Or something that goes against the general opinions of the community? Vibes are the only benchmark that counts after all.
I tend to agree with the flow on most things but my thoughts that I’d consider going against the grain:
- QwQ was think-slop and was never that good
- Qwen3-32B is still SOTA for 32GB and under. I cannot get anything to reliably beat it despite shiny benchmarks
- Deepseek is still open-weight SotA. I’ve really tried Kimi, GLM, and Qwen3’s larger variants but asking Deepseek still feels like asking the adult in the room. Caveat is GLM codes better
- (proprietary bonus): Grok 4 handles news data better than GPT-5 or Gemini 2.5 and will always win if you ask it about something that happened that day.
(P2/2)
The skepticism about quantum effects in the brain is well-founded and represents the orthodox view. The “brain is a classical computer” model has driven most of our progress in neuroscience and AI. The strongest argument against a “quantum brain” is of decoherence. In a warm wet brain quantum coherence is rapid. However, quantum biology doesn’t require brain-wide, long-lived coherence. It investigates how biological systems exploit quantum effects on short timescales and in specific, protected environments.
We already have proven examples of this. In plant cells, energy transfer in photosynthetic complexes appears to use quantum coherence to find the most efficient path with near-100% efficiency, happening in a warm, wet, and noisy cellular environment. Its now proven that some enzymes use quantum tunneling to accelerate chemical reactions crucial for life. The leading hypothesis for how birds navigate using Earth’s magnetic field involves a quantum effect in a protein called cryptochrome in their eyes, where electron spins in a radical pair mechanism are sensitive to magnetic fields.
The claim isn’t that a neuron is a qubit, but that specific molecular machinery within neurons could utilize quantum principles to enhance their function.
You correctly note that the “neuron as a binary switch” is an oversimplification. The reality is far more interesting. A neuron’s decision to fire integrates thousands of analog inputs, is modulated by neurotransmitters, and is exquisitely sensitive to the precise timing of incoming signals. This system operates in a regime that is often chaotic. In a classically chaotic system, infinitesimally small differences in initial conditions lead to vastly different outcomes. The brain, with its trillions of interconnected, non-linear neurons, is likely such a system.
Consider the scale of synaptic vesicle release, the event of neurotransmitter release triggered by the influx of a few thousand calcium ions. At this scale, the line between classical and quantum statistics blurs. The precise timing of a vesicle release could be influenced by quantum-level noise. Through chaotic amplification, a single quantum-scale event like the tunneling of a single calcium ion or a quantum fluctuation influencing a neurotransmitter molecule could, in theory, be amplified to alter the timing of a neuron’s firing. This wouldn’t require sustained coherence; it would leverage the brain’s chaotic dynamics to sample from a quantum probability distribution and amplify one possible outcome to the macroscopic level.
Classical computers use pseudo-random number generators with limited ability to truly choose between multiple possible states. A system that can sample from genuine quantum randomness has a potential advantage. If a decision process in the brain (like at the level of synaptic plasticity or neurotransmitter release)is sensitive to quantum events, then its output is not the result of a deterministic algorithm alone. It incorporates irreducible quantum randomness, which itself has roots in computational undecidability. This could provide a physical basis for the probabilistic, creative, and often unpredictable nature of thought. It’s about a biological mechanism for generating true novelty, and breaking out of deterministic periodic loops. These properties are a hallmark of human creativity and problem-solving.
To be clear, I’m not claiming the brain is primarily a quantum computer, or that complexity doesn’t matter. It absolutely does. The sheer scale and recursive plasticity of the human brain are undoubtedly the primary sources of its power. However, the proposal is that the brain is a hybrid system. It has a massive, classical, complex neural network as its substrate, operating in a chaotic, sensitive regime. At the finest scales of its functional units such as synaptic vesicles or ion channels, it may leverage quantum effects to inject genuine undecidably complex randomness to stimulate new exploration paths and optimize certain processes, as we see elsewhere in biology.
I acknowledge there’s currently no direct experimental evidence for quantum effects in neural computation, and testing these hypotheses presents extraordinary challenges. But this isn’t “hiding God in the gaps.” It’s a hypothesis grounded in the demonstrated principles of quantum biology and chaos theory. It suggests that the difference between classical neural networks and biological cognition might not just be one of scale, but also one of substrate and mechanism, where a classically complex system is subtly but fundamentally guided by the unique properties of the quantum world from which it emerged.
Yeah, thanks as well, engaging discussion.
I think that’s a fairly common misconception. What Gödel proved was that there isn’t one single formal system in which we can derive everything. It doesn’t really lead to the conclusion that questions can’t be answered. There is an infinite amount of formal systems, and Gödel doesn’t rule out the possibility of proving something with one of the countless other, different systems, starting out with different axioms. And as I said, this is a limitation to formal logic systems and not to reality.
Yes, that’s another distinct form of undecidability. There are decision problems we can’t answer in finite time with computers.
I think it is a bit of a moot point, as there are lots of impossible things. We have limited resources available, so we can only ever do things with what we have available. Then we have things like locality and I don’t even know what happens 15km away from me because I can’t see that far. Physics also sets boundaries. For example we can’t measure things to perfection and can’t even do enough measurments for complex systems. And then I’m too heavy to fly on my own and can’t escape gravity. So no matter how we twist it, we’re pretty limited in what we can do. And we don’t really have to resort to logic problems for that.
To me, it’s far more interesting to look at what that means for a certain given problem. We human can’t do everything. Same applies to knowledge, physics calculations and AI. At the point we build it, it’s part of the real world and subject to the same limitations which apply to us as well. And that’s inescapable. You’re definitely right, there are all these limitations. I just don’t think it’s specific to anything in particular. But it certainly means we won’t ever build any AI which knows everything and can do everything. We also can’t ever simulate the entire universe. That’s impossible on all levels we discussed.
I mean if quantum physics is the underlying mechanism of the universe, then everything “uses” quantum effects. It boils down to the question if that model is useful to describe some process. For example if I drop a spoon in the kitchen, it always falls down towards the floor. There are quantum effects happening in all the involved objects. It’s just not useful to describe that with quantum physics, regular Newtonian gravity is better suited to tell me something about the spoon and my kitchen… Same is with the enzymes and the human brain. They exist and are part of physics, and they do their thing. Only question is which model do we use to describe them or predict something about them. That might be quantum physics in some cases and other physics models in other cases.
It certainly sounds like the God of the gaps to me. Look at the enzyme example. We found out there’s something going on with temperature we can’t correctly describe with our formulas. Then scientists proposed this is due to quantum tunneling and that has to be factored in… That’s science… On the other hand no such thing happened for the human brain. It seems to be perfectly fine to describe it with regular physics, it’s just too big/complex and involved to bridge the gap from what the neurons do to how the brain processes information. And then people claimed there’s God or chaos theory or quantum effects hidden inside. But that’s wild unfounded claims and opinion, not science. We’d need to see something which doesn’t add up, like how it happened with the enzymes. Everything else is religious belief. (And turns out we already simulated the brain of a roundworm and a fruit fly, and at least Wikipedia tells me the simulation is consistent with biology… Leading me to believe there’s nothing funny going on and it’s just a scalability problem.)