Anirban Bandyopadhyay, who has published a lot of research on the topic, has presented good evidence that microtubules have quantum properties.
From one published paper:
"We demonstrate that a single brain-neuron-extracted microtubule is a memory-switching element, whose hysteresis loss is nearly zero. Our study shows how a memory-state forms in the nanowire and how its protein arrangement symmetry is related to the conducting-state written in the device, thus, enabling it to store and process ∼500 distinct bits, with 2 pA resolution between 1 nA and 1 pA. Its random access memory is an analogue of flash memory switch used in a computer chip. Using scanning tunneling microscope imaging, we demonstrate how single proteins behave inside the nanowire when this 3.5 billion years old nanowire processes memory-bits."[1]
As he discusses in an interview[2], the idea that the membrane is the only important part of the neuron is an idea from 1907 and is fundamentally incorrect. While he does not claim to prove Orch-OR and has his own theories, he is sure the internal structure of neurons with protofilaments of various sizes capable of up to terahertz frequencies has vital functionality that needs its place in neuroscience.
There are about 5,000 microtubules per neuron. If these are quantum devices, we are many thousands or millions of years away from AGI, if it's even possible to achieve it without replicating those structures.
As someone who's extremely skeptical about the premise of AGI, I don't see how these results (if they are replicable) would imply anything much about it. Computers are not exactly storage-limited as it is, and latency and (cross-sectional) bandwidth to memory tend to be a lot more impactful than raw capacity in terms of impact on effective computational power. Besides that, neurons have a lot more stuff in them than just microtubules (since they're living cells), which gives us a lot of wiggle room to improve on them even if our actual circuits are potentially less space-efficient than the biological alternatives. IMO, the appeal of studying biological organisms for ideas for computation is a lot more about things like energy efficiency and robustness than pure performance.
Because the current approach to AGI depends on absolutely nothing happening inside the membrane of the neuron.
If there are 5,000 intercommunicating structures with quantum properties * 80 billion classically connected neurons instead of just the 80 billion node neural network, we may have not even approached the capabilities of a single neuron with classical binary supercomputers. That would explain why there isn't a single example of successful AGI, even to emulate the behavior of simple bacteria.
As far as efficiency, quantum computers require 1,500 square feet and lots of electricity to preserve the state of tens of qubits. They can solve problems with less overall power than classical alternatives, but you can't pack a whole lot of them into a neuron.
But nothing of what you quoted of the article has anything to do with qubits, let alone entangled ones? Again, even if it's accurate and useful, it would be a way to provide space (and maybe energy?) efficient storage, not quantum computation. This is not surprising, because living cells have very different requirements from synthetic computers!
And taking an "outside" view, it's certainly not the case that humans are particularly good at solving problems where the only efficient algorithm we know of runs on a quantum computer... so even if there were any interesting quantum computation going on, it's not clear why that would be needed for AGI.
Going back to "cells are not computers," there are some (apparently good) arguments that plant photosynthesis relies in some essential way on nonclassical electron behavior to achieve its high efficiency for the purposes for which plants use it (biomass production), but that doesn't mean we can't achieve higher performance for the purposes of energy production with solar panels using a much simpler process. Even if you believe that the complexity in living organisms is mostly essential (which I do!) it doesn't mean much for the design of machines for humans to use.
I agree with you that the current methods for trying to achieve AGI are dubiously related to how actual brains work and probably aren't going to be successful without some major changes, but that's a very different point!
> But nothing of what you quoted of the article has anything to do with qubits, let alone entangled ones? Again, even if it's accurate and useful, it would be a way to provide space (and maybe energy?) efficient storage, not quantum computation. This is not surprising, because living cells have very different requirements from synthetic computers!
The structure of a microtubule is a fibonnaci geometry, and the theory is that different pathways along the structure provide superposition using a chain of hydrophobically isolated pockets of benzene molecules within the tubulin protein walls. This provides error correction for part of the state of the quantum system, somewhat misleadingly called a qubit, as well as protection against decoherence. I think consciousness depends on these structures and states because it explains why anesthesia, which bind to aromatics, stop consciousness without killing the brain. That doesn't mean all of Orch-OR is correct, but it is an extremely important piece of evidence, and the only testable hypothesis that I know of for why anesthesia works.
And I agree, living cells have very different requirements. They need to draw as little power as possible, rewire themselves as the environment/computational needs change, and be capable of repairing themselves.
> And taking an "outside" view, it's certainly not the case that humans are particularly good at solving problems where the only efficient algorithm we know of runs on a quantum computer... so even if there were any interesting quantum computation going on, it's not clear why that would be needed for AGI.
There's no evolutionary advantage to solving complex math, but people with different neurology are able to perform incredible calculations. The entire principle behind AGI is that if you can model the network effect of the brain, you get AGI. If that model is completely wrong, the theory behind AGI isn't going to work.
> Going back to "cells are not computers"
Correct, cells cannot be classical computers. They would require too much power for too little benefit. That's why paramecium have microtubules instead of processors, and rely on fundamental aspects of quantum physics instead of comparably primitive turing machines. And to borrow a phrase from Hameroff, proponents of AGI should try modeling the behavior of single celled organisms before they try the brain.
> there are some (apparently good) arguments that plant photosynthesis relies in some essential way on nonclassical electron behavior to achieve its high efficiency for the purposes for which plants use it (biomass production), but that doesn't mean we can't achieve higher performance for the purposes of energy production with solar panels using a much simpler process. Even if you believe that the complexity in living organisms is mostly essential (which I do!) it doesn't mean much for the design of machines for humans to use.
The latest breakthroughs in solar efficiency are literally based on inspiration from biology:[1] "Although we can’t replicate the complexity of the protein scaffolds found in photosynthetic organisms, we were able to adapt the basic concept of a protective scaffold to stabilize our artificial light-harvesting antenna.”
The newest research of building quantum computing devices is moving away from trying to wrangle individual atoms and instead moving to storing and manipulating molecules.[2] So, for the next generation of computing, the complexity of living organisms might be absolutely essential for designing machines. As quantum computers grow in capability, we will be able to model more of the quantum world, because "predicting the behavior of even simple molecules with total accuracy is beyond the capabilities of the most powerful computers."[3] Each generation of quantum computers will bootstrap the next.
Once the hubris and arrogance of people who think nature couldn't have possibly evolved to take advantage of quantum properties is finally over, I think there will be a revolution in every field as it gets cheaper and cheaper to model the planck scale world. The first victim will be AGI, and there is a lot of money and ego desperate to keep that marketing scheme viable.
> The latest breakthroughs in solar efficiency are literally based on inspiration from biology:[1] "Although we can’t replicate the complexity of the protein scaffolds found in photosynthetic organisms, we were able to adapt the basic concept of a protective scaffold to stabilize our artificial light-harvesting antenna.”
Whether or not "the next generation" is "biologically inspired" (which doesn't mean using exactly the same mechanism), solar panels right now outperform plants on a pure energy production basis, and do this without any complex molecular or quantum machinery. This is because energy production is much easier than biomass production. That's my basic point, if you don't care about beating life on literally every axis (particularly energy efficiency, replication, and use of cheaply available materials) it's entirely conceivable you can do better. So if people want to build nanobots there's basically no chance they're going to beat life, but that's pretty different from AGI (even though it seems like the same people are invested in both for whatever reason).
The comic is confidently patronizing and either very old or poorly researched. It assumes that isolated atoms are the only way to interact with superposition, which is not true and not where any of the next generation designs for quantum computing are headed.
“Realization of universal quantum gates is rather challenging in the case of spin defects because the rigorous conditions needed for confining quantum decoherence are likely to limit the coherent exchange of information between qubits as a result of scarce control over qubit-qubit distances. In this respect, a chemistry-driven bottom-up approach to qubit scalability is more appropriate. Molecules are highly versatile, enabling their electronic structures and spin environments to be tuned at will with the use of simple synthetic chemistry tools. Moreover, they can be replicated in large number, functionalized in the desired way, and organized in a controlled manner for the production of large qubit arrays. Undoubtedly, chemical design offers endless opportunities for magnetic molecules to be tailored for specific technological tasks.”
From one published paper:
"We demonstrate that a single brain-neuron-extracted microtubule is a memory-switching element, whose hysteresis loss is nearly zero. Our study shows how a memory-state forms in the nanowire and how its protein arrangement symmetry is related to the conducting-state written in the device, thus, enabling it to store and process ∼500 distinct bits, with 2 pA resolution between 1 nA and 1 pA. Its random access memory is an analogue of flash memory switch used in a computer chip. Using scanning tunneling microscope imaging, we demonstrate how single proteins behave inside the nanowire when this 3.5 billion years old nanowire processes memory-bits."[1]
As he discusses in an interview[2], the idea that the membrane is the only important part of the neuron is an idea from 1907 and is fundamentally incorrect. While he does not claim to prove Orch-OR and has his own theories, he is sure the internal structure of neurons with protofilaments of various sizes capable of up to terahertz frequencies has vital functionality that needs its place in neuroscience.
There are about 5,000 microtubules per neuron. If these are quantum devices, we are many thousands or millions of years away from AGI, if it's even possible to achieve it without replicating those structures.
[1] https://aip.scitation.org/doi/abs/10.1063/1.4793995
[2] https://www.closertotruth.com/series/quantum-physics-conscio...