71–80 of 183 posts
If I had a nickel for every time some neurologist tried to compare brains to neural networks. It's a surefire way to tell someone is either desperate for grant money or has been smoking crack. (previously: comparing brains and "electronic computers") Their entire article hinges on the complaint "brain seems shallow and neural networks are deep, ergo neural networks are doing it wrong." Neurologists seem to have a rea…
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No one disagrees we might be able to discern insights if we understand how our brain is wired. The problem is the current state of neuroscience is so flawed in its approach it’s not looking like they’re of any use. They don’t even understand how a 900 neuron worms system works but are more than happy to tap half a billion dollars from unsuspecting politicians saying they’ll map the human connectome. Go read the brain…
what are you talking about is this konrad kording's shitposting alt??? this reeks of naivety I certainly have many critiques of methods used in neuroscience rn (as a working neuroscientist) but to reduce those to the conclusion that the entire project of neuroscience is hopeless is absurd. We understand certain things quite well actually, and it's not at all obvious what "understanding" at a larger scale would look l…
From where I stand I can’t see anyone giving a clear explanation of anything our brain does or does not do in a disease. The only novel treatment that has come out seems to have been stick a rod into the brain and zap it and it just magically cures a lot of diseases we still don’t understand even a bit.
This is not even starting to discuss what little we have learned about how brains algorithms work. I’m still waiting to understand why pyramidal neurons were somehow groundbreaking. We found some neuron that fires when you walk to a place, why wouldn’t we find one?
And what are you saying about the fly connectome again? Do we have exact names for every neuron in the fly brain and its verified connectome for every neuron?
Last I checked the worm connectome has been available in intricate detail for decades and the scientists still haven’t had any proper decoding of the algorithms in that system. In fact I know every lab trying to figure that out now, I wrote proposals in the topic myself. Everyone else has apparently decided it’s not sexy enough to work with worms so they have just leaped to more complex systems with no basic understanding. I’m not the only one saying this. Sydney Brenner said as much in an editorial. But the field was too busy doing I don’t know what to listen.
Sydney, B. & Sejnowski, T. J. Understanding the human brain. Science 334, 567 (2011).
I remember sauntering to the occasional neuroscience talk during my ut southwestern PhD and occasionally hearing some professor brag about how the majority of one of their PhD’s jobs was to segmenting a single neuron in the thousand EM images or something. Surely that’s a sign this field needs revision?
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A fabricated re-telling of the past, given that we didn't start using GPUs for this type of compute until the turn of the millenium.
AlexNet was the turning point for DL.
AlexNet was a state-of-the-art image recognition net for a (relatively) brief amount of time. It wasn't the first CNN to use GPU acceleration, and it was quickly eclipsed in terms of ImageNet performance.
Regardless, I think bringing up AlexNet kinda invalidates your initial point. Although yes, it turns out that the two were a great match, CNNs and modern GPUs were clearly developed independently of each other, as evidenced by the many, many iterations of both before they were combined.
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This is a really weird take. There is such a long history of shared insights between biology and neural network research, and to say they’re unrelated or can’t take inspiration from one another is bizarre. > The concept of CNNs didn't come from biology I just opened a survey paper on CNNs and literally the first sentence of the paper reads: > “Convolutional Neural Network (CNN) is a well-known deep learning architect…
That's later backfill, a retroactive change to give a manufactured "biological" origin story. Whether they're real or not, researchers love a good "we took this from nature, isn't nature wonderful!" explanation. The C in CNN isn't "Convolution" for no reason. It came from work with convolutional filters (yay Sobel kernels!) which at it's height became filter banks and gabor filters and so on before neural networks pr…
The first N in CNN is "Neural" for a reason.
It’s indeed odd that current dnn’s require massive amount of energy to retrain and lack any kind of practical continuous adaptation and learning.
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what are you talking about is this konrad kording's shitposting alt??? this reeks of naivety I certainly have many critiques of methods used in neuroscience rn (as a working neuroscientist) but to reduce those to the conclusion that the entire project of neuroscience is hopeless is absurd. We understand certain things quite well actually, and it's not at all obvious what "understanding" at a larger scale would look l…
Can you please elaborate what great strides the field of neuroscience has made in the past 30 years? From where I stand I can’t see anyone giving a clear explanation of anything our brain does or does not do in a disease. The only novel treatment that has come out seems to have been stick a rod into the brain and zap it and it just magically cures a lot of diseases we still don’t understand even a bit. This is not ev…
onus isn't on me to justify the existence of an entire field to you. the claim that neuroscience has not made great strides in the last 30 years is an extraordinary one, and that's all on you. but it especially doesn't help your case that if you had googled "fly connectome " you would have seen that the first result is a complete connectome of a larvae and the third result is the tour de force from Janelia that produced an adult connectome. With names and verified connections. there is even a wikipedia article for the drosophila connectome!
> I remember sauntering to the occasional neuroscience talk during my ut southwestern PhD and occasionally hearing some professor brag about how the majority of one of their PhD’s jobs was to segmenting a single neuron in the thousand EM images or something. Surely that’s a sign this field needs revision?
and if you had gone on to actually read the hemibrain connectome paper you would have gained some appreciation for the gargantuan achievement that it was. it took hundreds of person years to generate ground truth segmenting neurons by hand, to develop the ML techniques required to automatically segment the rest (extremely difficult problem) and to then validate the automatic segmentations. not to mention the insane effort it was to acquire a half petabyte EM image of a single fly at sub-synaptic resolution in the first place.
I gotta hand it to you though, the position of naivety you've delivered your middlebrow dismissal from is truly impressive in magnitude.
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CNNs actually are biologically inspired. The receptive field in a CNN mimics the way that cortical neurons only respond to stimuli in a restricted region of the visual field. Different cortical neurons have receptive fields that partially overlap to cover the whole visual field [1]. [1] - https://en.wikipedia.org/wiki/Convolutional_neural_network
Sure, and airplanes are inspired by birds. That doesn't mean that detailed studies of the Boeing 747 are going to unlock a lot of hitherto unknown mysteries of heron behaviour.
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What does this comment add to the discussion?
I dunno. My comment complained about the parent comment not adding positively to the discussion. And gave at least a bit of support for that complaint. Would you have preferred I emulate your style, and complain while providing no support for my complaint? Ok.