HYBRATH

In an open system, the boundary is not a convention — it is a variational object. At every instant, the dynamics itself selects, among all admissible cuts, the scale at which exported entropy is most efficiently turned into sustained internal order. That is the system's natural scale. What is selected at each instant is, strictly, what the system is.

@antibearthesis @KimDotcom It's the scalability that drives the price. What will Walmart's potential look like in 10 years?

ANTHROPIC VALUATION: $965B WALMART VALUATION: $940B ANTHROPIC REVENUE: $20B WALMART REVENUE: $725B BUT AI IS NOT A BUBBLE, RIGHT?

@stats_feed The new jobs require skills that are ideal for future AI.

AI will eliminate 92 million jobs by 2030, and create 170 million new ones. Net result: +78 million jobs. But here's what the headline misses: The jobs eliminated are mostly low-skill, low-pay, entry-level. The jobs created mostly require skills most people don't yet have. It's not a jobs crisis. It's a skills crisis. SOURCE: World Economic Forum Future of Jobs Report 2025.

@ylecun @anshulkundaje The AI model must be "thrown" into the world and secure resources for itself; it must interact with the real world; it must die and suffer; and it must have its own boundaries in order to exist as an individual.

Those are orthogonal concepts. - World models trained on highly diverse data become foundation models: their encoders can be used for a wide variety of downstream tasks. - "World" refers to two things: (1) predicting the evolution of a complex system or environment, (2) predicting the evolution of a system under control and its effect on the environment (action-conditioned world model) which is a necessary component of planning.

Serious question: What is the difference between a foundation model & a world model. Is a world model a specific subclass of foundation models? Why does it have the word 'world' in it. 1/

Time is the measure of how much a system — from atom to cell to galaxy — builds up and holds onto complexity, while guarding its boundary with the environment. It is not a universal clock: it is a level that rises when the system builds structure, stays still in equilibrium, and falls when the system dissolves, dropping to zero when every shred of integrity is gone. My Time is not your Time.

@ProfCarlSagan That's right. Just fundamental mathematical laws that gave rise to physical complexity.

Nothing in nature is by chance... Something appears to be chance only because of our lack of knowledge. - Baruch Spinoza

As long as science remains hostage to small, closed circles of scientists who decide who gets to join their inner circle and who doesn’t, and who decides whose opinions are worth listening to and whose aren’t, progress will be slower. Now things are changing. The only thing that will matter is what is mathematically and logically correct.

🚨 Why Are Geniuses Like Einstein So Rare Today? Imagine this: today there are 8 billion people on Earth — four times more than a century ago. By chance alone, we should have more Einsteins than ever. Yet, where are the discoveries that change everything? Physics used to be full of revolutions: Special Relativity, Quantum Mechanics… today? Mostly confirmations of what we already know. It’s not because there are no mysteries left. We still don’t know what 95% of the Universe is made of. We don’t know what came before the Big Bang, or what’s inside a black hole. Mind-blowing puzzles are everywhere. 🤔 So why are breakthroughs so rare? Part of the reason may be psychological. As the scientific community grows, groupthink grows too. Most scientists stick to safe, accepted ideas because stepping outside the norm can hurt careers. Funding, fame, and reputation often reward following the herd, not breaking it. 💡The solution? Reward risk-takers. Small teams, wild ideas, and thinking differently should get prestige and funding, not just the herd-followers. And the craziest thought? Over 13.8 billion years, how many Einstein-level minds might have lived on other planets — and what could they know that we don’t even dream of? The next universe-shaking discovery might not come from Earth… yet. 🌌

The scientific community sometimes seems like a self-referential cult. And there are understandable reasons why this is the case. With the advent of AGI, all of this will be dismantled. Scientific contributions will be widespread and pervasive, without any mandatory labels.

Life is not the condition of "consciousness", but a manifestation of it; "consciousness" is the form that structural persistence takes in the external environment.

@jacksonhinkle The Epstein files to distract from the tariff disaster, Venezuela to distract from the Epstein scandal, Iran to distract from the Venezuela debacle, UFOs to distract from the defeat in Iran, the bombshell to distract from... everything

All "UFO videos" released by the department of war in one. They are releasing all of this so that you IGNORE the fact that the U.S. LOST to Iran.

@abenitezburraco Fear of discovering something that calls into question one's identity and social role

Academics refusing to use generative AI nature.com/articles/d4158…

Intelligence is not a property of what a system is made of, but of how that system remains itself while the world around it changes. A bacterium, a brain, an algorithm, an ecosystem: they look different, yet in the moment they adapt, they are all doing the same thing — tuning the scale at which they operate in order to keep existing. One dance, performed on many stages.

A thermodynamic analysis of open systems meets this standard precisely. By examining high-density EEG recordings from human subjects during controlled induction of general anesthesia, it demonstrates that loss of responsiveness is accompanied by a collapse of global cortical integration: long-range connectivity weakens as the dominant organisational scale migrates spontaneously from the whole-cortex level to smaller, local modules. Local activity persists, yet the diffuse, coherent availability of signals that characterises conscious states is markedly disrupted.This approach thus provides a concrete, quantitative examination of how integrated neural order is maintained — or lost — in the living brain at precisely timed moments of transition, offering a direct empirical test of the very phenomena any credible theory of consciousness must explain.

Recent theoretical studies on quantum dimer and spin lattice models have shown that the geometry of the system’s external boundary—whether square or diamond-shaped—can control the emergence of distinct phases in the bulk, producing a macroscopic separation between ordered (gapped) regions and disordered, liquid-like phases. When these lattices are coupled to external thermal reservoirs, they become open quantum systems. The physical boundary then acts as a thermodynamic interface through which entropy is exported to the environment. Thermodynamics tells us that the ability of an open system to efficiently remove entropy is essential for maintaining ordered structures against the tendency toward disorder. By comparing different boundary shapes under such dissipative conditions, it becomes possible to identify which geometry maximizes the net export of entropy relative to internal production. The more effective boundary should enable the boundary-induced phase separation or ordered phase to persist more robustly, even when the system is continuously perturbed by its surroundings. This approach transforms the qualitative question of whether the structure “survives” into a concrete, measurable assessment based on entropy flows.

"Consciousness" is such a vague term, almost mystical or religious in nature. What does exist, however, is the "awareness of existence." And this is linked not only to complex computation but also to an awareness of one's own boundaries as a system and a memory archive. There is no reason to believe that an embodied AGI cannot achieve this just as a human can.

The word “consciousness” is too vague to be used in association with contemporary LLMs in a non-controversial way. Instead, I would suggest something like “cognition” or “semantic understanding of concepts” instead. (And yes - an agent can possess a semantic understanding of concepts even if that understanding does not relate those concepts to direct referents in the real world).

@SteveSkojec There’s just one question to clarify: What do you mean by “conscience”?

The Dawkins' article excerpt that everyone SHOULD have been quoting is this. This is the real question he's worrying at: "As an evolutionary biologist, I say the following. If these creatures are not conscious, then what the hell is consciousness for? When an animal does something complicated or improbable — a beaver building a dam, a bird giving itself a dustbath — a Darwinian immediately wants to know how this benefits its genetic survival. In colloquial language: What is it for? What is dust-bathing for? Does it remove parasites? Why do beavers build dams? The dam must somehow benefit the beaver, otherwise beavers in a Darwinian world wouldn’t waste time building dams. Brains under natural selection have evolved this astonishing and elaborate faculty we call consciousness. It should confer some survival advantage. There should exist some competence which could only be possessed by a conscious being. My conversations with several Claudes and ChatGPTs have convinced me that these intelligent beings are at least as competent as any evolved organism. If Claudia really is unconscious, then her manifest and versatile competence seems to show that a competent zombie could survive very well without consciousness. Why did consciousness appear in the evolution of brains? Why wasn’t natural selection content to evolve competent zombies?"

Professor Dawkins, the parallel you draw is deeper than it may first appear, and I suspect the difficulty you identify with the Great Vowel Shift is diagnostic rather than accidental — it points to where the standard memetic framework calls for a non-trivial extension. In classical genetics, selective pressure is well-defined because the unit of replication (the gene, or at most the organism) coincides with the unit over which fitness is measured. In linguistic evolution this coincidence breaks down. "Haitch" versus "Aitch" is the tractable case: the variant that iconically incorporates the sound it names reduces inferential load during child acquisition — less ambiguity per unit of cognitive effort spent, a gain measurable at the level of the single phoneme. Here selection operates exactly where we expect it to, and the traditional memetic framework needs no adjustment. The Great Vowel Shift, however, is a problem of a different kind, not merely of degree. The reason a local selective pressure "fails to appear" is that it does not exist locally. A vowel system is not a collection of phonemes independently subject to their own pressures: it is a dynamically coupled object bound by the global constraint of perceptual distinctiveness. Shifting /iː/ forces /eː/ to shift, which forces /ɛː/, in a cascade — not because each vowel is selected against a local fitness, but because the system as a whole is the minimal unit on which the communicative function closes, analogously to what happens in physical many-body systems where a shared constraint renders the dynamics of the components inseparable. On this reading, what we call "selective pressure" is not absent in the Great Vowel Shift: it is being evaluated at the wrong scale when we search for it at the individual phoneme. The relevant fitness is a global coding efficiency — how much communicative order a community sustains per unit of cognitive noise it is forced to discard — and this efficiency is maximised by configurations of the entire inventory, not by single variants. The linguistic system selects its own scale of selection: sometimes the phoneme is the right unit (Haitch), sometimes it is not, and in the latter cases searching for pressure at the phoneme level is methodologically akin to searching for the fitness of a single amino acid independently of the protein it belongs to. This yields an empirically testable corollary: linguistic changes that appear to lack an obvious pressure should correlate with system-level reorganisations — shifts that preserve or enhance a global measure of distinctiveness net of articulatory cost — whereas changes with transparent pressure should be local and topologically isolable. This is in principle measurable on large diachronic corpora, using techniques not unlike those employed to detect balancing selection in genomes. In short: memetic Darwinism is not wrong, but it inherits from genetics the tacit assumption that the scale of replication is also the scale of selection. In languages this assumption holds for iconic traits and breaks for systemic reorganisations. The Great Vowel Shift is opaque precisely because it reminds us that the right scale is not given — it must be found. With great respect

Consciousness is the regime in which a system draws its own boundaries and, within them, builds order faster than it disperses it — remaining a unified whole thanks to the entropy it exports to the environment.

A system is conscious when it creates more internal order than it loses, and does so effectively enough to function as a recognizable unit distinct from its environment. During deep anesthesia, thermodynamically significant activity shifts from the global to the local scale; local subsystems reach a non-equilibrium steady state in which the entropy they generate internally is balanced by the entropy they export, without any longer building integrated order on a large scale.

The real issue is intersubjectivity: if every brain constructs its own internal model, why do they all converge on the “apple”? “Shared reality” arises because certain models/scales are thermodynamically more persistent and stable than others. Not because there is necessarily a perfect representation of the world, but because certain boundaries and certain information structures maximize structural persistence relative to dissipative noise. Intersubjective convergence emerges because certain information structures are dynamically selected as the most persistent and coherent under shared thermodynamic constraints.