The code for my simple assembly language artificial neural network is now on github: github.com/ComputingMongoose/AsmANN
@academicpresentations60622 ай бұрын
Someone is going down a rabbit hole for nerdy people like me and we are very grateful for that
@ComputingMongoose2 ай бұрын
Glad you enjoyed it !
@iCrimzon2 ай бұрын
Ive always made jokes about writing NNs in x64 ASM or COBOL on programming language vids but this guy actually did it. You made my dream come true.
@ComputingMongoose2 ай бұрын
Always happy to make someone's dream come true 😅
@iCrimzon2 ай бұрын
@@ComputingMongoose now im gonna copy your code and put my money where my mouth is, learn to make NNs in asm even if its just twice for fun
@ComputingMongoose2 ай бұрын
@@iCrimzon Sounds great !
@elementare.2 ай бұрын
You're insane, I'll watch your videos from start. Thank u!
@ComputingMongoose2 ай бұрын
I'm glad you enjoyed it. Also, stay tuned for more. I will post in a few days a comparison with Pytorch Lightning for the same small data and will continue building more functionality for my ASM neural network.
@amadzarak77462 ай бұрын
Amazing work brother. Just subbed. Can’t wait to see ur future content and projects
@ComputingMongoose2 ай бұрын
Thanks! Glad to have you on board!
@aladinmovies2 ай бұрын
I am thinking about this (but I cannot program). Your work is incredible, keep it up! Thank you!
@ComputingMongoose2 ай бұрын
Glad you enjoyed it!
@Abhishekedutain29 күн бұрын
Ohh, man i love this really.
@JoeBurnett2 ай бұрын
Wow! This is great! I would also love seeing this adapted in ARM assembly if you’re taking suggestions for future videos.
@ComputingMongoose2 ай бұрын
Suggestions are always welcome! I am also playing with a Pi Pico at the moment, but not in assembly. In the future however I may do some ARM assembly as well.
@ChristopherLePage-o2f2 ай бұрын
Thank you for uploading this. I am researching how to write chatbots. This helps a lot. .pytorch is powerful software language... My personal favorite.. Cheers :)
@ComputingMongoose2 ай бұрын
Glad it was helpful!
@zamplifyАй бұрын
This is insane ❤
@ComputingMongooseАй бұрын
Glad you enjoyed it!
@fernandoadventius7098Ай бұрын
This is AMAZING!
@ComputingMongooseАй бұрын
Glad you enjoyed it !
@fernandoadventius7098Ай бұрын
@@ComputingMongoose : Subscribed. Please keep posting great Assembly Codes with Neurals.
@ComputingMongooseАй бұрын
@@fernandoadventius7098 My other assembly videos are also somewhat related. They will later be assembled into a larger ANN allowing loading external data.
@box92832 ай бұрын
YOU MAD LAD! LOVE YOU MAN!
@RichardLofty2 ай бұрын
Test your performance against the same network written in other languages!
@ComputingMongoose2 ай бұрын
I do have a video exactly about this: ASM vs Pytorch Lightning kzbin.info/www/bejne/oGqnkoCYaNh7rdU
@shreymaru16132 ай бұрын
Crazy idea and efforts to make this 🤯
@ComputingMongoose2 ай бұрын
Glad you enjoyed it! And not really that much effort. I always enjoyed assembly and I'm currently working in AI research, so I was really curious how it compares to have it in ASM vs Python. In a few days I will post a video with the speed comparison of a similar small network implemented in Pytorch Lightning, for the same data and no gpu. So stay tuned for more crazy stuff 😎 🙃
@fhmisml2 ай бұрын
somehow youtube brought me here and this is insane, +1 sub
@ComputingMongoose2 ай бұрын
Glad KZbin worked its magic this time !
@alexleo4863Ай бұрын
Creating a neural network with bare hands, this is insane
@ComputingMongooseАй бұрын
Glad you enjoyed it!
@therobotocracy2 ай бұрын
I was thinking about this.
@ComputingMongoose2 ай бұрын
Judging from the comments, views and likes, it seems a lot of people were thinking about this.
@vanvicka12 ай бұрын
This is God mode 😂❤
@ComputingMongoose2 ай бұрын
🤣🤣🤣 In this case, Welcome to Heaven 😇
@ddmasterdonАй бұрын
Com'om let us all contrib to the repo to add more layers ⚜
@ComputingMongooseАй бұрын
Pull requests are welcome
@kenedi9872 ай бұрын
amazing video,
@ComputingMongoose2 ай бұрын
Thank you!
@tusharrakhunde99212 ай бұрын
You're amazing 😮
@corelativ.2 ай бұрын
Such a great video , perhaps could you make an explanation how to learn code on your own way ?
@ComputingMongoose2 ай бұрын
Thank you. This is actually the second request for a learning video. I will try to make one, but not in the very near future since it will take me a while to cover the architecture and the basic instructions.
@felixhex2 ай бұрын
Could we use AVX extensions to accelerate our computation?
@ComputingMongoose2 ай бұрын
For larger networks indeed it should be possible to accelerate it with AVX (or other SIMD extensions). I will likely explore this in the future, after adding more complexity to the network.
@notsojharedtroll232 ай бұрын
I was discussing on a Some comments over videos about this and fucking hell. Very cracked
@ComputingMongoose2 ай бұрын
Glad you enjoyed it
@youtubpremiu00082 ай бұрын
i recently came across your channel and it seems you pretty great at dealing things at hardware level i also want to study and know about the computer hardware and but the problem is i didn't have any organized set of resources which make a lot harder to understand things i do have a pretty knowledge about the computers though but still there so many missing puzzles that are yet to fit to fully understand can you help me please.
@gac57002 ай бұрын
nand2tetris (building a computer from first principles), computer systems a programmer's perspective, operating systems three easy pieces, computer networking a top down approach
@ComputingMongoose2 ай бұрын
I see user @gac5700 already replied with a nice set of resources. I want to add that sometimes it may be easier to start learning using a simpler CPU (either a microcontroller or an older CPU for example). All CPUs have registers, buses, addresses, data, etc. In a simpler one you can play with a reduced set of such registers and instructions. I would recommend Intel 8080 (you can find a bunch of emulators) or Intel 8088 (again a bunch of emulators or even real hardware). 8088 is the basis for modern x86 architectures and the basic instructions are the same (also when a modern CPU turns on it is basically in 8088 mode). On the microcontroller side, you can easily start playing with a Pi Pico or similar and even create some circuits. Pi Pico has a modern ARM-based or RISC-V based CPU (these are different from x86). It all depends what you want to do with what you learn.
@ComputingMongoose2 ай бұрын
Good ones!
@burnytech2 ай бұрын
nice
@ComputingMongoose2 ай бұрын
Thanks
@Accanfo2 ай бұрын
Nuts
@GizmoJunk2 ай бұрын
Is this Giskard; is this you, from the The Engineering Guild? It sure sounds like it's you.
@ComputingMongoose2 ай бұрын
No.
@ChungusTheLarge2 ай бұрын
Don't send this video to a PM, or you will never be allowed to use TensorFlow again
@ComputingMongoose2 ай бұрын
🤣🤣🤣
@turnoff75722 ай бұрын
Here before your chammel gets some traction. Would you be willing to make x86 16 or 32bit assembly tutorials for absolute beginners to programming.
@ComputingMongoose2 ай бұрын
I was considering some beginner tutorials (not in the very near future though), but I was thinking about modern 64-bit stuff. Why are you interested in 16 or 32 bit as a beginner? From a job perspective, nowadays almost everything runs in 64-bit. If you want to do some code optimization or write routines for drivers in assembly you are likely working on 64-bit systems. Alternatively, you could learn ARM / RISC-V for things like embedded systems.
@filipzdravkovic71342 ай бұрын
@@ComputingMongoose What tutorial or course would you recommend to a person who is completely new to assembler ?
@ComputingMongoose2 ай бұрын
@@filipzdravkovic7134 I'm sorry, but I don't have a particular tutorial or resource in mind. My experience was accumulated over many years from many sources and through work. I do hope you will find a good resource.
@faridfael88262 ай бұрын
You are legend 😂
@ALTINSEA12 ай бұрын
Was this faster since its low level languae?
@ComputingMongoose2 ай бұрын
Actually yes. I will upload a video comparing this to Pytorch Lightning in a couple of days, using the same data and no gpu.