41–50 of 141 posts
To me one important aspect is the existence of adversarially attacks on neural networks. They essentially prove that the neural network never "understood" its data. It hasn't found some general categories which correspond somewhat to human categories. Human brains can be tricked too, but never this way and never beyond our capacities for rational thought.
Here's my guess: neurons tap into quantum mechanics but we are too primitive to understand that for now. The brain was initially modeled as humors/fluids back when we developed aqueducts, then telegraph came into the scene and it was modeled as electrical impulses and now computers/ML are popular therefore we see it as a neural network. Next step is quantum.
I really don’t get why everyone wants the Brian to operate on some new QM effect other than peoples perception that a 100 year old theory is somehow cutting edge, spooky, or something. Perhaps it’s that the overwhelming majority of people who talk about QM don’t actually understand it even a little bit. Odd bits of QM are already why lasers, LED’s, and transistors work. You use incites from the theory everyday in most electronic devices, but it’s just as relevant for explaining old incandescent bulbs we just had other theories that seemed to explain them.
The aspect of ai that makes me think something related is going on, is how artifacts look in image generation systems like stable diffusion. Often these systems will have really bizzare artificats, people with 3 arms, etc. However at the same time when you glance at the output without looking carefully you will sometimes miss these artifacts even though they should be absolutely glaring.
I don't know if AGI is down the road diffusion models have taken us. I'm not even really sure what most people mean by AI when they talk about it. But stable diffusion et al are clearly super human. I'm not sure that AGI is down the trail cut by diffusion models, but if it's ever accomplished, these models will almost assuredly represwbt some of the learnings required to get there.
The aspect of ai that makes me think something related is going on, is how artifacts look in image generation systems like stable diffusion. Often these systems will have really bizzare artificats, people with 3 arms, etc. However at the same time when you glance at the output without looking carefully you will sometimes miss these artifacts even though they should be absolutely glaring.
Here's my guess: neurons tap into quantum mechanics but we are too primitive to understand that for now. The brain was initially modeled as humors/fluids back when we developed aqueducts, then telegraph came into the scene and it was modeled as electrical impulses and now computers/ML are popular therefore we see it as a neural network. Next step is quantum.
If the Brian is using some physics we don’t understand that’s something new not Quantum Mechanics. QM a specific theory of how the world operates, if something else is involved it doesn’t fall under that theory it’s [insert new theory’s name here]. I really don’t get why everyone wants the Brian to operate on some new QM effect other than peoples perception that a 100 year old theory is somehow cutting edge, spooky,…
The aspect of ai that makes me think something related is going on, is how artifacts look in image generation systems like stable diffusion. Often these systems will have really bizzare artificats, people with 3 arms, etc. However at the same time when you glance at the output without looking carefully you will sometimes miss these artifacts even though they should be absolutely glaring.
For me, it's the way generative videos can rapidly, but to my eyes seamlessly, transition from one shape to another. I may not be able to record my dreams, but my memories of my dreams do match this effect, with one place or person suddenly becoming another.
To me one important aspect is the existence of adversarially attacks on neural networks. They essentially prove that the neural network never "understood" its data. It hasn't found some general categories which correspond somewhat to human categories. Human brains can be tricked too, but never this way and never beyond our capacities for rational thought.
Optical illusions is one thing, but, I don't know, "Predictably Irrational", "Thinking fast and slow" or just whatever is happening all around. We do not understand our data. In general yes, I believe most people will only accept thinking machine when it can reproduce all our pitfalls. Because if we see something and the computer doesn't, then it clearly still needs to be improved, even if it's an optical illusion. B…
I'd agree about sacred, but I have a hunch they may indeed be special… or at least useful. Current AI requires far more examples than we do to learn from, and I suspect all our biases are how evolution managed to do that.
Here's my guess: neurons tap into quantum mechanics but we are too primitive to understand that for now. The brain was initially modeled as humors/fluids back when we developed aqueducts, then telegraph came into the scene and it was modeled as electrical impulses and now computers/ML are popular therefore we see it as a neural network. Next step is quantum.
Look up 'Penrose argument'. Personally tho I believe it's the physicists' equivalent of seeing everything as a nail when using a hammer.
Here's my guess: neurons tap into quantum mechanics but we are too primitive to understand that for now. The brain was initially modeled as humors/fluids back when we developed aqueducts, then telegraph came into the scene and it was modeled as electrical impulses and now computers/ML are popular therefore we see it as a neural network. Next step is quantum.
If the Brian is using some physics we don’t understand that’s something new not Quantum Mechanics. QM a specific theory of how the world operates, if something else is involved it doesn’t fall under that theory it’s [insert new theory’s name here]. I really don’t get why everyone wants the Brian to operate on some new QM effect other than peoples perception that a 100 year old theory is somehow cutting edge, spooky,…
When you talk about QM a a theory of how the world operates, there are wide ranges of QM. Everything from predicting the structure and energy states of a molecule, to how P/N junctions work, to quantum computers. Now, for the first one (molecules), the vast majority of QM is just giving ways to compute the electron density and internuclear distances using some fairly straightforward and noncontroversial approaches.
For the other ones (P/N junctions, QC computers, etc), those involve exploiting very specific and surprising aspects of quantum theory: one of quantum tunnelling, quantum coherence, or quantum entanglement (ordered from least counterintuitive to most). We have some evidence already that there are some biological processes that exploit tunnelling and coherence, but none that demonstrate entanglement.
Personally, I think most people think the alternative to Penrose- the brain does not compute non-computable functions, and does not exploit or need to exploit any quantum phenomena (expect perhaps tunnelling) to achieve its goals.
Now, if we were to have hard evidence supporting the idea that brains use entanglement to solve problems: well, that would be pretty amazing and would upend large parts of modern biology adn technology research.