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NanoChat – The best ChatGPT that $100 can buy

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Re: NanoChat – The best ChatGPT that $100 can buy

#101

I'm doing a training run right now (started 20min ago). You can follow it at https://api.wandb.ai/links/sjd333-none/dsv4zkij Will share the resulting model once ready (4 hours from now) for anyone to test inference.

The comment beside the first chart

>Our main measure of progress. Bits per byte is, per Karpathy, "a much better measure than just the typical cross-entropy loss, because it further normalizes the loss on each token by the number of bytes of that token, making the metric tokenizer-invariant".

Is so blindingly obvious, that I'm ashamed to think that I didn't think do it when trialing my own tokenizer approach on tinystories. I might go back and have a look at how well my tokenizer compared to how well I imagined it compared.

Re: NanoChat – The best ChatGPT that $100 can buy

#102

> nanochat is also inspired by modded-nanoGPT Nice synergy here, the lineage is: Karpathy's nano-GPT -> Keller Jordan's modded-nanoGPT (a speedrun of training nanoGPT) -> NanoChat modded-nanoGPT [1] is a great project, well worth checking out, it's all about massively speeding up the training of a small GPT model. Notably it uses the author's Muon optimizer [2], rather than AdamW, (for the linear layers). [1] https:/…

Muon was invented by Keller Jordan (and then optimized by others) for the sake of this speedrunning competition. Even though it was invented less than a year ago, it has already been widely adopted as SOTA for model training

Re: NanoChat – The best ChatGPT that $100 can buy

#103

from their promotional material: >> Why is the sky blue? > The sky is blue due to an optical illusion called the Rayleigh Scattering Rayleigh Scattering is not an illusion but an effect. > […] particles are made up of tiny blue and violet particles that cause the light to bend in a particular way. ugh. no, there are no "tiny blue" particles in the sky.

Where did you find that?

Re: NanoChat – The best ChatGPT that $100 can buy

#104

> nanochat is also inspired by modded-nanoGPT Nice synergy here, the lineage is: Karpathy's nano-GPT -> Keller Jordan's modded-nanoGPT (a speedrun of training nanoGPT) -> NanoChat modded-nanoGPT [1] is a great project, well worth checking out, it's all about massively speeding up the training of a small GPT model. Notably it uses the author's Muon optimizer [2], rather than AdamW, (for the linear layers). [1] https:/…

Muon was invented by Keller Jordan (and then optimized by others) for the sake of this speedrunning competition. Even though it was invented less than a year ago, it has already been widely adopted as SOTA for model training

This is the common belief but not quite correct! The Muon update was proposed by Bernstein as the result of a theoretical paper suggesting concrete realizations of the theory, and Keller implemented it and added practical things to get it to work well (input/output AdamW, aggressive coefficients, post-Nesterov, etc).

Both share equal credit I feel (also, the paper's co-authors!), both put in a lot of hard work for it, though I tend to bring up Bernstein since he tends to be pretty quiet about it himself.

(Source: am experienced speedrunner who's been in these circles for a decent amount of time)

Re: NanoChat – The best ChatGPT that $100 can buy

#105

> nanochat is also inspired by modded-nanoGPT Nice synergy here, the lineage is: Karpathy's nano-GPT -> Keller Jordan's modded-nanoGPT (a speedrun of training nanoGPT) -> NanoChat modded-nanoGPT [1] is a great project, well worth checking out, it's all about massively speeding up the training of a small GPT model. Notably it uses the author's Muon optimizer [2], rather than AdamW, (for the linear layers). [1] https:/…

8xH100 is pretty wild for a single inference node.

Is this what production frontier LLMs are running inference with, or do they consume even more VRAM/compute?

At ~$8/hr, assuming a request takes 5 seconds to fulfill, you can service roughly 700ish requests. About $0.01 per request.

Is my math wrong?

Re: NanoChat – The best ChatGPT that $100 can buy

#106

> nanochat is also inspired by modded-nanoGPT Nice synergy here, the lineage is: Karpathy's nano-GPT -> Keller Jordan's modded-nanoGPT (a speedrun of training nanoGPT) -> NanoChat modded-nanoGPT [1] is a great project, well worth checking out, it's all about massively speeding up the training of a small GPT model. Notably it uses the author's Muon optimizer [2], rather than AdamW, (for the linear layers). [1] https:/…

8xH100 is pretty wild for a single inference node. Is this what production frontier LLMs are running inference with, or do they consume even more VRAM/compute? At ~$8/hr, assuming a request takes 5 seconds to fulfill, you can service roughly 700ish requests. About $0.01 per request. Is my math wrong?

This is the spec for a training node. The inference requires 80GB of VRAM, so significantly less compute.

Re: NanoChat – The best ChatGPT that $100 can buy

#107
Interesting exchange on the use of AI coding tools:

    curious how much did you write the code by hand of it?

    Karpathy: Good question, it's basically entirely hand-written (with tab autocomplete). I tried to use claude/codex agents a few times but they just didn't work well enough at all and net unhelpful, possibly the repo is too far off the data distribution.
https://x.com/karpathy/status/1977758204139331904

Re: NanoChat – The best ChatGPT that $100 can buy

#108

> nanochat is also inspired by modded-nanoGPT Nice synergy here, the lineage is: Karpathy's nano-GPT -> Keller Jordan's modded-nanoGPT (a speedrun of training nanoGPT) -> NanoChat modded-nanoGPT [1] is a great project, well worth checking out, it's all about massively speeding up the training of a small GPT model. Notably it uses the author's Muon optimizer [2], rather than AdamW, (for the linear layers). [1] https:/…

8xH100 is pretty wild for a single inference node. Is this what production frontier LLMs are running inference with, or do they consume even more VRAM/compute? At ~$8/hr, assuming a request takes 5 seconds to fulfill, you can service roughly 700ish requests. About $0.01 per request. Is my math wrong?

As vessenes wrote, that‘s for training. But a H100 can also process many requests in parallel.

Re: NanoChat – The best ChatGPT that $100 can buy

#109
post #4

I've always thought about the best way to contribute to humanity: number of people you help x how much you help them. I think what Karpathy is doing is one of the highest leverage ways to achieve that. Our current world is build on top of open source projects. This is possible because there are a lot of free resources to learn to code so anyone from anywhere in the world can learn and make a great piece of software.…

(This is a bit ranty, but due to a sincere desire for a better world, and being the recipient of personal attacks for believing a better world is achievable by a different path to others)

I feel like this point of view is an ideal not shared by one of the main branches of anti-AI sentiment.

The idea of intellectual property works against this. Rather than contributing to humanity directly, ownership of information is accumulated by individuals and then rented to humanity.

At the same time I agree that people should be able to have a livelihood that affords them the ability to create new intellectual contributions.

The service Karpathy is providing is also being provided by thousands of YouTube creators in a huge variety of topics. It's a little sad that so many must support their efforts with support their efforts with sponsorships from sources with varying degrees of ethical behaviour. Patreon is better but still not ideal. I sincerely believe this _is_ one of the best ways to contribute to society.

A recent Daily Show had Jon Stewart describe training AI as strip mining human knowledge. Training AI is regularly described as theft as if this position is a given without any counter argument possible. It is opinion masquerading as fact. This saddens me because it suggests to me that the war to control the narrative is being won by people who want to entrench a hypercapitalistic vision of ownership where not only is a particular expression of an idea ownable but also stakes a claim to own some of any ideas that come from viewing that expression.

I cannot see any way that this viewpoint would aid humanity as a whole, but instead assign benefits to a collection of individuals. The ability to trade intellectual property means that ownership inevitably gets passed to a smaller and smaller pool of individuals over time.

I think we really do need a new way to consider these issues in light of the modern world. When mentioning these thoughts to others a common refrain is that it doesn't matter because the powers that be (and their lobbyists) will prevent any fix from happening. I have never been fond of that particular fatalism, especially when it inhibits discussion of what would be better.

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