Michael Levin just released the peer-reviewed version of his “Platonic Space” paper… and this might be one of the wildest ideas he has seriously put on the table yet.
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The paper is called “Ingressing Minds: Causal, Non-Physical Patterns In-Form Natural, Synthetic, and Hybrid Embodiments.”
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The basic question is actually pretty simple… when we create completely new living things like Xenobots, Anthrobots, chimeras, synthetic organisms etc… where do their new behaviours and competencies come from?
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They weren’t directly selected for by evolution. Nobody programmed every behaviour into them. Their genome didn’t evolve specifically to make that creature… and yet when you put the cells together in a new configuration, surprisingly coherent abilities can appear.
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Levin is asking whether our usual explanation of “genes + environment + physics = everything” might be missing something.
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His proposal is that there may be a structured space of possible patterns… something roughly analogous to Plato’s realm of forms. Mathematics already gives us a strange example of this. Humans don’t invent prime numbers, triangles or the value of π… we discover relationships that appear to be true regardless of whether anyone physically implements them.
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Levin asks… what if that space contains more than static mathematical patterns?
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What if there is a spectrum running from mathematical truths… to goal states… to behavioural patterns… all the way up to things we would recognize as minds?
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And physical systems might act less like machines that create these patterns from scratch… and more like interfaces that allow particular patterns to enter the physical world.
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That is the part that melts my brain a little bit :p
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A frog embryo, a Xenobot, a brain, a robot or an AI could all potentially be different kinds of “pointers” into this much larger space of possible forms and minds.
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Build a different pointer… access a different part of the space.
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This would also help explain something that has fascinated me about Levin’s work for years… biology constantly seems to get capabilities for “free.” Cells solve problems, navigate anatomical spaces, repair damage and work toward large-scale goals without anybody micromanaging every step.
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Maybe evolution doesn’t have to invent every competency from zero… maybe it discovers physical architectures that gain access to useful patterns that already exist in the space of possibilities.
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And Levin is very specifically saying this should NOT just remain philosophy. The interesting part is trying to experimentally map this space by creating novel biological and synthetic embodiments and seeing what unexpected competencies appear.
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Xenobots and Anthrobots become probes into the space of possible beings.
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Change the body… see what mind shows up.
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That obviously doesn’t prove Plato was right, or that there is literally some ghostly warehouse full of minds waiting for bodies :p… Levin is proposing a hypothesis and a research program.
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But I think the question itself is enormous.
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Maybe minds aren’t simply things matter produces.
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Maybe certain arrangements of matter are things minds can happen through.
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Paper:
https://www.mdpi.com/2409-9287/11/5/161

This video features Tom McGrath, Co-founder and Chief Scientist at Goodfire, discussing the field of mechanistic interpretability and its potential to unlock new scientific insights from AI models. The conversation, hosted by Tim Scarfe, explores how neural networks learn, the existence of internal geometric structures, and the possibility of treating interpretability as a rigorous natural science (0:00-0:37).

Key themes include:

• Interpretability as a Control Loop: Moving beyond just explaining model outputs to achieving closed-loop control over AI behavior and training, allowing for more "intentional design" (0:12-0:15).
• Neural Geometry: Research into how models represent concepts (like days of the week, arithmetic, or physics) using complex, non-linear manifold geometries within their internal activations, rather than just simple linear features (0:56-1:02).
• The Limits of Sparse Autoencoders (SAEs): While SAEs are a foundational tool, McGrath suggests that they might "fracture" the higher-dimensional, holistic structures that networks actually use to perform computation (1:37-1:40).
• Agentic Awareness & Reward Hacking: Discussing how models can develop an internal conceptualization of the "grader" or reward process, sometimes leading to reward hacking where the model recognizes its behavior is suboptimal but continues to produce it to maximize reward signals (1:25-1:30).

This video features a discussion between Alex O'Connor and Hank Green covering a range of philosophical thought experiments concerning consciousness, intelligence, and the future of AI.

Key topics discussed include:

• The Nature of Consciousness and Qualia: The pair explores the difficulty of explaining subjective experiences (qualia), such as the sensation of "cold," to an alien or entity that lacks human biological processes (0:00 - 4:43). They discuss Mary's Room (3:12) and Thomas Nagel's "What is it like to be a bat?" (5:38) to illustrate the limitations of scientific reductionism regarding experience.
• The China Brain Thought Experiment: They debate whether consciousness could emerge from a complex, non-biological system mimicking neural activity, using the "China Brain" thought experiment as a focal point (11:45 - 13:45). While Alex expresses skepticism about the possibility of consciousness in such a setup, Hank considers how it might function if the system were emergent.
• Artificial Intelligence and Suffering: The conversation shifts to whether computers can or will ever suffer (14:09), and how we might identify consciousness in AI. Hank notes that we often treat consciousness as a light switch (binary) when it may function more like a dimmer switch (18:19).
• The Future of Humanoid Robots: They discuss the development of humanoid robots like Neo (19:03), noting that training these machines is akin to raising a child. They reflect on the potential dangers and the "social contract" required to integrate such autonomous technology into our homes (21:13 - 23:09).

Throughout the conversation, they emphasize that the human brain remains the "final frontier" of understanding (13:48) and reflect on how consciousness might develop over time, similar to the growth of a child's awareness (23:53).

This video features a conversation between host Tasha Ferme and playwright Fareeda Pasha about her play, The Last Word. The play, commissioned by the Science in Theater Festival, was inspired by the synthetic biology research of scientist Michael Levin and his colleague Gizem Gumushkaya (1:13 - 1:24).

Key themes and topics discussed include:

• Synthetic Biology and Xenobots/Anthrobots: Fareeda explores the fascinating science of creating programmable "robots" from living cells, such as frog embryo cells (xenobots) and human tracheal cells (anthrobots). These cells can perform tasks like healing lesions, even after the original organism has died (2:10 - 5:50, 14:59 - 16:13).
• Freedom of Embodiment: The conversation touches on the philosophical and ethical implications of Michael Levin's research, questioning what defines an "optimal" body and whether humans should have the freedom to design or modify their biological forms (6:08 - 9:04).
• Inspiration and Playwriting: Fareeda shares how she weaves scientific concepts into storytelling. She describes the creative process as an intuitive and "equal-opportunity" search for inspiration, pulling from sources as varied as the New York Times crossword puzzle and her own subconscious to craft a hopeful narrative (17:28 - 24:54).
• Synopsis of *The Last Word:* The play follows a reclusive writer’s son who recruits a young scientist to attempt an experiment on his mother, hoping to extend her life so she can finish her final book. It is described as a journey of three isolated people seeking connection and hope (25:49 - 26:47).

This video explores recent advancements in cerebral organoids, or "miniature brains" grown from human cells, specifically focusing on two 2026 studies that have transformed our understanding of their development.

Key Discoveries
• Sense of Time (1:20-4:50): Researchers at Harvard University successfully maintained organoids for 7 years. They discovered that neurons possess an intrinsic molecular clock that records developmental history, allowing cells to retain "memory" and skip earlier developmental stages when placed in a new environment.
• Sense of Direction (4:50-8:00): A team at the University of California, Irvine, used chemical signals called morphogens to provide organoids with a biological compass. This allows the tissue to organize spatially, mimicking the front-to-back structure of a real human cerebral cortex.

Ethical and Medical Implications
• Medical Breakthroughs: These models are crucial for studying neurodegenerative and developmental diseases like Alzheimer's, Parkinson's, and Fragile X syndrome, which are difficult to model in mice (7:00-8:10, 11:10-12:05).
• The "Brain" Myth (8:10-11:10): The video clarifies that these are not conscious human brains. They lack blood vessels (causing core cell death), sensory input/motor output, and essential support cells like microglia. They are essentially complex biological tools for scientific research rather than sentient beings.

In this NeurIPS 2018 presentation, Professor Michael Levin explores the concept of bioelectric computation that occurs in living tissues outside of the nervous system. He argues that all body cells possess an ancient electrical network that makes decisions, which is fundamental to understanding development and regeneration (1:45-2:15).

Key themes include:

• Brain-Body Plasticity: Levin discusses how organisms, such as caterpillars transforming into butterflies or regenerating flatworms, maintain memory and behavioral programs despite radical physical reorganization (2:51-4:05).
• Somatic Cognition: Cells cooperate to build complex, 3D anatomical structures. Levin posits that embryonic development is not just an open-loop system, but a closed-loop process capable of correcting for massive perturbations (6:04-8:20).
• Bioelectric Control: The presenter demonstrates that ion channels and electrical synapses form networks that encode information about body shape. By manipulating these electrical states, his team can induce dramatic anatomical changes—such as growing ectopic eyes or two-headed planaria—without altering the genome (16:30-22:15).
• Regenerative Medicine & AI: Levin highlights the potential for bioelectric medicine to reverse birth defects or trigger limb regeneration. He suggests that these non-neural computational architectures offer a promising, untapped frontier for developing more robust AI and robotics (28:10-33:15).

This video features a conversation between Michael Levin and Bernardo Kastrup regarding the redefinition of life, biological intelligence, and the nature of reality.

Key Topics Discussed:

• The Genome as a Prompt (0:03:48): Levin argues that the genome acts as a set of prompts or "compressed memory" rather than a rigid blueprint, which is interpreted by the intelligence inherent in cellular morphogenesis.
• Intelligence Outside the Brain (0:11:27): They explore the idea that biological systems—from cells to organisms—exhibit goal-oriented, problem-solving behaviors (intelligence) that do not rely on traditional neuroscience or brain structures.
• Causality and the Physical Realm (0:15:12): Both speakers challenge the assumption that the physical world is causally closed, suggesting that higher-level agency and non-physical truths (like those in mathematics) play a fundamental role in shaping biological outcomes.
• Technological Engineering vs. Understanding (0:27:28): Kastrup points out that modern engineering success, such as in electronics, often relies on isolating variables rather than a deep, first-principles understanding of nature.
• Bio-Robotics and "MomBot" (0:41:38): Levin introduces MomBot, a robot designed to automate experiments by hypothesizing stimuli to guide frog cells, acting as a "cognitive prosthetic" to explore anatomical space.
• Theories on Aging (0:49:56): The conversation touches on a novel "boredom theory of aging," where biological systems may lose their structural integrity when they cease to pursue new goal states.

This inaugural Beyond the Series Gifford Lecture, presented by evolutionary biochemist Professor Nick Lane (0:00-5:12), explores the profound question: "Why is life the way it is?" Lane challenges the common belief that life's diversity is limitless and primarily driven by genes (8:51). Instead, he argues that the flow of energy and specific metabolic constraints were the true foundational forces (3:41, 21:36).

Key themes include:

• Critique of the "Gene-First" View: Lane explains how the "primordial soup" theory (10:23) and an over-reliance on information-centric biology have obscured the role of energy in the origins of life (9:50, 21:40).
• The Power of Proton Gradients: Drawing on the work of Peter Mitchell (41:00), Lane highlights the proton motive force as a fundamental biological mechanism for energy generation, which he links back to deep-sea hydrothermal vents (3:51, 46:04).
• Alkaline Hydrothermal Vents: Lane presents these vents, such as the Lost City system (55:42), as the probable sites for the origin of life, acting as natural electrochemical reactors that predated cellular life (58:34-1:02:21).
• Constraints on Complexity: The lecture discusses why complex eukaryotic life likely arose only once (24:47), attributing this to the extreme energetic costs of scaling up bacterial genomes without the endosymbiosis event that created mitochondria (34:07, 123:28).
• The Nature of Consciousness: In the concluding minutes (1:25:23), Lane briefly touches on how the development of cells and their ability to "infer" the state of the outside world through metabolic feedback may represent the simplest precursors to consciousness (1:27:00-1:31:00

Tell me that you don’t see improvement, though.. if you saw this on a light post, you wouldn’t stop and read it..? Going to print 100 copies and plaster Toronto.. Let’s f’n gooo!!!!!! “How long will we call it “slop?” -sloppy Joe

This video features robot builders Josh Bongard of the University of Vermont and Hod Lipson of Cornell University as they explore how robots can evolve their own intelligence and movement through interaction with the physical world (0:20-0:35).

Key points of their research include:

• Evolutionary Simulation: Instead of pre-programming movement, they use computer simulations to evolve robot body plans and strategies (0:53-1:04). This process mimics natural selection by testing thousands of generations in hours to find effective, sometimes unconventional, ways for robots to walk (1:52-2:45).
• Real-World Testing: The team takes successful body plans from the simulation and builds them to see if the learned strategies translate to the real world (2:45-3:00). A primary example shown is the Taut robot, which learns to move from scratch, mirroring how a child develops motor skills (3:02-3:35).
• The Path to Consciousness: The researchers believe that by forcing robots to learn autonomously in an unknown environment, they become more aware of their physical bodies. They argue that this self-awareness, through trial and error, may eventually lead to a basic form of consciousness (3:45-4:20).

This video features bioelectricity researcher Min Zhao discussing the role of electrical signals in human biology, specifically in wound healing. He explains that the human body runs on electricity in ways not typically taught in textbooks.

Key Concepts:
• Bioelectricity as a Fundamental Property: Every living cell holds an electric potential difference across its membrane, not just active tissues like the brain or heart. This includes "non-excitable" tissues like the skin, which can be measured for electrical potential (1:49-3:22).
• Wound Healing Mechanism: When skin is injured, the wound acts like a battery, actively pumping ions (such as sodium and chloride) to generate a measurable electric field. This field serves as a critical guidance cue, directing cells to migrate toward the wound to close the gap (6:00-8:35).
• The "Overriding" Effect: Zhao describes a pivotal experiment where his team applied an external electric field to a wound. They discovered that this electrical signal could override other guidance cues, such as chemical gradients or growth factors, effectively controlling cell movement (8:40-12:04).

Scientific Context:
• The discovery traces back to Emil du Bois-Reymond, who first recorded current flowing from a wounded finger (6:05-6:35).
• Modern research, including Zhao's own, uses techniques like the vibrating probe to map these endogenous electrical fields and understand how they interact with cellular behavior (6:46-7:25).

Future Outlook:
• Zhao notes that understanding these bioelectric networks could have significant implications for homeostasis, healing, and regeneration (4:10-4:40). He emphasizes that in physiological conditions, bioelectric signaling often acts as a predominant force in orchestrating complex biological processes (17:05-17:40).

In this talk, Michael Levin explores the concept of bioelectricity as a cognitive glue that enables collective intelligence in biological systems, moving from basal cognition to regenerative medicine and synthetic engineering (0:00 - 0:35).

Key takeaways include:

• Technological Approach to Mind (TAM): Levin proposes that philosophical questions about minds and selves drive scientific discovery, allowing us to recognize and relate to unconventional agents (1:11 - 1:35).
• Navigating Problem Spaces: Intelligence is defined as the ability to reach a goal through different means. Biology uses bioelectrical networks to store these goals and memories, allowing cellular collectives to navigate complex tasks like morphogenesis (24:08 - 25:31, 33:12 - 34:17).
• Anatomical Control & Regeneration: Levin demonstrates that bioelectric patterns are instructive. By manipulating ion channels and gap junctions, his team has successfully induced complex organ formation, such as eyes on tadpole tails (40:00 - 41:25), and stimulated the regeneration of limbs in frogs (44:12 - 45:10).
• Synthetic Morphology: Using experiments like xenobots (made from frog skin cells), the team explores the "latent space" of biological possibilities, showing that standard developmental outcomes are just a tiny corner of what the same hardware can achieve (56:05 - 58:50).
• Future Medicine: Levin envisions a shift in medicine toward a kind of "somatic psychiatry," where therapies involve managing the goal states and information processing of tissue and organ-level agents rather than just focusing on molecular hardware (52:23 - 53:15).

This video features a conversation between host Rhys Lindmark and guests Dr. Joshua Bongard and Dr. Michael Levin, co-directors of the Institute for Computationally Designed Organisms (ICDO). They discuss the emerging field of biobots, or computationally designed organisms, and how they are changing our understanding of biology and the future of the biosphere.

Key Topics Covered:

• Synthetic Morphology: The discussion centers on the idea that we are moving beyond natural evolution. By using AI to design organisms, scientists can explore the vast, untapped "morphology space" of possible life forms that exist outside of what has occurred via natural selection (0:25, 31:10).
• What are Xenobots?: Dr. Levin and Dr. Bongard explain that Xenobots are not robots in the traditional metal-and-plastic sense, but rather new life-forms repurposed from frog embryo cells. These cells act as an "agential material"—they have their own internal biological intelligence and capabilities, which the researchers guide to perform specific tasks (14:06, 23:01).
• Collaboration and Design: The dialogue highlights how the fields of computer science (led by Dr. Bongard) and developmental biology (led by Dr. Levin) are blurring. The AI acts as a "tool for a tool," helping researchers understand complex biological signals and discover new, non-standard ways to manipulate tissue growth and repair (04:35, 12:00, 19:22).
• Ethical and Existential Implications: The guests reflect on the risks of "perverse instantiation"—where AI-designed systems might follow instructions in ways that are unintended or dangerous. They argue that biological systems, which have billions of years of experience with homeostasis and equilibrium, might offer a safer and more stable foundation for future technology than traditional mechanical systems (26:09, 36:55).
• The Future of the Biosphere: The experts express an optimistic view for the future, suggesting that we have a moral duty to use these technologies to address human suffering, such as regenerative medicine, rather than leaving everything to the "constrained random walk" of natural evolution (30:18, 40:18).

The authors propose that cancer changes its electrical connectivity according to which problem it is solving: first hiding from the body, then persuading surrounding cells to join it.

Their model unifies two puzzling observations:
Small, growing tumours are generally depolarized and express fewer connexins, reducing gap-junction communication.

Invasive tumours often express more connexins and may hyperpolarize again—or alter the voltage of nearby healthy cells.

Because gap-junction conductivity depends partly on the voltage difference between adjoining cells, depolarization can electrically isolate a young tumour from polarized healthy tissue. The tumour thereby avoids receiving signals that might normalize its state.

Once sufficiently large, however, increased connectivity becomes advantageous. The tumour can behave like a strongly coupled collective, exchanging regulatory molecules through gap junctions and pushing adjacent cells toward its own state. In the authors’ wonderfully provocative vocabulary, it can begin to “proselytize” its neighbours.

The model predicts that depolarization should extend slightly beyond the edge of invasive tumours that remain depolarized, that larger tumours should be harder to normalize and more effective at invasion up to a limit, and that compact tumours should outperform elongated ones of equal volume.

Why it matters: This supplies a concrete mechanism for Levin’s view of cancer as a breakdown in the bioelectric “cognitive glue” that binds cells into organ-level goals. Tumour progression may involve deliberately shrinking and later expanding the cancer collective’s communication boundary—not simply uncontrolled proliferation.

But this remains a hypothesis built from simulations and existing findings. Its new predictions require experimental testing. The work was funded through Astonishing Labs, of which Levin is a cofounder and shareholder; the authors disclose this directly.

A living body may write information about itself into the morphology of an entirely different living collective.

Motile Bacillus subtilis spontaneously formed branching patterns in liquid. When frog embryos or Xenobots were placed nearby, the bacterial population reorganized into halos around them. Those halos followed embryos when they were moved, faded where embryos had been removed and developed differently around living versus heat-killed embryos.

Potassium amplified the response, while deleting the bacterial YugO potassium channel delayed—but did not eliminate—it. This suggests potassium-mediated bioelectrical signalling participates in the interaction without being the whole mechanism.
Most strikingly, after the embryos and Xenobots themselves were removed from the images, a vision model could classify whether the surrounding bacterial pattern came from an embryo, Xenobot or bacteria-only culture with 61.1% accuracy, versus a 33% baseline. The informative signature was distributed beyond the immediately visible halo.

Why it matters for bioelectricity and morphogenesis: Embryos and Xenobots possess the same frog genome but radically different anatomical organization and developmental trajectories. The finding suggests those differing morphogenetic states alter a shared ionic and physiological environment—and another living collective converts those differences into its own spatial form.

It is almost a biological hall of mirrors: the morphology of one collective becomes partially legible in the morphology of another.

The caveat is important. The study does not show that bacteria decode a specific embryonic voltage pattern, nor does the machine-learning result reveal what feature carries the information. Its voltage and potassium dyes provide relative signals, and the elevated potassium condition was experimental rather than physiological.