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Comment by jsheard | Hacker News Reader

Where is the money for training big expensive open source models going to come from once the investor hype blows over and companies like Mistral actually have to try to make a profit? They currently have negligible revenue despite their $6 billion valuation, that status quo can't be maintained forever.

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I guess a parallel could be made to vue, react and svelte. Who would bother investing so much time, energy and money into developing an open-source front-end framework for free/funded by corps that use it? Vue, react and svelte don't earn anything I suppose, but then again I'm no expert in this field.

I guess like some other here have commented, techniques have to be implemented to minimize training time and I suppose the government needs to fund studies which then will benefit the general population to make it possible to train and host AI models.

But I honestly have no idea ... I'm just a simple dev running my mistral on a single RTX lol

We'll see, but I think the equivalent to people donating their own time to a traditional open source project would be people donating spare compute time for training, and nobody has figured out an effective way to do a Folding@home-style distributed version of ML training yet. Having to train open source models on big expensive compute clusters, and bid against commercial interests who also want to rent those clusters could be likened to having to pay everyone working on a traditional open source project full market rate for their time.

It might be great for everyone if AI research had a reason to look into non brute force training methods.

LLM training isn't even remotely brute force[1], even with tons of clever tricks to reduce the amount of compute necessary it's still fundamentally just a really hard problem.

[1]: https://youtu.be/MD2fYip6QsQ

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