a shared information network. Levin's research demonstrates that
Speaker 3: this bioelectric network acts as a software layer that processes
Speaker 3: information and dictates large scale anatomical outcomes. The voltage gradients
Speaker 3: physically map out the anatomical axis of the organism.
Speaker 2: So wait, it's not the DNA turning genes on and
Speaker 2: off that directly decides where an arm goes. It's the
Speaker 2: bioelectric field. Saying this coordinate requires an arm, and then
Speaker 2: the cells read that field and activate the necessary genes
Speaker 2: to build it.
Speaker 3: You've isolated the exact mechanism. The bioelectric pattern is the
Speaker 3: primary driver. The genetic transcription is downstream. The genes build
Speaker 3: the hardware the ion channels themselves, but the state of
Speaker 3: the network the actual voltage gradient is an epigenetic phenomenon.
Speaker 3: It's an emergent property, and the most irrefutable evidence for
Speaker 3: this doesn't come from zenobots. Actually, it comes from an
Speaker 3: entirely different model organism, the polenarian flatworm.
Speaker 2: Oh right. If you've ever taken a biology lab, you
Speaker 2: know plenaria. They are those tiny, cross eyed flatworms that
Speaker 2: are famous for regeneration. You can cut one into like
Speaker 2: a dozen pieces and each piece will regrow into a
Speaker 2: complete worm.
Speaker 3: Are the undisputed masters of anatomical homeostasis. And for decades,
Speaker 3: the assumption was that a localized stem cell population they're
Speaker 3: called neoblasts, would just consult the DNA to figure out
Speaker 3: what was missing and rebuild it.
Speaker 2: So if you cut off the head, the cells at
Speaker 2: the womb site, look at the DNA, realize they are
Speaker 2: missing ahead, and build one.
Speaker 3: That was the assumption. But Levin's lab proved that isn't true.
Speaker 2: They completely dismantled it.
Speaker 3: They totally dismantled it. They took a genetically normal plenarium,
Speaker 3: they amputated its head. Then using specific pharmacological agents like
Speaker 3: octanol which blocks gap junctions, or ionophores that alter membrane permeability.
Speaker 3: They transiently disrupted the bioelectric gradient at the woon site.
Speaker 2: They essentially forced the cells at the front room to
Speaker 2: adopt the voltage signature typically associated with the back end.
Speaker 3: Exactly, they didn't touch the DNA, They just hacked the
Speaker 3: electrical gradient.
Speaker 2: They hacked the software.
Speaker 3: They hacked the software, and the result was that the
Speaker 3: flatworm regenerated a second tail where its head used to
Speaker 3: be amazing or, in other experiments, they altered the posterior
Speaker 3: gradient to mimic an anterior one, and the worm grew
Speaker 3: a second, perfectly functional head on its rear.
Speaker 2: But here is the part that genuinely breaks my understanding
Speaker 2: of biology. If you take that two headed worm, let
Speaker 2: the drugs wear off entirely so the ion channels are
Speaker 2: functioning normally again, and then you amputate both heads.
Speaker 3: What regenerate a two headed worm.
Speaker 2: Regenerates wait without the drugs, Without.
Speaker 3: The drugs, and with a completely wild type unaltered genome.
Speaker 3: The DNA of that flatworm still definitively dictates I am
Speaker 3: a single headed organism.
Speaker 2: Because it's still normal DNA.
Speaker 3: Right. But the bioelectric network has a memory. By transiently
Speaker 3: altering the voltage gradient. Initially, the researchers permanently shifted the
Speaker 3: attractor state of the electrical network. The target morphology, the
Speaker 3: shape the tissue is constantly striving to achieve, was rewritten.
Speaker 2: So the tissue is consulting the electrical field, not the genome,
Speaker 2: to determine its final shape.
Speaker 3: The bioelectric pattern is the spatial memory of the organism.
Speaker 3: The cells are constantly communicating, evaluating their current physical arrangement
Speaker 3: against this stored bioelectric target morphology. If there is a mismatch,
Speaker 3: like a severed head or a laceration, they trigger cell
Speaker 3: division and migration to reduce.
Speaker 2: The error, and once the physical shape matches the bioelectric memory, they.
Speaker 3: Stop exactly they reach it ecuilibric.
Speaker 2: And this explains the anthrobots and zenobots. When you isolate
Speaker 2: the cells from the embryo or the trachea, you strip
Speaker 2: away the overarching bioelectric field of the whole organism. You
Speaker 2: leave them in a state of sensory deprivation.
Speaker 3: Precisely, the local network depolarizes. The cells suddenly realize they
Speaker 3: are no longer constrained by the bioelectric boundaries of a
Speaker 3: frog or a human wind pipe. They're in a new environment,
Speaker 3: so they rapidly negotiate a new stable bioelectric state.
Speaker 2: They find a new target morphology, yes, that.
Speaker 3: Suits their isolated conditions, resulting in the spherical ciliated constructs
Speaker 3: we observe.
Speaker 2: But this, I mean this pushes us into some incredible
Speaker 2: deep philosophical waters because if the DNA isn't providing the
Speaker 2: blueprint and the bioelectric field is just the operating system
Speaker 2: maintaining the shape, where do these specific shapes actually come from?
Speaker 3: That is the million dollar question.
Speaker 2: Why does an isolated cluster of cells reliably form a
Speaker 2: spherical self healing entity, and why does an AI discover
Speaker 2: a kinematic replicating geometry.
Speaker 3: This is where we cross from molecular biology into metaphysics. Frankly,
Speaker 3: Michael Levin proposes that biological systems are interfacing with what
Speaker 3: he calls a morpho space or a platonic space of
Speaker 3: possible patterns.
Speaker 2: Okay, I want to tread carefully here because invoking Platonism
Speaker 2: in modern science usually triggers alarm bells.
Speaker 3: Oh.
Speaker 2: Absolutely, the standard materialist view is strictly bottom up. Form
Speaker 2: is nothing more than an emergent illusion caused by the
Speaker 2: blind interaction of fundamental particles. There's no predetermined goal, no
Speaker 2: ideal form. It's just chemistry tumbling forward in time, filtered
Speaker 2: by survival of.
Speaker 3: The fittest, that is the dominant paradigm. Levin argues that
Speaker 3: standard emergence doesn't adequately explain the sheer, reliability and elegance
Speaker 3: of these novel competencies. I mean, you think about it.
Speaker 3: The frog genome was optimized by millions of years of
Speaker 3: evolutionary pressure to survive in a pond ecosystem. Right, there
Speaker 3: was zero evolutionary pressure to select for the ability to
Speaker 3: form a millimeter scale geometrically replicating.
Speaker 2: Pac Man exactly. A random blind mutation process doesn't accidentally
Speaker 2: pre program an incredibly complex, flawlessly executed survival strategy for
Speaker 2: an environment the organism has literally never encountered.
Speaker 1: Right.
Speaker 3: Therefore, Levin argues the blueprint for the xenobot isn't stored
Speaker 3: in the DNA. It exists as an abstract mathematical potentiality
Speaker 3: within a latent morphospase. The cells aren't inventing the shape,
Speaker 3: they are discovering it.
Speaker 2: It's like think of it like cimatics. If you take
Speaker 2: a metal plate, cover it in fine sand and run
Speaker 2: a specific audio frequency through the plate. The sand spontaneously
Speaker 2: arranges itself into a perfectly so metrical, complex geometric mendala.
Speaker 3: Well that's a phenomenal analogy.
Speaker 2: Yes, And if you change the frequency, the sand instantly
Speaker 2: shifts into a different, equally perfect mandala.
Speaker 3: Because the sand doesn't possess the blueprint for the mandala
Speaker 3: and the metal plate doesn't possess it, the pattern exists
Speaker 3: as a mathematical reality of acoustic nodes and anti noodes.
Speaker 3: The physical matter the sand simply settles into the energetic
Speaker 3: minimums of that pre existing mathematical structure.
Speaker 2: So in this framework, what is the genome if it's
Speaker 2: not the blueprint?
Speaker 3: The genome is a hash pointer, It is an IP address,
Speaker 3: It is a frequency dial on your somatic plate. Millions
Speaker 3: of years of evolution have finally tuned the frog's genome
Speaker 3: to reliably point to the specific coordinate in morphospace that
Speaker 3: corresponds to a frog.
Speaker 2: It tunes the cellular hardware to access that specific state.
Speaker 3: Yes, but when we physically rearrange the cells or alter
Speaker 3: their bioelectric networks, we are essentrally turning the dial. We
Speaker 3: move the pointer to an adjacent coordinate in the morphospace,
Speaker 3: and the physical matter of the cells snaps into a
Speaker 3: new attractor state, the zenobot.
Speaker 2: This aligns heavily with analytic idealism, doesn't it, and the
Speaker 2: process philosophy of Alfred North Whitehead.
Speaker 3: It draws directly from Whitehead. I mean white had completely
Speaker 3: rejected the idea that reality is just dead matter bouncing
Speaker 3: around and avoid He proposed that the fundamental constituents of
Speaker 3: reality are actual occasions or events of experience, and crucial
Speaker 3: to his philosophy is the concept of ingression. Aggression yeah,
Speaker 3: abstract eternal objects, patterns, forms, mathematical truths ingress into physical
Speaker 3: reality when the local conditions permit it.
Speaker 2: So the xenobot form always existed in this abstract mathematical space,
Speaker 2: waiting for the right physical substrate to ingress into, just
Speaker 2: like the prime number has existed before humans evolve the
Speaker 2: cognitive capacity to count them.
Speaker 3: Precisely. We didn't invent prime numbers, we developed a neural
Speaker 3: architecture capable of discovering them. Levin suggests that biology is
Speaker 3: cognition all the way down. Cells, tissues, organs. They are
Speaker 3: cognitive agents navigating this mathematical morphospace. Solving physiological problems by
Speaker 3: accessing these ideal forms.
Speaker 2: Now, obviously asserting that Darwini emergence is insufficient and invoking
Speaker 2: a mathematical realm of ideal forms is going to face
Speaker 2: intense visceral pushback from the scientific establishment.
Speaker 3: Oh, it already is.
Speaker 2: So we have to examine the counter arguments, impartially because
Speaker 2: of the bait here is fierce.
Speaker 3: We absolutely do. The skeptics fundamentally reject the necessity of
Speaker 3: a platonic morphospace. They rely on the principle of parsimonia
Speaker 3: or Oukham's razor. They argue that everything we observe, from
Speaker 3: the two headed plenaria to the kinematic replication of the
Speaker 3: xenobox can be entirely explained by the non linear dynamics
Speaker 3: of complex systems.
Speaker 2: They say, it's just the combinatorial explosion of physical interactions.
Speaker 3: Right, look at the AI that design the pac Man shape.
Speaker 3: The defenders of Levin's view say the AI discovered the
Speaker 3: ideal replicating form in the platonic realm. But the materialist
Speaker 3: critics argue that the AI simply brute forced a physics problem.
Speaker 2: It just crunched the numbers.
Speaker 3: Yeah, it ran billions of permutations of fluid dynamics and
Speaker 3: cellular adhesion until it found a physical arrangement that mechanically
Speaker 3: resulted in loose cells clumping together.
Speaker 2: If you shuffle a deck of cards enough times, eventually
Speaker 2: you deal royal flush. You didn't access an ethereal realm
Speaker 2: of perfect poker hands. You just exhausted the probability space exactly.
Speaker 3: The skeptics argue that cells are incredibly complex biochemical machines
Speaker 3: when you put them in a novel environment. They're intricate
Speaker 3: feedback loops, you know, gene regulatory networks, protein folding mechanics,
Speaker 3: membrane tensions. They just interact in undredictable emergent ways.
Speaker 2: And the fact that these interactions stabilize into a moving
Speaker 2: sphere isn't proof of an ideal form, right.
Speaker 3: They say, it's just proof that biological matter seeks thermodynamic equilibrium.
Speaker 3: They view Levin's morphospace as scientifically unfalsifiable, a biological god
Speaker 3: of the gaps that mystifies something we simply haven't fully
Speaker 3: mapped biochemically yet.
Speaker 2: But the defenders of the morphospace theory have a direct
Speaker 2: counter to the shuffle deck argument.
Speaker 3: They do. They point to this sheer efficiency and elegance
Speaker 3: of the observed behaviors. I mean, if you deal a
Speaker 3: royal flush once, it's probability. If you shuffle the deck
Speaker 3: and deal a royal flesh fifty times in a row,
Speaker 3: you have to suspect the deck is stacked.
Speaker 2: That makes sense.
Speaker 3: Biological systems, when placed in completely alien configurations, don't thrash
Speaker 3: around blindly for billions of years looking for a solution.
Speaker 3: They find incredibly elegant solutions like kinematic replication or neural
Speaker 3: bridging almost immediately. The defenders argue that random combinatorial search
Speaker 3: cannot account for that level of rapid, coordinated problem solving
Speaker 3: without an underlying mathematical topology guiding it.
Speaker 2: And Levin explicitly claims this hypothesis is falsifiable, which moves
Speaker 2: it out of pure philosophy and into empirical science.
Speaker 3: Yes, his proposed test is substrate independence.
Speaker 2: Substrate independence, right.
Speaker 3: If the bioelectric software and the MorphOS based patterns are
Speaker 3: truly independent of the genetic hardware, we should be able
Speaker 3: to induce them across radically different substrates. We've seen it
Speaker 3: in amphibians, we've seen it in human epithelial cells.
Speaker 2: So If researchers can engineer constructs using like Avian cells
Speaker 2: or reptilian cells or eventually maybe hybrid biosilicon polymers, and
Speaker 2: they reliably observe the exact same unexpected algorithms of healing,
Speaker 2: motility and geometric replication.
Speaker 3: Then you prove the pattern isn't a quirk of frog
Speaker 3: DNA or human DNA, it's a universal attractor state.
Speaker 2: Wow. If Microsoft Word runs perfectly on a PC, a MAC,
Speaker 2: and a Linux machine, you know the software exists independently
Speaker 2: of the hardware architecture.
Speaker 3: Precisely Substrate independence is the ultimate test of the MorphOS
Speaker 3: space hypothesis.
Speaker 2: Regardless of which side of the philosophical debate you land on,
Speaker 2: whether you view this as incredibly complex material emergence or
Speaker 2: the aggression of platonic forms, the practical real world reality
Speaker 2: of these biobots is about to hit us like a
Speaker 2: free train.
Speaker 3: Oh. The applications are world changing.
Speaker 2: The implications span medicine, environmental science, and fundamental ethics. Start
Speaker 2: with the immediate technological applications.
Speaker 3: Well, the most obvious advantage of a zenobot or an
Speaker 3: anthrobot over a traditional metallic nanobot is that it is
Speaker 3: one hundred percent biocompatible and entirely biodegradable.
Speaker 2: They just dissolve.
Speaker 3: Yeah, They operate for a few weeks on their internal
Speaker 3: energy stores, and when those stores are depleted, they simply
Speaker 3: degrade into harmless dead cells.
Speaker 2: This makes them the ultimate environmental cleanup tool.
Speaker 3: You could engineer massive swarms of specific biobots, deploy them
Speaker 3: into the ocean, and have them autonomously seek out and
Speaker 3: aggregate microplastics. They clump the plastics into easily retrievable basses,
Speaker 3: and then the bots themselves dissolve harmlessly into the ecosystem.
Speaker 2: That's incredible. But the medical applications of the human derived
Speaker 2: anthrobots that is where things get truly disruptive. We talked
Speaker 2: earlier about them acting as paramedics for neural tissue and
Speaker 2: a petri dish map that onto a human patient.
Speaker 3: Imagine a patient suffering from a severe spinal cored transsection
Speaker 3: or a traumatic brain injury. Today our options for neural
Speaker 3: regeneration are incredibly limited, but with this technology, a neurologist
Speaker 3: could take a simple swab of the patient's own tracheal
Speaker 3: cells just a swamp. They culture those cells in a
Speaker 3: lab induce them to form anthrobots and then deploy them
Speaker 3: directly into the spinal lesion.
Speaker 2: And because they are constructed entirely from the patient's own DNA,
Speaker 2: there is zero risk of immune.
Speaker 3: Rejection, exactly, no immunosuppress and drugs required. These personalized autonomous
Speaker 3: living machines navigate the wound topography, physically bridge the severed
Speaker 3: neural tracts, and secrete the exact localized biochemical signals required
Speaker 3: to stimulate the patient's own neurons to grow along the bridge.
Speaker 2: It's personalized cellular medicine.
Speaker 3: We could use them to seek out and dismantle acerroschlorotic plaques,
Speaker 3: and arteries. We could load them with specific chemotoxins, program
Speaker 3: their bioelectric target morphology to recognize the surface proteins of
Speaker 3: a specific tumor, and have them deliver the payload with
Speaker 3: microscopic precision.
Speaker 2: Weaving healthy tissue completely.
Speaker 3: Untouched, entirely untouched.
Speaker 2: They also represent a massive leap for pharmacology and drug testing, don't.
Speaker 3: They They do? Right now? We rely on animal models mice, rats,
Speaker 3: primates to test the efficacy and toxicity of new drugs,
Speaker 3: but a mouse's biochemistry is vastly different from a human's.
Speaker 3: Many drugs that cure cancer and mice fail catastrophically in
Speaker 3: human trials. Anthrobots offer a scalable, programmable platform of actual
Speaker 3: human tissue. You can create a swarm of human neurobots
Speaker 3: and test an Alzheimer's drug directly on their primitive neural networks,
Speaker 3: observing the real time synaptic response. It is faster, more accurate,
Speaker 3: and entirely circumvents the ethical dilemmas of animal testing.
Speaker 2: But and here's the catch, it introduces an entirely new,
Speaker 2: arguably much darker ethical dilemma because we are erasing the
Speaker 2: boundary between an evolved organism and an engineered machine. And
Speaker 2: this ties into a concept you mentioned earlier, basal agency.
Speaker 3: Basl agency, it's the idea that telling on me goal
Speaker 3: direct to behavior is not an exclusive property of complex brains.
Speaker 3: A single cell has goals. It wants to maintain homeostasis,
Speaker 3: it wants to survive. A tissue has goals it wants
Speaker 3: to achieve its target morphology. The anthrobots demonstrate that human tissue,
Speaker 3: when isolated, possesses a profound level of basal agency. It navigates,
Speaker 3: it solves problems, it heals.
Speaker 2: So if you're listening to this, you really have to
Speaker 2: confront this reality. We are taking human cells, your cells,
Speaker 2: we are placing them in a fluid, and they are
Speaker 2: spontaneously building a modal living entity, an entity that, as
Speaker 2: of twenty twenty six, can spontaneously generate a primitive neural
Speaker 2: network to coordinate its actions. It has goals, It acts
Speaker 2: with purpose. So what exactly is it?
Speaker 3: That's the problem. It doesn't fit our ethical frameworks. It
Speaker 3: wasn't born, it won't grow into a human being, It
Speaker 3: doesn't have a traditional life cycle, but it is composed
Speaker 3: of living human tissue, and it exhibits cognitive competencies.
Speaker 2: Do we owe it ethical consideration? If an anthrobot with
Speaker 2: a rudimentary neural network avoids a noxious chemical and a
Speaker 2: petri dish is experiencing a primitive form of suffering.
Speaker 3: We simply don't know. Our entire ethical philosophy is deeply
Speaker 3: tied to the presence of a centralized nervous system. When
Speaker 3: we distribute cognition, when we recognize that titu itself thinks
Speaker 3: and solves problems, the line between a biological machine we
Speaker 3: can dispose of and an organism we must protect completely blurs.
Speaker 2: And this ethical ambiguity is only going to compound because
Speaker 2: the pace of this research is accelerating exponentially.
Speaker 3: It is we are already moving toward automated.
Speaker 2: Discovery, AI driven robot scientists.
Speaker 3: Yes, we are building closed loop laboratory systems where an
Speaker 3: artificial intelligence designs a new biobot shape a robotic arm
Speaker 3: physically sculpts or manipulates the cellular medium to create thousands
Speaker 3: of iterations. The AI observes their behavior via microscopic cameras,
Speaker 3: and then it iteratively refines the design in real time.
Speaker 2: We are automating the evolution of entirely novel life forms.
Speaker 3: We are also looking at bidirectional interfaces integrating these biological
Speaker 3: constructs with digital systems. Imagine a synthetic biological neural network
Speaker 3: grown from human cells, physically wired into a silicon microchip
Speaker 3: acting as the cognitive processor for a drone or a
Speaker 3: digital environment.
Speaker 2: That is just science fiction becoming reality.
Speaker 3: We are tearing down the silos separating computer science, evolutionary biology,
Speaker 3: and cognitive philosophy. We're realizing that information processing and computation
Speaker 3: aren't just things that happen in silicon chips or human brains.
Speaker 3: They are the fundamental language of all biological matter.
Speaker 2: This has been an absolutely staggering journey. We started with
Speaker 2: ordinary frog skin cells stripped of their embryonic context, self
Speaker 2: organizing into motal machines. We saw how a supercomputer simulating
Speaker 2: fluid dynamics discovered kinematic self replication, a geometric form of
Speaker 2: reproduction completely alien to Darwinian history.
Speaker 3: We explored anthrobots.
Speaker 2: Right fully mature human wind pipe cells spontaneously assembling into
Speaker 2: autonomous paramedics capable of bridging severed nerves. And we dove
Speaker 2: into the invisible bioelectric software that governs this all forcing
Speaker 2: us to question whether biology is merely complex chemistry, or
Speaker 2: if it is a system actively navigating a vast platonic
Speaker 2: morphospace of ideal forms.
Speaker 3: The overarching takeaway is that these constructs zenobots, anthrobots, neurobots
Speaker 3: are not just novel feats of engineering. They are profound
Speaker 3: epistemological tools. They are microscopes that allow us to observe
Speaker 3: the hidden architecture of biological possibility.
Speaker 2: They show us what's really going on under the hood.
Speaker 3: They demonstrate that life is infinitely more plastic, more competent,
Speaker 3: and more agential than our standard mechanistic models have allowed
Speaker 3: us to believe the hardware is incredibly versatile. But the software,
Speaker 3: the bioelectric networks, and the abstract possibility spaces they navigate
Speaker 3: is where the true mystery of life resignes.
Speaker 2: Which brings us to a final provocative thought for you
Speaker 2: to ponder. We've spent this entire time marveling at what
Speaker 2: isolated frog cells and human tracheal cells can achieve when
Speaker 2: the suppressive signals of the larger body are removed. We've
Speaker 2: seen them build robots, invent new methods of replication, and
Speaker 2: spontaneously wire up primitive brains simply by shifting their coordinates
Speaker 2: in that vast possibility space.
Speaker 3: It's all about releasing those constraints.
Speaker 2: So consider the trillions of cells comprising your own body
Speaker 2: right now. If a handful of skin cells can be
Speaker 2: coaxed into becoming an autonomous healing machine, what dormant, unimaginable architectures, abilities,
Speaker 2: and entirely new forms of life are locked inside your
Speaker 2: own tissues, silently waiting for the precise electrical signal to
Speaker 2: awaken them.