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New neural network architecture inspired by neural system of a worm

quantamagazine.org

41–50 of 73 posts

Re: New neural network architecture inspired by neural system of a worm

#41

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

"I’m skeptical that biological systems will ever serve as a basis for ML nets in practice" First of all, ML engineers need to stop being so brainphiliacs, caring only about the 'neural networks' of the brain or brain-like systems. Lacrymaria olor has more intelligence, in terms of adapting to exploring/exploiting a given environment, than all our artificial neural networks combined and it has no neurons because it is…

ATP synthase's shape is my favorite go-to random fact :)

Re: New neural network architecture inspired by neural system of a worm

#42
post #14

The old neuroscience saying goes like this: "Human brain have billions of neurons and so it is too complex to understand, that's why neuroscience study simpler organisms. Flatworm's brain have 52 neurons. We have no idea how it works". Did finally something changed in this regard?

Many in the SciTech world who would shrink at even the thought of legitimizing Psychoanalysis should know that Freud only developed his psychological theory after trying and failing to create an entirely physical explanation for cognitive processes (Cf. "Project for a Scientific Psychology", Standard Edition I, pg.283).

The entire field of Psychology would not exist if not for this failure, a failure which is also an admittance that something as dynamic as the internal processes of the mind can in the first place only be understood in a social context, and that socio-psychological context is always in a constant flux. So the first thing to analyze, then, is what social processes, unique among humans, lead to the development of the psyche? Clear as light in day, the first word ever spoken by every person on this planet is a simple bilabial plosive repeated with an open-back vowel, "mama", or any of the many other similar words which all are formed in the same way and all for the same reason, its the only word a baby can articulate, and the first thing a baby learns is that when it speaks this word, milk and comfort arrive. So for Freud, everything goes back to the mother. The further one gets from that original source of comfort, the more complex means they employ to try and return, ceaselessly failing, always repeating the same thing over and over again. This is the origin of all language, all logic, and all of human society for Freud.

Certainly, people still feel the need to see a therapist, and yet there is some hope among people who work in AI that following along the path we have been, one day the AI and Neural-Networks will somehow "match" human intelligence, when humans were never truly intelligent in the first place and always have had to employ some means of artifice for productive labor and the transmission of knowledge. No true advances will be made until we recognize that AI is an outgrowth of human logic and human social labor, which, at the moment, somehow seems as though it will dominate us, even though it is our own creation.

Re: New neural network architecture inspired by neural system of a worm

#43

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

well i will agree on one thing....

corporations are constantly looking for a machine to do labor for free. life itself did not evolve just to do labor for a corporation so by trying to copy biological intelligent life, the result won't necessarily want to do what you tell it to do or be interested in your profit motives.

Re: New neural network architecture inspired by neural system of a worm

#44

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

“ which will necessarily be different than nature’s”

We are nature’s…

Re: New neural network architecture inspired by neural system of a worm

#45

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

[dead]

Re: New neural network architecture inspired by neural system of a worm

#46

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

We are nature. For all we know the solutions that cells came up with were derived in similar ways. Kevin Kelly’s “What Technology Wants” documents how evolution repeats itself in our technology.

Re: New neural network architecture inspired by neural system of a worm

#47

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

"I’m skeptical that biological systems will ever serve as a basis for ML nets in practice" First of all, ML engineers need to stop being so brainphiliacs, caring only about the 'neural networks' of the brain or brain-like systems. Lacrymaria olor has more intelligence, in terms of adapting to exploring/exploiting a given environment, than all our artificial neural networks combined and it has no neurons because it is…

If I had done synthetic biology my goal would have been to create cells that could reliably compute sine waves... by digitally computing taylor series polynomial approximations. Turns out engineering digital systems from cells is a remarkably challenging problem.

Examples of "switches" in biology abound, my favorite simple one is the Mating Type of Yeast: yeast have two sex types, and swap a small region of DNA in-place with variants to switch between them. Perfect example of self-modifying code!

Re: New neural network architecture inspired by neural system of a worm

#48

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

A hell lot of computation inside a neuron (in fact inside any cell) is chemical in nature. Proteins interacting, channels opening and closing, membrane doing membrainy stuff.. In fact their is a AND gate which is entirely chemical in nature.

Simulating chemical reactions are slow in silicon therefore chemical side is ignored.

If you glance over the graphs in chemistry papers, most of them are sigmoids. sigmoids are the sinusoid of chemical world. Its nice and heartening to see sinusoid appearing often in AI/ML as a fundamental computation.

Re: New neural network architecture inspired by neural system of a worm

#49

It makes a good headline, but reading over the paper ( https://www.nature.com/articles/s42256-022-00556-7.pdf ) it doesn’t seem biologically-inspired. It seems like they found a way to solve nonlinear equations in constant time via an approximation, then turned that into a neural net. More generally, I’m skeptical that biological systems will ever serve as a basis for ML nets in practice. But saying that out loud fee…

"I’m skeptical that biological systems will ever serve as a basis for ML nets in practice" First of all, ML engineers need to stop being so brainphiliacs, caring only about the 'neural networks' of the brain or brain-like systems. Lacrymaria olor has more intelligence, in terms of adapting to exploring/exploiting a given environment, than all our artificial neural networks combined and it has no neurons because it is…

Well, our brains are the most wonderful thing in the world, at least our brains say so.

Re: New neural network architecture inspired by neural system of a worm

#50

Earlier quoted context omitted.

"I’m skeptical that biological systems will ever serve as a basis for ML nets in practice" First of all, ML engineers need to stop being so brainphiliacs, caring only about the 'neural networks' of the brain or brain-like systems. Lacrymaria olor has more intelligence, in terms of adapting to exploring/exploiting a given environment, than all our artificial neural networks combined and it has no neurons because it is…

[1] linked above is an absolute powerhouse of a lecture by Michael Levin. Wow.

Thanks for calling it out, made me watch it. Absolutely fascinating. Incredible implications.
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