Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Cubic millimetre of brain mapped at nanoscale resolution

nature.com

Post reply on HN
Print view View original

131–140 of 205 posts

Re: Cubic millimetre of brain mapped at nanoscale resolution

#131

Post by hetman »

throwup238 wrote: post #12

> The 3D map covers a volume of about one cubic millimetre, one-millionth of a whole brain, and contains roughly 57,000 cells and 150 million synapses — the connections between neurons. This is great and provides a hard data point for some napkin math on how big a neural network model would have to be to emulate the human brain. 150 million synapses / 57,000 neurons is an average of 2,632 synapses per neuron. The adu…

That may or may not still be too simple a model. Cells are full of complex nano scale machinery and not only might it me plausible some of it is involved in the processes of cognition, I'm aware of at least one study which identified some nano scale structures directly involved in how memory works in neurones. Not to mention a lot of what's happening has a fairly analogue dimension.

I remember an interview with one neurologist who stated humanity has for centuries compared the functioning of the brain to the most complex technology devised yet. First it was compared to mechanical devices, then pipes and steam, then electrical circuits, then electronics and now finally computers. But he pointed out, the brain works like none of these things so we have to be aware of the limitations of our models.

Re: Cubic millimetre of brain mapped at nanoscale resolution

#132

Post by ruined »

sigmoid10 wrote: post #124
djmips wrote: post #107

Earlier quoted context omitted.

It's amusing to say that bird brains are on the next generation node size.

Would be interesting to see what their wafer yield is. Like, are they more or less prone to mental disease.

all the crows can tell i'm crazy, but i've never met an insane crow.

Re: Cubic millimetre of brain mapped at nanoscale resolution

#133

Post by RaftPeople »

philsnow wrote: post #119
steve_adams_86 wrote: post #57

Earlier quoted context omitted.

This might be a dumb question, because I doubt the distances between neurons makes a meaningful distance… But could a small brain, dense with neurons like a crow, possibly lead to a difference in things like response to stimuli or “compute” speed so to speak?

Not a dumb question at all; one of the hard constraints of cou design is signal propagation time. Even going at 1/3 the speed of light, when you only have on the order of a billionth of a second (clock frequencies in the GHz), a signal can’t get very far. I haven’t heard of a clocking mechanism in brains, but signals propagate much slower and a walnut / crow brain is much larger than a cpu die.

> I haven’t heard of a clocking mechanism in brains

Brain waves (partially). They aren't exactly like a cpu clock, but they do coordinate activity of cells in space and time.

There are different frequencies that are involved in different types of activity. Lower frequencies synchronize across larger areas (can be entire brain) and higher frequencies across smaller local areas.

There is coupling between different types of waves (i.e. slow wave phase coupled to fast waves amplitude) and some researchers (Miller) thinks the slow wave is managing memory access and the fast wave is managing cognition/computation (utilizing the retrieved memory).

Re: Cubic millimetre of brain mapped at nanoscale resolution

#134

Post by startupsfail »

dsalfdslfdsa wrote: post #69
throw310822 wrote: post #55

Earlier quoted context omitted.

Or you can subscribe to Geoffrey Hinton's view that artificial neural networks are actually much more efficient than real ones- more or less the opposite of what we've believed for decades- that is that artificial neurons were just a poor model of the real thing. Quote: "Large language models are made from massive neural networks with vast numbers of connections. But they are tiny compared with the brain. “Our brains…

"Efficient" and "better" are very different descriptors of a learning algorithm. The human brain does what it does using about 20W. LLM power usage is somewhat unfavourable compared to that.

It is using about 20W and then a person takes a single airplane ride between the coasts. And watches a movie on the way.

Re: Cubic millimetre of brain mapped at nanoscale resolution

#135

Post by RaftPeople »

dragonwriter wrote: post #60
throw310822 wrote: post #55

Earlier quoted context omitted.

Or you can subscribe to Geoffrey Hinton's view that artificial neural networks are actually much more efficient than real ones- more or less the opposite of what we've believed for decades- that is that artificial neurons were just a poor model of the real thing. Quote: "Large language models are made from massive neural networks with vast numbers of connections. But they are tiny compared with the brain. “Our brains…

I mean, Hinton’s premises are, if not quite clearly wrong, entirely speculative (which doesn't invalidate the conclusions about efficienct that they are offered to support, but does leave them without support) GPT-4 can produce convincing written text about a wider array of topics than any one person can, because it's a model optimized for taking in and producing convincing written text, trained extensively on writte…

> Humans know a lot of things that are not revealed by inputs and outputs of written text (or imagery), and GPT-4 doesn't have any indication of this physical, performance-revealed knowledge, so even if we view what GPT-4 talks convincingly about as “knowledge”, trying to compare its knowledge in the domains it operates in with any human’s knowledge which is far more multimodal is... well, there's no good metric for it.

Exactly this.

Anyone that has spent significant time golfing can think of an enormous amount of detail related to the swing and body dynamics and the million different ways the swing can go wrong.

I wonder how big the model would need to be to duplicate an average golfers score if playing X times per year and the ability to adapt to all of the different environmental conditions encountered.

Re: Cubic millimetre of brain mapped at nanoscale resolution

#136

Post by RaftPeople »

hetman wrote: post #131
throwup238 wrote: post #12

> The 3D map covers a volume of about one cubic millimetre, one-millionth of a whole brain, and contains roughly 57,000 cells and 150 million synapses — the connections between neurons. This is great and provides a hard data point for some napkin math on how big a neural network model would have to be to emulate the human brain. 150 million synapses / 57,000 neurons is an average of 2,632 synapses per neuron. The adu…

That may or may not still be too simple a model. Cells are full of complex nano scale machinery and not only might it me plausible some of it is involved in the processes of cognition, I'm aware of at least one study which identified some nano scale structures directly involved in how memory works in neurones. Not to mention a lot of what's happening has a fairly analogue dimension. I remember an interview with one n…

> That may or may not still be too simple a model

Based on the stuff I've read, it's almost for sure too simple a model.

One example is that single dendrites detect patterns of synaptic activity (sequences over time) which results in calcium signaling within the neuron and altered spiking.

Re: Cubic millimetre of brain mapped at nanoscale resolution

#138

Post by m3kw9 »

jamiek88 wrote: post #9
teuobk wrote: post #2

The interactive visualization is pretty great. Try zooming in on the slices and then scrolling up or down through the layers. Also try zooming in on the 3D model. Notice how hovering over any part of a neuron highlights all parts of that neuron: http://h01-dot-neuroglancer-demo.appspot.com/#!gs://h01-rele...

My god. That is stunning. To think that’s one single millimeter of our brain and look at all those connections. Now I understand why crows can be so smart walnut sized brain be damned. What an amazing thing brains are. Possibly the most complex things in the universe. Is it complex enough to understand itself though? Is that logically even possible?

Physics of the universe is the most complex thing in the universe

Re: Cubic millimetre of brain mapped at nanoscale resolution

#139

Post by j_m_b »

dyauspitr wrote: post #117
j_m_b wrote: post #113

Earlier quoted context omitted.

> Computing power should get there around 2048 We may not get there. Doing some more back of the envelope calculations, let's see how much further we can take silicon. Currently, TSMC has a 3nm chip. Let's halve it until we get to the atomic radius of silicon of 0.132 nm. That's not a good value because we're not considering crystal latice distances, Heisenberg uncertainty, etc., but it sets a lower bound. 3nm -> 1.5…

3nm doesn’t mean the transistor is 3nm, it’s just a marketing naming system at this point. The actual transistor is about 20-30nm or so.

Thanks for the comment. I looked more into this and it seems like not only are we in the era of diminished returns for computational abilities, costs have also now started matching the increased compute. i.e 2x performance leads to 2x cost. Moore's law has already run it's course and we're living in a new era of compute. We may get increased performance, but it will always be more expensive.

Re: Cubic millimetre of brain mapped at nanoscale resolution

#140

Post by s1artibartfast »

ToValueFunfetti wrote: post #100
Intralexical wrote: post #91

Earlier quoted context omitted.

Tested with GPT-3.5 instead of GPT-4. > When I clarified that I did mean removal, it said that the procedure didn't exist. My point in my first two sentences is that by clarifying with emphasis that you do mean " removal ", you are actually adding information into the system to indicate to it that laser eye removal is (1) distinct from LASIK and (2) maybe not a thing. If you do not do that, but instead reply as if la…

I tried all of your follow-up prompts against GPT-4, and it never acknowledged 'removal' and instead talked about laser eye surgery. I can't figure out how to share it now that I've got multiple variants, but, for example, excerpt in response to the glass eye prompt: >If someone is considering a glass eye after procedures like laser eye surgery (usually due to severe complications or unrelated issues), it's important…

I think the distinction that they are trying to illustrate that if you asked a human about laser eye removal, they would either laugh or make the decision to charitably interpret your intent.

The llm does not do either. It just follows a statistical heuristic and therefore thinks that laser eye removal is the same thing

Post reply on HN