Roger Penrose argues scaling computation won't create consciousness. Sentiment: ~37% supportive, ~39% confronting. Discussion on physics, AI and limits.
Adding more GPUs will never make a machine conscious. Nobel Prize-winning physicist Roger Penrose just dismantled the entire AI race’s core assumption. Right now, the industry operates on one belief. Build massive data centers. Scale the models. AGI will just “wake up.” Penrose destroys this completely. Penrose: “There is this sort of view that once you make a computer complicated enough or something, it suddenly becomes aware. I just don’t believe that. There’s no reason to believe that.” A machine can compute better than any human alive. But computation is not awareness. Penrose: “There is something quite different involved in understanding things, in being aware of things, of feeling things, which is not part of computations.” We’re confusing rule-following with actual intelligence. Penrose: “The keyword is the word ‘understanding.’ You can follow rules alright, but we don’t understand what we’re doing. The understanding is the key point.” Models today are exceptional at processing data. At mimicking logic. But true understanding requires consciousness. Penrose: “It doesn’t make sense to say of a device that it understands something if it’s not even aware of it. There is something much more profound in being conscious of something.” And here’s what should terrify every AI lab on earth. Penrose: “I believe that the brain is following the laws of physics, sure. We don’t have a good picture of the laws of physics.” Penrose: “Quantum mechanics is not an answer to the way the universe operates. It’s a partial answer. It’s incomplete.” We’re trying to engineer synthetic consciousness using classical computation. While biological consciousness likely operates on physics we haven’t even discovered yet. The race to AGI isn’t just an engineering problem. It’s a frontier science problem. The labs are hiring engineers. The problem might require physicists who don’t exist yet.
Real-time analysis of public opinion and engagement
What the community is saying — both sides
Many replies endorse Penrose’s claim that piling up GPUs or parameters won’t “flip the switch” — users repeatedly argue that raw compute alone cannot generate subjective experience.
A clear split appears between task competence and inner life — commenters invoke Searle, Gödel and the Chinese Room to say models can behave intelligently without having qualia or true understanding.
Numerous people warn that unconscious systems can still cause real harm if they gain goals, tools, feedback loops and scale — the risk path is “scale → utility → deployment,” not “scale → consciousness.”
Many suggest biology, wetware, quantum effects or undiscovered physics might be required for consciousness, arguing we should explore alternative substrates and designs rather than only larger silicon models.
Replies criticize venture and marketing narratives that treat scaling as a miracle path to AGI, calling the belief almost religious and warning it may steer research down the wrong route.
Several voices emphasize sensory influx, real-time embodiment, memory replay and bodily needs (even “suffering”) as central to consciousness — aspects current LLMs lack.
Users urge more philosophical, ethical and interdisciplinary input — the suggestion is that engineers alone can’t resolve foundational questions about mind and value, and humility is needed on all sides.
Some propose evolving simple agents in sandboxes or radically different architectures rather than skipping “billions of years” of evolutionary design through brute force scaling.
Many acknowledge that regardless of consciousness, present AI is already reshaping society and accelerating change; regulation and careful deployment are urged even for non‑sentient systems.
A minority frame consciousness as supernatural or spiritual (souls, God), while others remain agnostic — but across perspectives there’s broad respect for Penrose and a demand for deeper inquiry.
Penrose's quantum-consciousness claim is widely rejected — many replies call his microtubule/quantum arguments speculative or fringe, arguing there's no empirical evidence and that invoking new physics shifts the burden away from neuroscience and systems theory.
Consciousness is not seen as required for AGI or practical capability — lots of people point out that machines can outperform humans on tasks without subjective experience, and that usefulness, not qualia, drives development and deployment.
A significant minority insists AI may already show forms of awareness or will do so soon — respondents vary between “LLMs are already person‑like,” “different kinds of consciousness are possible,” and skepticism about any definitive test for subjective experience.
scale-plus-compute versus architecture and embodiment — many emphasize scaling, persistent memory, multimodal sensors, and algorithmic innovations (symbolic integration, recursive self‑models) as competing or complementary paths.
some urge a “protect first, prove later” stance, worry about the undesirable implications of creating conscious machines, and argue companies would rather avoid true consciousness for legal and moral reasons.
Calls for empiricism and interdisciplinarity — numerous replies demand evidence over belief, encourage input from psychologists, philosophers, and cognitive neuroscientists, and criticize appeals to authority or intuition as insufficient.
The conversation is highly polarized and often blunt — expect a mix of technical rebuttals, confident predictions, religious/spiritual takes, and sharp insults, reflecting strong disagreement about both facts and values.
Most popular replies, ranked by engagement
With all due respect to Penrose regarding his other domains of expertise, he's been banging on this particular drum for decades, and it's never made the slightest bit of sense to anyone who understands neuroscience, or cognitive science, or AI. It's just pseudo-scientific gobbledy-gook.
@r0ck3t23 He’s merely expressing his own thoughts (wishes?), without anything to back it up other than conjecture. How is this a “dismantling?”
@r0ck3t23 I’m tired of explaining what I’m building, so instead I’ll just put this demo video here, this is not an llm, doesn’t use transformers, I can remove knowledge instantly without retraining, it works like a brain. https://t.co/4fd7Ap39SK
@r0ck3t23 Yes. Well this idea that “more” compute is what is needed to reach AGI was debunked by @DavidDeutschOxf a decade and a half ago. https://t.co/pVJ4bvUNRA And here’s further explanation: https://t.co/HAGpDqz2Oa
Penrose is shaking up the foundations of physics, the modern dogma of "computational consciousness." No matter how powerful the GPUs we line up, it will never go beyond the realm of "highly sophisticated computers." I feel that the time has come for us to redefine intelligence in the uncharted territories of biology and physics, rather than mathematics.
@r0ck3t23 AI run on digital computers can never wake up because it can’t solve the phenomenal binding problem. Orch-OR can’t solve the binding problem either. For c. 86 billion decohered neurons each supporting quantum coherence in microtubules is a microexperiential zombie, not a mind.