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LLM Visualization
- nickdothutton 1y agoSomehow this is both useful and aesthetically pleasing/satisfying. Well done!
- JackYoustra 1y agoI saw this back on the first HN post and man. One of my favorite pedagogical tools to use.
- b0dhimind 1y agoDangit dunno what Add-on is interfering but not working on my current Firefox profile. (same user.js in a different profile but its working fine there)
- sema4hacker 1y agoFantastic graphics that immediately make me think "what a kluge, no way this will achieve AGI".
- felipelalli 1y agoIncredibly amazing.
- owenversteeg 1y agoThis is a fantastic visualization, but it and the rest of the literature all boil down to "input text goes in, we do some linear algebra on that and the model weights together, and... magic comes out." Of course, the precise incantations of the linear algebra _are_ important, the whole thing is worthless without the attention method, but that's just a method, a fairly simple one at that relative to what it does. How does it get from the ideas to the intelligence? What if we saw intelligence as the ideas themselves?
- daniel321r4 1y ago[dead]
- jkingsman 1y agoWow, this is tremendously intricate and very impressive! What an awesome way to visualize the process.
- dang 1y agoRelated. Others? LLM Visualization - https://news.ycombinator.com/item?id=38505211 https://news.ycombinator.com/item?id=38505211 - Dec 2023 (131 comments)
- dpflan 1y agoHere is another take on visualizing transformers from Georgia Tech researchers: https://poloclub.github.io/transformer-explainer/ https://poloclub.github.io/transformer-explainer/ The Illustrated Transformer: https://jalammar.github.io/illustrated-transformer/ https://jalammar.github.io/illustrated-transformer/ Sebastian Raschka, PhD has a post on the architectures: https://magazine.sebastianraschka.com/p/from-gpt-2-to-gpt-oss-analyzing-the https://magazine.sebastianraschka.com/p/from-gpt-2-to-gpt-os... This HN comment has numerous resources: https://news.ycombinator.com/item?id=35712334 https://news.ycombinator.com/item?id=35712334
- th0ma5 1y agoI always liked this visualization from a while ago https://alphacode.deepmind.com/ https://alphacode.deepmind.com/ (Press play, zoom all the way out and scroll down if on mobile)
- aaa_2006 1y agoThis is awesome! Would be cool if these LLM visualizations were turned into teaching tools, like showing how attention moves during generation or how prompts shift the model’s output. Feels like that kind of interactive view could really help people get what’s going on under the hood.
- martin-t 1y agoI wish n-gate was still around. He would note the high vote to comment ratio. When HN has little to say, it's always a sign of a high quality very technical article. On a more serious note, this highlights a deeper issue with HN, similar sites and the attention economy. When an article takes a lot of time to read: - The only people commenting at first have no read it. - By the time you are done reading it, it's no longer visible on the front page so new people are not coming in anymore and the discussion appears dead. This discourages people who read it from making thoughtful comments because few people will read it. - There are people who wait for the discussion to die down so they can read it without missing the later thoughtful comments but they are discouraged from participating earlier while the discussion is alive because then they'd have to wade through the constantly changing discussion and separate what they have already seen from what they haven't. --- Back on topic, I'd love to see this with weights from an actual working model and a customizable input text so we could see how both the seed and input affects the output. And also a way to explore vectors representing "meanings" the way 3blue1brown did in his LLM videos.
- cellular 1y agoWith weights on an actual model: https://youtu.be/KSovbSkARYw https://youtu.be/KSovbSkARYw "Adding numbers. the green line are the weights. At the top: the red circle indicates an incorrect answer. the green circle indicates a correct answer. As the NN learns, the weights adjust and the green circle appears more often. "
- QuantumNoodle 1y agoFascinating visualization. To think, we can visualize the entire* process but cannot understand the inner workings of a model with regards to decision making. This was true last I looked into it a year or so ago, not aware on any advancements in that aspect.
- xwolfi 1y agoWe completely understand the inner workings and can see the emerging result, but it's hard for us to accept that it took no decision and just chose a nice word to complete a sentence, time after time, and sounds intelligent. Then it says Strawberry has two r, and you're like ok, it's just a huge statistical matrix with zero value.
- baq 1y agoHammers have zero value when you’re trying to cook food with them, too.
- psychoslave 1y agohttps://m.youtube.com/watch?v=LhaBkvneMW8 https://m.youtube.com/watch?v=LhaBkvneMW8
- ares623 1y agoHammers that sucked up half a trillion dollars from the economy and are basically propping it up, and the makers and everyone else around them are shouting from rooftops that they are great at cooking food.
- noisy_boy 1y agoAnd your boss's boss and his boss and the owner and the investors and every other rando is asking whether we are cooking with hammers yet and if not, why because how else can we get rid of those expensive cooks who use kitchenware.
- aj-seven 1y ago[dead]
- pkdpic 1y agoI just want to say that this is fantastic and I'm planning to show it to my 5yo son's computer club.
- ksvarma 1y agoWow, just incredible. What a piece of art. Thank you for your work!!
- kittikitti 1y agoThis is really great, and I'm excited to deep dive into it. I think combined with observability tools, this resource empowers scientists to break open what people presume to be a "black box".
- gcid73 1y agoOk now I get it, this is an incredible resource. Thanks for your effort.
- southp 1y agoIt's fascinating, even though my knowledge to LLM is so limited that I don't really understand what's happening. I'm curious how the examples are plotted and how much resemblance they are to the real models, though. If one day we could reliably plot a LLM into modules like this using an algorithm, does that mean we would be able to turn LLMs into chips, rather than data centers?
- southp 1y agoI'm new in this area and I've learned a lot from the replies. Thanks for sharing, folks :) Just to clarify, when I said "to turn LLMs into chips", I didn't mean to run it on CPU/GPU/TPU or any general purpose computing units, but to hardwire the entire LLM as a chip. Rethinking about it, the answer is likely yes since it's serializable. However, given how fast the models are evolving, the business value might be quite dim at the moment.
- xwolfi 1y ago... you can run a good LLM on a macbook laptop.
- psychoslave 1y agoWhich one? I tried a few months ago, and it was like one word every few seconds. I didn't dig far though, just installing the llm tool which apparently is doing what 'mise' is doing for programming environment, and went with first localy runnable suggestion I could found.
- _1 1y agoYou might need to play around with the default settings. One of the first models I tried running on my Mac was really slow.. Turns out it was preallocating a long context window that wouldn't fit in the GPU memory, so it ran on the CPU.
- psychoslave 1y agoCan you recommend some tutorial?
- mia697660 1y ago[dead]
- weego 1y agoI have a related question I guess, it relates to how I can visualise the foundations of this beyond just a code implementation. Where does this come from in abstract/math? Did we not have it before, or did we just not consider it an avenue to go into? Or is it just simply the idea of scraping the entirety of human knowledge was just not considered until someone said "well, we could just scrape everything?" Were there recent breakthroughs from what we've understood about ML that have lead to this current explosion of research and pattern discovery and refinement?
- blahgeek 1y agoI think it’s two fold: the evolution of hardware (GPUs) that give us enough compute power, and the invention of novel algorithms (transformer) that can effectively consume and understand all these data.
- Viibrant 1y agoFrom my understanding, the field of AI was all about knowledge representation. Researchers in the past handcrafted representations with expert knowledge but that only gets you so far. So instead, why not learn representations from data directly? That's the current stage we're at and is the whole scraping the entirety of human knowledge thing. Compute has gotten good enough and data readily accessible to do all this, plus we have architectures like transformers that scale really nicely.
- navigate8310 1y ago468 upvotes and 24 comments, something's strange.
- FergusArgyll 1y agoI find that to be a sign of a great submission; it's not contentious but everyone loves it
- m4r71n 1y agoKarpathy walks through this visualization in https://www.youtube.com/watch?v=7xTGNNLPyMI https://www.youtube.com/watch?v=7xTGNNLPyMI, well worth a watch!
- FergusArgyll 1y agoIs there a similar resource for understanding backprop / the training sequence?
- cellular 1y agohttps://youtu.be/DTRNOJBIDMY https://youtu.be/DTRNOJBIDMY For multilayer back propagation. Skips all the obtuse subscript jargon which differs in every text out there!