Neural Network 3D Simulation
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- เผยแพร่เมื่อ 3 ก.ค. 2024
- Artificial Neural Networks 3D simulation.
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this is the coolest visualization of neural nets , i have ever seen. awesome
thanks
On an unrelated note, how do I give a comment -1 likes? Asking for a friend.
I agree
@@DenisDmitrievDeepRobotics th-cam.com/video/0U_FBHKYqRk/w-d-xo.html
I only love neural nets
"do you ever look at someone and wonder what is going on inside their head?"
@David Parry there's something going on inside of the head of a stereotypical stereotyper... unfortunately, you rarely get to see their regression model. oh well. who am I to judge?
@David Parry we may not have anything going on up there, but at least we're finally as smart as you.
Beautiful comment
Inside out? Where did I see this dialogue??
@@kinseysharon2672 inside out yes
that's the sound of my GTX 1050 screaming in pain..
@@w花b It's not.
@@w花b it's 50% slower
タメル Who exactly... said that?
@@w花b lol
This is such a cool project to have realized. Mind blowing. I would be interested in seeing a 'making of' this one. I think this is so beautiful it deserves being called art and needs a place on a screen on my wall, in an infinite loop.
The spiking network looked like what I'd imagine the brain would do
@hyper Computational neural networks model brains the same way a stick figure models a person. 웃 Adding a couple of lines for hair, might might the stick figure more closely model a person but it's still a bad model.
The interconnected nature of brain neurons might be partially modeled by neural networks but there is a lot of brain structure that is left out. It's not just a matter of scale, it's a matter of kind. For example, hormones are integral to brain function but neural nets have nothing that is analogous.
@@myothersoul1953 Hmmmm... All models are wrong, some are useful. Just because it is incomplete and doesn't get anywhere near the scale or complexity of the brain doesn't make it a bad model. What's important is to know what you are trying to learn from the model and if it serves that purpose it is a good model. Got a better idea for computationally modelling the brain?
@@TheRealJavahead That it doesn't get near the scale of complexity or include major components of the brain makes it a very poor model. Just like a stick figure is very poor model of human anatomy. Fortunately I am not in the business of modeling the brain because that's a very challenging task. Before a model could build how the brain functions needs to me understood. Many scholars across the world are working on parts of that. I'm sure they would tell they are making progress but are we no where near a complete understanding.
You are right, what you are trying to learn from the model is important to know. What aspects of the brain you model focuses will vary depending on whether you are interested on perception, cognition, emotions or motor control. It would be a huge mistake to think the such a simple model such as neural nets come close to representing any of those.
@@myothersoul1953 I do note that you have gone from categorising this as "a bad model" to "a poor model," next step might be that this is an "acceptable model." ;-) Relying on a reductio ad absurdum argument with your stick figure analogy is a false equivalency and doesn't support your assertion that this is a very poor (or bad) model. My point is, neither of us is in a position to determine how bad or good the model is without knowing its purpose.
@@TheRealJavahead The purpose of a model is to represent something. A poor model does a bad job of representing.
The reason I use the stick figure analogy is neural nets are often represent with lines a circles which are the same things used to draw stick figures. Stick figures only represent actual humans at the grosses of levels and neural nets resemble brain function at the grosses of levels (at best). That is neural nest are poor modes. But you are right, all analogies break down when pushed. The neural net analogy of the brain just needs the slightest breezy to fall down.
A better representation of neural nets would be a set of equations and procedures but that still doesn't match the brain. That's why they do such a bad job of representing how brains actually function.
This is amazing! It must've been a pain to render, considering the reflections and the frame-rate.
@DarkXSeries7 how about you can easily code it ;) in python or c#
This is amazing. I think this animation provides an incredibly intuitive understanding of how neural networks operate and a generalized interpretation of the fundamental mechanics of how they work.
I’m tryna make a neural net that discovers better neural nets through random trial and error. I’ll update you guys in 42000 years.
it has already been done by deepmind, they used neural network to tune hyperparameters of other neural network.
Already done. Check out Google's AutoML !!
Ah, but where is the neural network that tests neural networks on their ability to discover better neural networks?
@@J4hk2 you can always go deeper.
check out HyperNEAT
This is so cool. I love it. The spiking neural net was the coolest to watch. However, I couldn't help but notice that the spiking net wasn't working either.
They are super difficult to train. But they have been shown to be potentially more powerful than any ANN
@@kronek88 I think it depends on the problem you want to tackle, if you need a immediate approximation of something that requires a lot of computational power, then yes it's useful. But if you want a very precise result of a problem that isn't time consuming computationally. Then I think there are better algorithms than this one.
@MetraMan09 Yes, they mimic natural human brains. Like they can try and solve a task, approach it another way, check their answer, etc. It's kind of able to divide itsself up and basically train another couple neural nets to each do their thing to work together to solve complex tasks. It requires a LOT of computational resources but also can solve tasks static networks simply can not solve. It is, however, capable of being potentially dangerous if not done correctly. In theory, this kind of network is the kind of artificial intelligence that we theorize could pass for human in a turing test.
Also spiking neural network could create autonomous AI system, simulate memory and brain functions.
How? Can you elaborate?@@kotcraftchannelukraine6118
Machine learning makes sense to me at a very basic level but overall it still seems like magic to pass stimulus through a weighted network like that and it eventually can recognize patterns. Especially since this process leads to consciousness in human brains..
Суть всей "магии" заключается в том, что скрытый слой можно настроить так, что на любое входное значение, на выходе будет соответствующий нужный правильный выходной сигнал, который мы хотели получить.
That's amazing, best visualisation on a nn I've seen!! Great work!
Best video on youtube, deserves to be on main stream during football game commercials
The final version shows the back propagation in such a nice way! Well done
Beautiful !
Thanks Denis! Wonderful Creativity!
Hats off to the visualization!! Great job
Beautiful animations! You did a terrific job with the visualizations! Thank you, it brings great insights to a network!😊
absolutely incredible upload. Thank you!
This is crazy! Awesome visualization! Thx! :)
Thanks a lot man! Just incredible!
this is absolutely awesome! great work
Gorgeous! Great Work!
This is absolutely awesome, will share it on my social network, great job!
pls make 3d visulaization of that lol
Beautiful simulation! Thanks.
this is really amazing man , Exquisite
Excellent work, truly praiseworthy!
This is amazing. Thanks for sharing!
Absolutely AWESOME !!!!
This is absolutely beautiful.
We're currently developing our deep learning infrastructure in our group (freeD), and I work specifically on the visualizing tools.
I'm nowhere near your master level rendering skills and I kinda feel like crying right now.
This is absolutely awesome! music too!!
This is just like I imagined neural nets when I first heard about them. So glad you were able to make it real!
Denis.. Congratulations !!! Amazing render + animation
Great work !
This is a good spatial representation of the tensor as a hypergraph.
This visualization is so awesome that it feels like a science fiction movie!!! Great job!
Good job, Denis.
As someone who has written digit recognition networks from scratch and wrote a paper about it I must say that this is a really good 3d visualization of the neural net.
This is so satisfying to watch.
This is an awesome visualization job.
Amazing work
The image actually moves when you stop the clip. So cool!
It is not the image that moves - it is our brains automl experimenting with the bias hyperparameter.
Great job. Very exciting demonstration
The Coolest and the best visualization to understand neural nets! loved it!
I must say this video is brilliant!
Amazing video! great work
This is the coolest video I have ever watched.
So mesmerizing 😍, reason 1: The beauty of the network, reason2: The Background Score.
great animation - especially in combination with those sounds!
Actually even the music is awesome! it evokes curiosity and adds sense of mystery to the scene!
this visualization is next level, dope as hell
This is amazing! congrats my friend!
That's a lot of hidden layers ya got there Bucko.
I smell... overfitting
@@trentonpaul6376 Depends on the size of the dataset.
3? I guess that's a lot... If you're training on like an embedded graphics chip 😆
@@NilesBlackX 3 is for really non linear data. Written numbers doesn't need more than 1 hidden layer
@@terrykarekarem9180 MNIST doesn't, but proper handwriting training benefits from more layers. Adding punctuation, capitalization and diacritics makes the complexity rise above O(26) by an exponential.
Regardless, 3 hidden layers isn't 'a lot' by any means, since that's a relative term which implies greater than average, and average depth for a FFNN definitely isn't < 4.
WOW! amazing visualisation!
The spiking viz was amazing. Feels like in your brain, you're trying to understand the concept but it doesn't sink in and there is the darkness. And suddenly you get the point! It all lights up.
Very intuitive thanks!
hands down.. this is the best visualization of neural networks I have ever seen! just WOW
Amazing!
This is just awesome. I usually don’t comment on videos, but mate, this, is one of the best videos I’ve seen on yt
Ben Kahrmann what? Do you even know anything about machine learning?
super amazing, thanks a lot!!
Watching this made me reflect on life.
what a fantastic job!
It's really helpful. Thank you.
UNBELIEVABLE !! Wow... :) Thank you... !
Great video, thanks :)
Awesome video!
excellent visualisation
Man, that's awesome!
i subscribed for content like this!
Amazing appreciate your work
This really cool... The music also!
Professor! Too Cool!
That's beautiful!
Impressive man !
Awesome animation!
super cool video.
really cool visualization :)
Great work
Really good , thanks
Impressive!!
Perfect visualization.
A way to summarize it all this is great!
Absolutly amazing
This is fantastic. thankyou.
Music+visual both are cool
This is an amazing creation.
this is the most fascinating visual representation of the neural network
Great..Nice visualisation👍
Thank you
Wish the resolution was a bit higher and the bit rate didn't destroy the detail. I'd like to see this in at least 1440p
This is so cool.
Awesome!
It's sooo beautiful!
Really liked this
Денис, великолепная работа!
Хорошая демонстрация работы нейосетей для новичков этой сфере
most awwesome video for neural networks representation
Soo clear, helps us understand better how theyvwork
So cool!
Stunning
Sir, salute!
Spiking neural network gave me goose bumps.
Very cool!