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Comment by evantbyrne | Hacker News Reader

Valuation matters quite a bit for continued funding.

Yes, and it can matter in a very bad way if you need to subsequently have a "down round" (more funding at a lower valuation).

Initial high valuations mean the founders get a lot of initial money giving up little stock. This can be awesome if they become strongly cash-flow positive before they run out of that much runway. But if not, they'll get crammed hard in subsequent rounds.

The more key question is: how much funding did they raise at that great valuation, and is it sufficient runway? Looks like €450 million plus an additional €120 million in convertible debt. Might be enough, depending on their expenses...

I'm not saying that either of your concerns are invalid. The LLM space is just the wrong place to be for investors who are worried about cash-flow positivity this early in the game. These models are crazy expensive to develop _currently_, but they is getting cheaper to train all the time. Meaning Mistral spent a fraction of what OpenAI did on GPT-3 to train their debut model, and that companies started one year from now will be spending a fraction of what both are spending presently to train their debut models.

YUP. Plus, the points at the end of your post, abt how much faster and cheaper it is getting to train new models indicates that Mistral may have hit a real sweet-spot. They are getting funding at a moment where the expectations are that huge capital is needed to build these models, just when those costs are declining, so the same investment will buy them a lot more runway than it did for previous competitors...

His point is with regards to reaching & maintaining profitability, not revenue spending.

It's too early for Mistral to focus on revenue. These AI companies are best thought of as moonshot projects.

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