It’s kinda weird thinking deep tech companies should be profitable a year in.
Like it takes time to make lots of money and it’s really hard to build state of the art models.
Reality is this market is huge and growing massively as it is so much more efficient to use these models than many (but not all) tasks.
At stability I told team to focus on shipping models as next year is the year for generative media where we are the leader as language models go to the edge.
They didn't say that companies should be profitable at a year in.
To my mind they just seemed to be responding to the slightly clickbait-y title, which focuses on the valuation, which has some significance but is still pretty abstract. Still, headlines love the word "billion".
The straight-news version of the headline would probably focus more on a16z's new round.
I acknowledge it’s easy to be an armchair critic. You are the ones in battlefield doing real work and pushing the edge.
The thing is I don’t want the pro-open-source players to fizzle out and implode because funding dried up and they have no path to self sustainability.
AGI could be 6 months away or 6 decades away.
E.g Cruise has a high probability of imploding. They raised too much and didn’t deliver. Now California has revoked their license for driverless cars.
I’m 100% sure AGI, driverless cars and amazing robots will come. Fairly convinced the ones who get us there will be the cockroaches and not the dinosaurs.
I think its also tough at the early stage of the diffusion (aha) of innovation curve, we are at the point of early adopters and high churn before mass adoption of these technologies over the coming years as they are good enough, fast enough and cheap enough.
AGI is a bit of a canard imo, its not really actionable on a business sense.
Profitability likewise means jack shit. You just need to be have a successful acquisition by a lazy dinosaur or go make enough income to go public. You can lose money for 10yrs straight while transferring wealth from the public to the investors/owners. With that said, I'm short Mistral for them being French. I have absolute zero faith in EU based orgs.
On profitability, For all the new comers, I don't think anyone can wager that any of them is going to make money. Capital efficiency is overrated so long as they can survive for the next year+, they are all trying to corner the market and OpenAI is the one that seems to have found a way to milk the cow for now. I truly believe that the true hitmakers are yet to enter the scene.
This is just tangential, but I wouldn't call their APIs "nice", I'd be far less charitable. I spent a few hours (because that's how long it took to figure out the API, due to almost zero documentation) and wrote a nicer Python layer:
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...
Instead of "path to profitability", I think path to ROI is more appropriate, though.
WhatsApp never had a path to profitability, but it had a clear path to ROI by building a unique and massive user base that major social networks would fight for.
Until a company is consistently showing growth in revenue and a path to sustainable profitability, valuation is essentially wild speculation.
OpenAI is wildly unprofitable right now. The revenue they make is through nice APIs.
What is Mistral’s plan for profitability?
Right now stability AI is in dumps and looking for a buyer.
Only companies I see making money in AI are those who live like cockroaches and very capital efficient. Midjourney and Comma.ai come to mind.
Very much applaud them for open release of models and weights.