9 ms·
Interestingly, this is not a new result; people have been doing stuff like this since at least the 90s, most notably Steve Potter at GA Tech and Tom DeMarse in
by frisco 3y ago
Interestingly, this is not a new result; people have been doing stuff like this since at least the 90s, most notably Steve Potter at GA Tech and Tom DeMarse in Florida.[1][2] (I built a shitty counterstrike aimbot using a cultured neural network in college based on their papers.)
There was a lot of coverage back in 2004 when DeMarse hooked it up to a flight simulator and claimed it was flying an F-22 [3] (lol, but I don't blame him too much...)
The basic idea is that if you culture neurons on an electrode array (not that hard) you can pick some electrodes to be "inputs" and some to be "outputs" and then when you stimulate both ends the cells wire together more or less according to Hebb's rule[4] and can learn fairly complex nonlinear mappings.
On the other hand, these cultures have essentially no advantage over digital computers and modern machine learning models. Once you get through the initial cool factor, you realize it's a pain to keep the culture perfectly sterile, fed, supplied with the right gases, among many other practical problems, for a model which is just much less powerful, introspectable, and debuggable than is possible on digital computers.
[1] https://bpb-us-w2.wpmucdn.com/sites.gatech.edu/dist/f/516/files/2010/10/DeMarseAutonRobots2001.pdf https://bpb-us-w2.wpmucdn.com/sites.gatech.edu/dist/f/516/fi...
[2] https://potterlab.gatech.edu/labs/potter/animat/ https://potterlab.gatech.edu/labs/potter/animat/
[3] https://www.cnn.com/2004/TECH/11/02/brain.dish/ https://www.cnn.com/2004/TECH/11/02/brain.dish/
[4] https://en.wikipedia.org/wiki/Hebbian_theory https://en.wikipedia.org/wiki/Hebbian_theory
- sroussey 3y agoWe have lots of these cultures around for drug testing. I wonder if the “brain” playing pong affects the tests in any way.
- api 3y agoWhat I always wonder about with these systems is how feedback was delivered to the cultured neurons. How do we tell them they're doing things correctly? Or is this some form of unsupervised learning with them?
- seydor 3y agothe original paper is available https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6 https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6 They used a specific region of the electrode array to deliver the "reward" signal which was a regular predictable pulse pattern . An error was represented with unpredictable activity
- dr_dshiv 3y agoWait, wtf, sentience? “In vitro neurons learn and exhibit sentience when embodied in a simulated game-world”
- seydor 3y agoThe paper used unfortunate terminology everywhere even if there were negative comments about in the preprint. It caused a number of reactions https://pubmed.ncbi.nlm.nih.gov/36863319/ https://pubmed.ncbi.nlm.nih.gov/36863319/
- fnordpiglet 3y agoI was with you up to “once you get over the cool factor.” It seems impossible to get over how cool it is to have a minibrain playing video games. Having one of those at home must really impress the girls.
- spaceman_2020 3y ago“Meet my brother. He’s adopted”
- fnordpiglet 3y agoAll he does is lay around playing pong
- zapdrive 3y ago[flagged]
- valianteffort 3y agoWhat do you mean? You don't want the comment section on HN to be reduced to low effort, repetitive humor for the purpose of karma whoring?
- _yb2s 3y agoMoreover, if there are girls not impressed by this, you will know, and have really dodged a bullet.
- _yb2s 3y ago> The basic idea is that if you culture neurons on an electrode array (not that hard) you can pick some electrodes to be "inputs" and some to be "outputs" and then when you stimulate both ends the cells wire together more or less according to Hebb's rule[4] and can learn fairly complex nonlinear mappings. This is fascinating, can you clarify it a bit? Do you 'stimulate', e.g. apply electrical potential to both the inputs and outputs to represent each instance of training data, without any physical distinction between input and output at that stage? And then if you apply the potential only the inputs, you can then read predictions on the outputs?
- SubiculumCode 3y agoOnce AI gets over the initial cool factor that humans are wet-tech, they'll realize it's a pain to keep the human culture perfectly sterile, fed, supplied with the right gases, among many other practical problems, only for a model which is just much less powerful, introspectable, and debuggable than is possible on digital computers.
- ungamedplayer 3y agoThat was beautiful.
- xvilka 3y ago> On the other hand, these cultures have essentially no advantage over digital computers and modern machine learning models. Absolutely false. While it's indeed hard to keep it alive, real neurons are far more sophisticated than what AI researchers think they are. Modern digital so called neural networks are built on the outdated and oversimplified knowledge of neuron model, almost a century-old by now.
- seydor 3y agosophisticated is not a scientific word. they are complex and complicated, and the voltage dynamics across their elaborate membrane takes a lot of computers to simulate. But we don't really know what it is doing or if it is particularly sophisticated. Nature has found a lot of complex solutions to simple problems because it does not know better. We don't know how well it did with intelligence
- xvilka 3y agoWe already do know[1] the a single neuron has the same level of complexity as multilayered digital "neural network". [1] https://www.youtube.com/watch?v=hmtQPrH-gC4 https://www.youtube.com/watch?v=hmtQPrH-gC4
- seydor 3y agoThere are different studies proposing 2 or 3 layer network for representing the input-firing curve of neurons (Usually hippocampal). Of course, neural networks are abritrary approximators so the size of the network determines the fidelity of the reproduction. But it 's not clear what the firing does and what amount of complexity in the firing code is reduntant or useful for making AI systems
- uoaei 3y agoWhat is clear however is the evident power savings in implementing cultured neural networks vs digital ones for a given network capacity.
- spagettnet 3y agoDo you have a writeup or video of the aim bot you made? Would love to see it!
- ge96 3y agoTangent: was thinking it would be cool if you had a bio mass that could connect to a pcie slot and act as a graphics card. That would be some really impressive tech. Build circuits in the goo with floating particles.
- auastro 3y agoOne of the early CorticalLabs founders here. This is like dissing AlphaZero because "This is not a new result; computers have been playing chess since the 50s!". We are standing, as always, on the shoulders of giants. Steve Potter is one of our advisors. We've improved on every axis 10x. We process over 1000 signal channels in real-time and respond with sub-millisecond latency from our simulated environment. We've recorded thousands of hours of play time from mouse and human neurons. We're investigating biological learning with top neuroscientists from around the globe. This is by far the most rigorous, extensive and technologically advanced work on in-vitro learning ever produced. Our work goes well beyond Hebbian, "fire together, wire together", We have follow up papers in the pipeline that study internal non-linear dynamics and show how whole-network dynamics changes during game play and learning. Being able to observe and measure cognition has huge applications to drug testing and discovery. For background, frisco (the above commenter) helped start NeuralLink. Consider this, our DishBrain is a completely reproducible, highly controlled test bed for brain computer interfaces. This will massively accelerate neural interface development, all without sacrificing any chimpanzees. > On the other hand, these cultures have essentially no advantage over digital computers and modern machine learning models The brain is the single existing example of general intelligence. A human brain can do more computation than our largest super computers with 20W of power (a million times more efficient). Trillions of interacting synaptic circuits, rewiring themselves on the molecular level. Biological learning is the only game in town, honed by a eons of evolution. There are fundamental physical limits to hot slabs of silicon. Do you have a single credible proposal for building such a machine that isn't growing one? > (I built a shitty counterstrike aimbot using a cultured neural network in college based on their papers.) Nice humble brag. I trained neural networks from my bedroom in highschool in 2002. There is a long road between a cool university project and building a world class neuroscience R&D company, you know that! CoriticalLabs is always open to collaborations. We're here to talk when you want to integrate some of our cutting-edge neuroscience technology with your work. Instead grumbling about the 90's, let's look forward to what neuroscience looks like in the 2030's
- thaumasiotes 3y ago> A human brain can do more computation than our largest super computers with 20W of power The power needs of the human brain are likely to be measured quite accurately. The same is not true of the "amount of computation" performed by the brain. How are you measuring that?