For the visual learners, here's a classic intro to how LLMs work: https://bbycroft.net/llm

Lovely visualization. I like the very concrete depiction of middle layers "recognizing features", that make the whole machine feel more plausible. I'm also a fan of visualizing things, but I think its important to appreciate that some things (like 10,000 dimension vector as the input, or even a 100 dimension vector as an output) can't be concretely visualized, and you have to develop intuitions in more roundabout ways.

I hope make more of these, I'd love to see a transformer presented more clearly.

This is just scratching the surface -- where neural networks were thirty years ago: https://en.wikipedia.org/wiki/MNIST_database

If you want to understand neural networks, keep going.

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The original Show HN, https://news.ycombinator.com/item?id=44633725

- while impressive, it still doesnt tell me why a neural network is architected the way it is and that my bois is where this guy comes in https://threads.championswimmer.in/p/why-are-neural-networks...

- make a visualization of the article above and it would be the biggest aha moment in tech

Really cool. The animations within a frame work well.

This Welch Labs video is very helpful: https://www.youtube.com/watch?v=qx7hirqgfuU

Super cool visualization Found this vid by 3Blue1Brown super helpful for visualizing transformers as well. https://www.youtube.com/watch?v=wjZofJX0v4M&t=1198s Show 1 reply

I like the CRT-like filter effect.

I like the style of the site it has a "vintage" look

Don't think it's moire effect but yeah looking at the pattern

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Oh wow, this looks like a 3d render of a perceptron when I started reading about neural networks. I guess essentially neural networks are built based on that idea? Inputs > weight function to to adjust the final output to desired values? Show 3 replies

I love this visual article as well:

https://mlu-explain.github.io/neural-networks/

Great explanation, but the last question is quite simple. You determine the weights via brute force. Simply running a large amount of data where you have the input as well as the correct output (handwriting to text in this case). Show 1 reply

Spent 10 minutes on the site and I think this is where I'll start my day from next week! I just love visual based learning.

This visualizations reminds me of the 3blue1brown videos. Show 1 reply

As someone who does not use Twitter, I suggest adding RSS to your site.

Nice work

I get 3fps on my chrome, most likely due to disabled HW acceleration Show 1 reply

Nice visuals, but misses the mark. Neural networks transform vector spaces, and collect points into bins. This visualization shows the structure of the computation. This is akin to displaying a Matrix vector multiplication in Wx + b notation, except W,x,and b have more exciting displays.

It completely misses the mark on what it means to 'weight' (linearly transform), bias (affine transform) and then non-linearly transform (i.e, 'collect') points into bins

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Great visualization!

very cool stuff