> you would just eventually train and deploy your own model
Just train an LLM? It's really not that easy! Even if it was, it'd be like how people can "just" run their own email service. Hosted email API is not rocket science but in practice companies all choose to pay Microsoft or Google to do it. Doing these things isn't a core competitive advantage so it gets outsourced.
> The fact that Meta rather inexplicably chooses to give away assets that cost millions or billions to create doesn't mean LLMs aren't a product
EDIT
Your last paragraph makes an excellent point. In the near future, I could see big corps paying OpenAI (or a competitor) to train a private LLM on their squillion internal documents and build a very good helpdesk agent. (Legal and compliance would love it.)
Giving expensive things away for free is a great marketing technique that has been used since time immemorial, so why startups like Stability do it is somewhat understandable. And OpenAI uses free API access as a loss leader for their API product so that's understandable too.
Why Meta/Google/others do open weight releases is a bit less clear. Recall though that the first Llama wasn't really an open source release. You had to sign a document saying you were a researcher to get the weights, and that document was an agreement to keep the weights secret. Two people signed the documents, anonymously compared their weights, discovered they weren't watermarked (i.e. Meta didn't take this seriously, it was a sop to their AI politics/safety people) and promptly leaked them.
Presumably this was useful for the more libertarian wing of Meta as they could then prove the sky wouldn't fall, and so the influence shifted towards those arguing for more openness in research in general. With that Rubicon crossed other companies didn't see competitive advantage in withholding their similar sized models anymore and followed the leader, so to speak.
Sometimes it also feels like Meta may have over-purchased GPUs and - lacking a public cloud - have just decided to let their researchers do what they wanted. Which is great for the public! But we mustn't be too overconfident. This is really only possible because of Zuckerberg's unique corporate structure that makes him unfirable, combined with Meta being a big data company. It's really benefiting all of humanity here because he's invulnerable to board action so doesn't have to worry about heat from shareholders over 'wasting' money like this.
There's a lot of R&D being done right now on shrinking models whilst preserving quality, so hopefully the Zuck's generosity is enough to ride the open AI research community through the hard times when you needed billions to train LLMs.
These things are products.
The UX of the AI applications is the moat and the infrastructure providers behind those applications is pretty much always OpenAI and Anthropic at the moment because running your own open source LLMs (which are inferior out of the box) at scale is not cheap or easy to do it right - same reason most companies use cloud. Agree that once you hit super scale then you can run your own infrastructure but there are thousand of companies who won’t get that far and still need an LLM.
Then they don't suck as much.
With OpenAI and Claude, you throw some text instructions and you get back the answers which are surprisingly correct (minus a few exceptions). In order to replicate that with Llama you'd probably need N-hundreds finetunes and a model to decide which finetunes to use.
Would you consider Database to be a product ?
SQLLite , PostGres etc. are free and yet we have Oracle , Mongodb and MS SQL doing billions in revenues.
I imagine you meant to say that LLMs are comoditized.
Getting the correct words here is important, as you can see by all the people disagreeing on the literal interpretation of your post.
And yeah. LLMs have got the fastest transition from highly innovative singular product to plain commodity I've ever seen or read about. BSD licensed software libraries do not move that quickly. They were mostly not even adopted yet, and have a huge barrier to entry, what makes it much more of a feat.
Yep, much better way of putting it!
Well, you are humbly wrong then.
> You would just eventually train and deploy your own model because an LLM is not a product.
Hallucinations aren't exclusive to LLMs it seems.
The only play for OpenAI et al in my opinion is to try to pull up the draw bridge behind them by getting legislation passed which makes compliance prohibitively difficult if that's not your core business.