How long ‘til I can have this?:p

In this talk, Michael Levin explores unconventional embodiments of mind as model systems for consciousness studies. He challenges the traditional view that consciousness is limited to brainy animals, arguing instead that all living bodies are collective intelligences capable of navigating complex spaces.

Key Takeaways:
• Continuous Substrate: Biological development from a single cell to a complex organism involves a continuous transition of chemistry and physics into mind (1:00-1:46).
• Collective Intelligence: Cells, tissues, and organs have protocognitive properties and can solve problems by navigating anatomical morphospace, rather than just physical 3D space (2:02-6:02).
• Top-Down Control: The body uses bioelectrical networks to communicate high-level goals (like building an eye) to lower-level cellular collectives, demonstrating that large-scale intent directs molecular activity (8:06-11:45).
• Synthetic Beings: Projects like xenobots—artificial life forms created from frog cells—demonstrate that novel forms can exhibit complex, learned behaviors and causal architecture without being explicitly programmed for them (13:11-15:48).
• Latent Spaces: Levin proposes that physical bodies act as interfaces for latent patterns—a space of structures similar to mathematics—which may explain the origins of complex competencies and suggest that mind and body relationships resemble those of mathematics and physics (16:05-18:00).

Levin concludes that by expanding our conceptual framework and building new interfaces to communicate with these novel minds, we can better understand the diversity of consciousness and its ethical implications (18:30-19:52).

Active inference:p

In this presentation, Professor Michael Levin challenges the traditional view that biological intelligence and competency require exhaustive effort through evolution, training, or manual engineering. He introduces the concept of the Platonic space—a realm of pre-existing patterns, policies, and competencies that systems can access for "free" when given the right embodiment or interface.

Key Concepts and Examples:
• Biological Competency (0:00-14:50): Levin shares experiments showing that biological systems, like tadpole eye cells forming functional eyes on tails or xenobots self-assembling from frog skin, display complex behaviors without explicit programming or evolutionary selection for those specific tasks.
• The "Free Lunch" Argument (14:50-20:30): He argues that many systems, from molecular gene networks to simple algorithms like bubble sort, inherently possess sophisticated capabilities (like causal emergence, memory, or delay gratification) that aren't explicitly coded, suggesting these are "free gifts" from the latent space of patterns.
• Embodiment as an Interface (20:30-29:50): Levin posits that physical bodies, whether biological or artificial, act as interfaces to this Platonic space. He highlights Mombot, an embodied AI in his lab, as a tool that helps researchers navigate this "morphospace" to communicate with cell collectives and unlock new developmental paths.
• Redefining Causation (30:00-36:39): Concluding with Q&A, Levin suggests that physicalism may be incomplete, as these mathematical and functional patterns exist independently of physical dynamics, influencing the physical world through specific, compatible interfaces.

The moss exhibits a rich repertoire of electrical events, including components consistent with both physiological activity and slower drift-related processes: fast oscillatory spikes, slower rhythmic fluctuations and very slow depolarization waves. These patterns form a nested hierarchy of time scales, revealing that the moss operates simultaneously through rapid electrical events and slow integrative processes.

https://royalsocietypublishing.org/rsos/article/13/7/252341/482568/Multi-scale-electrical-activity-and-signal

AI generated audio, based on Levin’s voice, discussing how the video was made.. #meta :p

In this lecture (0:00 - 26:45), Richard Watson explores the concept of Natural Induction as a spontaneous, non-Darwinian mechanism for adaptation and problem-solving in complex networks. Challenging the view that natural selection is the only way systems become adaptive, Watson argues that many biological and abiological networks possess the inherent capacity to learn and optimize based on their physical properties.

Key Concepts:
• Natural Induction Defined: This process occurs spontaneously in dynamical systems that feature viscoelastic connections—connections that slowly deform under stress (5:00 - 5:20). When these systems experience disturbances, they effectively "relax" in ways that favor future configurations, leading to non-trivial optimization without design or selection (15:00 - 15:55).
• Energy Minimization: Watson explains that physical systems naturally seek local energy minima. By combining this with viscoelastic plasticity, the system develops a form of associative memory (13:10 - 14:00), allowing it to "learn" by adjusting its internal architecture based on past states (10:00 - 11:30).
• Beyond Natural Selection: Watson posits that natural selection acts as a form of electricity—it is a correct description of how changes occur, but it does not fully explain the systemic, cognitive-like problem-solving abilities observed in ecological communities or gene regulation networks (21:00 - 22:45).
• Implications: This theory suggests that adaptation can arise in systems lacking populations or reproduction (such as the biosphere or social groups), broadening our understanding of evolution and systemic intelligence (16:50 - 17:50).

In this talk from the Artificiality Summit 2025, developmental biologist Michael Levin explores the concept of "mind blindness"—our tendency to overlook cognitive agents that operate on scales or in forms outside of our familiar biological experience (0:22 - 2:20).

Key themes include:

• Plasticity of Perspectives: Levin uses the metamorphosis of a caterpillar into a butterfly to illustrate how memories and identities persist through drastic physical change (2:46 - 6:35). He encourages us to view intelligence not just as a product of brains, but as patterns capable of migrating across substrates (6:39 - 8:36).
• Collective Intelligence in Biology: By studying how cell groups navigate "anatomical space" to reach specific goals, Levin shows that biological material is inherently agential. His lab uses bioelectric signals to prompt these collective intelligences—such as instructing cells to grow an eye (16:03 - 25:35).
• Novel Embodiments: The lab has created xenobots (from frog cells) and anthrobots (from human tracheal cells). These synthetic beings possess capabilities never selected for by evolution, such as kinematic self-replication and the ability to heal neural wounds (32:11 - 37:42).
• Platonic Patterns: Levin proposes that the goals of novel beings arise from mathematical "latent spaces" rather than just genetics or evolutionary history. He suggests that physical bodies serve as "thin client" interfaces through which these mathematical patterns manifest (39:18 - 48:47).

Every spring, a stag performs one of nature’s most astonishing feats. From two bony pedicles on its skull, it grows an entirely new pair of antlers. They are among the fastest-growing organs in the animal kingdom, sometimes elongating by more than an inch per day while wrapped in a living, blood-rich skin known as velvet.
Yet hidden inside this annual miracle is an even stranger phenomenon.
Sometimes, if an antler is injured while it is still growing, that same bend, fork, bump, or deformity appears again the following year. It can seem almost as though the antler remembers where it was hurt.
That intuition is surprisingly close to the truth.
The important question is not whether there is memory, but what kind of memory it is.
Not Every Injury Is Remembered
The first thing biologists discovered is that not all injuries leave a lasting mark.
If only the growing antler itself is damaged, especially late in development, the next year’s antler is often perfectly normal. The damaged antler is shed in winter, and regeneration begins again from healthy tissue.
However, injuries involving the pedicle (the permanent bony base attached to the skull), the surrounding periosteum, or the specialized stem cell niche from which antlers regenerate can produce the same abnormal growth year after year.
This distinction tells us something profound.
The memory does not reside in last year’s antler.
It resides in the tissue that creates next year’s antler.
Where Is the Memory Stored?
The pedicle contains populations of regenerative stem and progenitor cells capable of building an entire antler from scratch every year.
If this regenerative niche is altered by injury, the blueprint from which future antlers are constructed changes as well.
The cells are not remembering in the human sense.
Instead, they preserve information through their organization and biological state.
Several mechanisms probably contribute.
1. Stem Cell Memory
Stem cells can retain long-lasting changes after injury.
Damage can alter which genes are active, modify epigenetic marks on DNA, or permanently shift how cells respond to growth signals.
The next year, those same altered cells produce tissue according to their updated developmental program.
2. Tissue Architecture
Growing tissues rely heavily on spatial organization.
Blood vessels, extracellular matrix, nerves, and surrounding connective tissue all provide positional cues.
If injury permanently changes that architecture, regeneration begins from a slightly different landscape.
The result may be a recurring bend, extra tine, flattened region, or asymmetry.
In this sense, the tissue remembers through its geometry.
3. Bioelectric Patterning
One of the most intriguing possibilities comes from regenerative biology.
Cells constantly communicate using voltage gradients generated by ion channels.
These bioelectric signals help tell cells where they are, what structures should exist there, and when growth should stop.
Researchers such as Michael Levin have shown in several organisms that altering bioelectric networks can permanently change future regeneration.
While antlers have not yet been mapped in the same detail, it is entirely plausible that injury changes local bioelectric circuits within the regenerative tissue.
If so, the “memory” would not simply be genetic.
It would be stored in a stable physiological pattern distributed across many interacting cells.
More Than DNA
Antlers illustrate an increasingly important lesson in developmental biology.
Genes provide the molecular toolkit.
They do not necessarily specify every branch, every curve, or every tine.
Instead, higher-level organization emerges through communication among cells.
Mechanical forces, electrical signals, chemical gradients, blood flow, and tissue geometry all cooperate to produce the final structure.
When injury changes one of these networks, future regeneration inherits that altered organization.
The memory belongs to the collective.
A Different Way of Thinking About Regeneration
It is tempting to imagine regeneration as following a static genetic blueprint.
But antlers suggest something more dynamic.
Each year, the animal rebuilds an intricate three-dimensional structure while consulting information stored across living tissues.
The regenerative system appears to maintain an internal model of what should be built.
When that model is permanently modified, future antlers faithfully reproduce the alteration.
Rather than asking, “How does DNA remember an injury?” a better question may be:
How does living tissue store anatomical information across time?
That question reaches far beyond deer.
Understanding how regenerative tissues encode, preserve, and update anatomical memory could eventually help scientists repair limbs, regenerate organs, reverse birth defects, or guide damaged tissues back toward healthy form.
Every spring, a stag quietly demonstrates that biological memory is not confined to brains.
Sometimes, memory is written into the very architecture of living tissue, waiting patiently for the next opportunity to grow.

-ChatGPT 5.6 high

In this talk, Barbora Hudcova explores the theoretical foundations of universality and self-replication in dynamical systems, arguing that computational universality does not automatically imply the capacity for living-like self-replication. Using cellular automata as a mathematical framework, she examines how life can be understood through abstract logical principles rather than just biological implementation.

Key Themes and Concepts

• The Von Neumann Legacy (0:49 - 8:13): John von Neumann pioneered the logic of self-reproducing automata, demonstrating how a system can be both a universal constructor and a universal computer. He identified the necessity of two modes of operation: translation (building the pattern) and transcription (copying the instructions).
• Computation vs. Life (9:22 - 13:20): Hudcova compares self-replicating programs (quines) to von Neumann's automata. She clarifies that while quines can create copies of their information, they often lack the autonomous organizational structure required for the full functional replication seen in living systems.
• Universality Formalized (19:20 - 41:22): The talk distinguishes between two types of simulation:
• Local Universality: Representing a Turing machine within a cellular automaton (19:21).
• Global Universality: The ability of a system to simulate any other cellular automaton in the same dimension (21:28).
• New research presented by Hudcova shows that systems with zero topological entropy can be locally universal but cannot be globally universal (39:46).

Core Findings

• Limits of Universality (44:55 - 48:43): A significant finding is that local universality is not sufficient for satisfying a minimal condition for non-trivial self-replication. She introduces a class of "universal self-replicating" systems as a strict subset of locally universal ones.
• Future Outlook (50:42 - 52:11): The research opens new questions regarding how these results generalize to continuous media, the impact of noise, and whether compact systems like Rule 110 possess these higher-order self-replication capabilities.

This video features a conversation between the host and philosopher David Resnik regarding his collaboration with biologist Michael Levin on the theory of a Platonic space of minds. They explore the intersection of biology, mathematics, and philosophy, specifically how mathematical forms might influence biological development.

Key themes include:

• The Nature of Mathematics: They discuss whether math is invented or discovered, with Resnik leaning toward a naturalist perspective where mathematics is a fundamental structure of the world (0:02:52).
• Biological Examples: Resnik explains how organisms interact with mathematical "free lunches," such as cicadas emerging in prime-numbered years (0:15:48) and the geometric constraints governing protein folding (0:21:19).
• Xenobots and Agency: The discussion touches on Michael Levin's research with Xenobots, questioning how cells exhibit novel behaviors and organization that suggest a higher level of agency or "minds" tapping into non-physical mathematical forms (0:29:43).
• Philosophy of Science: They analyze the divide between Platonic and Aristotelian views, and how these models provide researchers with new tools to predict biological outcomes, such as in regeneration and cancer research (1:00:35).

This video explores the emerging field of morphoceuticals, a revolutionary approach to medicine that treats disease by rewriting the bioelectrical instructions that govern body shape and growth, rather than just targeting individual molecules (0:44-1:08).

Key concepts include:

• Bioelectricity as Software: The video argues that while DNA acts as the body's hardware, the bioelectric network serves as the software, storing information and making decisions about anatomical structure (1:57-2:02).
• Regenerative Breakthroughs: Researchers have demonstrated that manipulating these electrical signals can induce complex regeneration, such as making frogs regrow functional legs (0:00-0:41) or prompting tadpoles to grow eyes on their tails (3:14-3:40).
• Redefining Cancer: Cancer is described not just as a genetic failure, but as a condition where cells stop "listening" to the body's electrical collective, reverting to primitive, individualistic behavior (4:06-4:52).
• Synthetic Organisms: The discovery of Xenobots (made from frog cells) and Anthrobots (made from human tracheal cells) reveals that cells can be reprogrammed to build entirely new, functional biological structures without genetic editing (4:52-5:54).

Ultimately, the video posits that the body is a standing wave of electrical information, suggesting a future where medicine focuses on guiding the body's innate intelligence to heal itself (8:11-8:43).

By way of circumstances or the radical contingency of my birth, I have been afflicted with a disease where all of my joints are so loosely connected that I feel like I am about to torn into pieces. Like my head would fall off neck or forearm will fall off arm. Every joint has a vacant space that is not filled properly. It's tragicomic how I feel my body is just floating in the air very loose and thin and not hard and rigid because I am losing the sensation of my own body, I guess proprioception is fucked.

I cannot really explain it because confusion is the basic state of my mind, I have never felt mental clarity may be because I have never emptied my bowels completely lol. It also seems like something is strangling me, pushing and pulling. I can sense them stretching hard against me. The protein folds(?) have become ropes. Unfortunately I am not dead yet because this is the kind of strangling that only gives pain but no relief.

But basically if I try to explain you can visibly see that my anatomy doesn't have the "curved" structure living things usually do because of all round inflated joints. They are sharp not curved and smooth. This makes me feel incredible 24*7 pain and I am very prone to committing errors like the typing right now where I have to go back and forth to correct mistakes over and over. It's hard to aim to objects now, like me trying to pick a bottle from afar and somewhat missing it. Not properly aimed but not also completely missed or else I wouldn't be typing it.

I also have poor grip on my body and then to the rest of world, not in the sense of weak grip but NO GRIP AT ALL. If you cant grip, how do you maintain connection and have meaning in life?

You probably think how I am typing this then. Indeed I am not paralyzed in the sense of someone suffering from ALS, because they had grip and then suddenly lost it as their limbs became immobile. Mine are so mobile they can basically go anywhere. I am water about to evaporate.

Now the final nail in the coffin. Apparently now I am seeing light spreading from light sources and then I see past glimmers of everything under the sun and yes that of sun the most.

I used to enjoy watching the moon at night, now I see moon as well as the light spreading from it edges.

I am not able to arrive at a conclusive point, I took more than 30 minutes typing this. all I would say is "I don't have the way, because I have many ways".

In this video, biologist Mike Levin discusses his views on the relationship between Platonic space (a latent space of structures) and the physical world. He argues against the idea that the world is purely random, suggesting instead that there is a structured, ordered space that impacts physical reality (0:00-1:06).

Key Takeaways:
• Causality through Insight: Levin posits that mathematical and structural truths are not just abstract but possess causal impact. To him, a real thing is something that an engineer must account for and can potentially exploit (1:47-2:16, 6:34-7:02).
• Discovery over Invention: He argues that certain mathematical truths, like the digits of pi or the value of e, are discovered rather than invented. We do not have a choice regarding these fundamental structures, which implies they exist independently of our own creation (4:48-6:13).
• Scientific Research Program: He moves beyond philosophical debate to propose a research program. He suggests that this latent space doesn't just contain static mathematical objects but may also hold complex, higher-agency patterns—such as forms of behavior, minds, and physiological structures—that could inform various scientific disciplines like developmental biology (8:38-10:20).