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PaperclipPerfector  13d ago (text post)   32622 thread views

Culture War Roundup for the week of March 24, 2025

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I don't think it's unlikely that humans are far more optimized for real-world relevant computation than computers will ever be. Our neurons make use of quantum tunneling for computation in a way that classical computers can't replicate. Of course quantum computers could be a solution to this, but the engineering problems seem to be incredibly challenging. There's also evolution. Our brain has been honed by 4 billion years of natural selection. Maybe this natural selection hasn't selected for the exact kinds of processes we want AI to do, but there certainly has been selection for some combination of efficient communication and accurate pattern recognition. I'm not convinced we can engineer better than that.

The human brain may always be more efficient on a watt basis, but that doesn’t really matter when we can generate / capture extraordinary amounts of energy.

Energy infrastructure is brittle, static and vulnerable to attack in a way that the lone infantryman isn't. It matters.

Do you expect that to remain true as the price of solar panels continues to drop? A human brain only takes about 20 watts to run. If we can get within a factor of 10 of that, that's 200 watts. Currently that's a few square meters of solar panels costing a couple thousand dollars, and a few dozen kilos of battery packs, also costing a couple thousand dollars. It's not as robust as a lone infantryman, but it's already quite a lot cheaper, and the price is continuing to drop.

Although that said, solar panels require quite a lot of sensitive and stationary infrastructure to make, I could see the argument that the ability to fabricate them will not last long in any large scale conflict.

The industry required to make all these doodads just becomes the target. Unless you dealing with something fully autonomous to the degree that it carries its own reproduction, you're not gonna beat life in a survival contest.

That said, I don't really expect portable energy generation to be efficient enough in the near future to matter in the way you're thinking. Moreover, this totally glosses over maintenance which is a huge weakness any high tech implement has in terms of logistics.

About 6 sqm of panels at STC, probably more like 12-18 realistically (2.4-3.6kW, plus at least 10-15kWh of batteries. The math gets brutal for critical uptime off-grid solar, but some people have more than that on an RV these days. So it's not really presenting a much larger target than a road-mobile human would be (at least one with the comms and computer gear needed to do a similar job)

And the machine brain is always going to be vastly more optimized for multitasking than a human.

I dunno, some of the ways I can think of to bring down a transformer station or a concrete-hulled building involve violent forces that would, in fact, be similarly capable of reducing a lone infantryman to a bloody pulp.

You're probably thinking of explosives or some kind, but you're thinking about terminal ballistics instead of the delivery mechanism and other factors.

A man in khakis with a shovel can move out of the way of bombardment, use cover to hide and dig himself fortifications, all of which mitigates the use of artillery and ballistic missiles.

Static buildings that house infrastructure have no such advantage and require active defense forces to survive threats. They're sitting ducks.

I'm not pulling this analysis out of my ass mind you, this is what you'll find in modern whitepapers on high intensity warfare that recommend against relying on anything that requires a complex supply chain because everybody expects most complex infrastructure (sats, power grids, etc) to be destroyed early and high tech weapons to become either useless or prized reserves that won't be doing the bulk of the fighting.

Do you have a source on the quantum tunneling thing? That strikes me as wildly implausible.

Roger Penrose has been beating this drum since the 1990s and hasn't managed to convince many other people, but he is a Nobel laureate now so I guess he's a pretty high-profile advocate. The way he argues for this stuff feels more like a cope for preserving some sort of transcendental, irreducible aura for human mathematical thinking rather than empirically solid neuroscience though.

Relevant paper: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.024402

Relevant other links: https://jacquesmattheij.com/another-way-of-looking-at-lee-sedol-vs-alphago/, https://www.biorxiv.org/content/10.1101/2020.04.23.057927v1.full, https://www.rintrah.nl/a-universe-fine-tuned-for-biological-intelligence/

My read on that paper is that it says

  1. The mechanism behind neural synchronization across distances in the brain is not fully understood
  2. Maybe that's because quantum effects play a significant role
  3. Here's a theoretical quantum mechanism that could potentially operate in myelinated axons
  4. Our mathematical model suggests this mechanism is physically possible under certain conditions
  5. The myelin sheath structure might provide sufficient isolation for quantum effects to persist despite body temperature
  6. We have no empirical evidence confirming or even suggesting that this actually happens in real neurons

I might find this study convincing if it was presented alongside an experiment where e.g. scientists slowly removed the insulating myelin coating from a single long nerve cell in a worm and watched what happened to the timing of signals across the brain. I'd expect the signals between distant parts of the brain not to stay synchronized as the myelin sheath degrades. If there's a sudden drop-off in synchronization at a specific thickness, rather than a gradual decline as the insulation thins, it might suggest quantum entanglement effects rather than just classical electrical conductivity changes.

In the absence of any empirical evidence like that I don’t find this paper convincing though.

I also don't think the paper authors were trying to convince readers that this is a thing that does happen in real neurons, just that further study is warranted.

This is highly speculative, and a light-year away from being a consensus position in computational neuroscience. It's in the big if true category, and far from being confirmed as true and meaningful.

It is trivially true that human cognition requires quantum mechanics. So does everything else. It is far from established that you need to explicitly model it at that detail to get perfectly usable higher level representations that ignore such detail.

The brain is well optimized for what's possible for a kilo and change of proteins and fats in a skull at 37.8° C, reliant on electrochemical signaling, and a very unreliable clock for synchronization.

That is nowhere near the optimal when you can have more space and volume, while working with designs biology can't reach. We can use copper cable and spin up nuclear power plants.

I recall @FaulSname himself has a deep dive on the topic.

That is a very generous answer to something that seems a lot more like complete gibberish. A single neural structure with known classical functions may, under their crude (the author's own words) theoretical model, produce entangled photons is the only real statement in that article. Even granting this, to go from that to neurons communicating using such photons in any way would be an absurd leap. Using the entanglement to communicate is straight up impossible.

You are also replying to someone who can't differentiate between tunneling and entanglement, so that's a strong sign of complete woo as well.

You're correct that I'm being generous. Expecting a system as macroscopic and noisy as the brain to rely on quantum effects that go away if you look at them wrong is a stretch. I wouldn't say that's impossible, just very, very unlikely. It's the kind of thing you could present at a neuroscience conference, without being kicked out, but everyone would just shake their heads and tut the whole time.

If this were true, then entering an MRI would almost certainly do crazy things to your subjective conscious experience. Quantum coherence holding up to a tesla-strong field? Never heard of that, at most it's incredibly subtle and hard to distinguish from people being suggestible (transcranial magnetic stimulation does do real things to the brain). Even the brain in its default state is close to the worst case scenario when it comes to quantum-only effects with macroscopic consequences.

And even if the brain did something funky, that's little reason to assume that it's a feature relevant to modeling it. As you've mentioned, there's a well behaved classical model. We already know that we can simulate biological neurons ~perfectly with their ML counterparts.

We know for a fact that the electron transport chain of mitochondria relies on quantum tunneling to move electrons between complexes and MRI doesn't seem to effect that very much, so I wouldn't be surprised if an MRI had no effect on conscious experience (although I couldn't tell you, I've never had one).

I don't buy the claim that we can simulate biological neurons perfectly with their ML counterparts. We can barely simulate the function of an entire bacterial cell, which for context, is about as big as a mitochondria. Can we approximate neuronal function? Sure. But something is clearly lost: what else would explain the great efficiency of biological versus human systems in terms of power consumption.

https://www.quantamagazine.org/how-computationally-complex-is-a-single-neuron-20210902/

They started by creating a massive simulation of the input-output function of a type of neuron with distinct trees of dendritic branches at its top and bottom, known as a pyramidal neuron, from a rat’s cortex. Then they fed the simulation into a deep neural network that had up to 256 artificial neurons in each layer. They continued increasing the number of layers until they achieved 99% accuracy at the millisecond level between the input and output of the simulated neuron. The deep neural network successfully predicted the behavior of the neuron’s input-output function with at least five — but no more than eight — artificial layers. In most of the networks, that equated to about 1,000 artificial neurons for just one biological neuron.

But something is clearly lost: what else would explain the great efficiency of biological versus human systems in terms of power consumption.

I really don't see this as a good explanation. We know that there are brains that are more efficient, by volume. Avian neurons are smaller, packed more densely, but can create a very smart animal that uses tools. You can find a wide range of "efficiency" values in biology, the human brain isn't particularly special.

I think it's far more likely that the brain's architecture is just very well optimized for its constraints, and power draw is a very important constraint. Running an LLM that is human level in reasoning (or close enough) uses a lot more power, but an 8B model can be surprisingly smart and run on a smartphone. I bet a model like that is "smarter" than a human child in relevant domains for far less power. Silicon computers are also far faster in terms of clock speed. They are incredibly reliable in terms of error rate and consistency. You've chosen IQ/watt as the metric in advance (and it's important), but silicon computers have enormous advantages that biology can only dream of. You can imagine the analogous situation, trying to convince people that it's important to simulate things like electron tunneling causing power draw in very small transistors (which is true), when that has no relevance to actually emulating a computer.

None of this requires quantum effects to be an irreducible aspect of human computation. Nor that it's responsible for the relative efficiency.

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