Looks like open-source is just a marketing tool for AI companies before they have a good enough model to sell. I guess we have to look for what Meta is going to do with LlaMA 3.
IMO, it is just a new version of wage/code theft with a “public good” side-story to convince the gullible that it is somehow “better” and “fair”, when everyone involved were making money, just not as much money as they could be taking with a little bit of court-supported code theft and a hand-waive of “volunteerism”.
However, from a marketing perspective - think of who the users of an open model are. They're people who, for one reason or another, don't want to use OpenAI's APIs.
When selling a hosted API to a group predominantly comprised of people who reject hosted APIs - you've got to expect some push back.
From my perspective, I want to use the best model. But maybe as models improve and for certain use cases that will start to change. If I work on a project that has certain parts that are fulfilled by Mistral and can reduce cost, that's cool.
I'm surprised how expensive this model is compared to GPT-4. Only ~20% cheaper
I'm guessing all currently available paid options are operating at a (perhaps significant) loss in order to capture market share. So it might be that nobody can afford to push the prices even lower without significant risk of running out of money before any "market capture" can realistically be expected to happen...
You say you know people who use and fine tune Mistral / variants
You know what you can't do with Mistral Large? Fine tune it, or use variants.
But I guess I'm hearing you say now, a key point was- the attractive part about Mistral was the open model aspect.
But it's difficult to pay expenses and wages if you can't charge money.
Re: fine tuning- hard for me to believe they won't add it eventually.
But Mistral has been marketing itself as the underdog competitor whose offerings are on par with gpt-3.5-turbo and even gpt-4, while being pro-OSS.
Lies, damn lies.
Examples: LlamaIndex, Langchain, and most likely Ollama.
That really rings like moral relativism. Even 15 years ago when we were still talking about "GPGPU" and OpenCL seemed like a serious competitor to Cuda, NVidia was much less open than AMD. Sure you can argue that they are "just" profit maximising, turns out it's quite detrimental to all of us...
If what you're saying is that we shouldn't be naive when dealing with for-profit companies and expect good gestures, I agree. But some are more evil than others.
There is no moral requirement to be open source.
Being closed is not fraud, coercion, theft, dishonest, anti-competitive, …
(On the other hand, being open, in situations where closed would be more profitable, is taking the moral high ground.
Open provides better value for the customer, user, and community.)
Aside from moralizing, the economic puzzle is: How to align the economic incentives of businesses with the real long term community value of openness. While also providing greater resources to successful innovators to incentivize and compound there best efforts.
(Note that copyright has been the solution to this problem for cultural artifacts. And patents try to do this for tech, but with more problems and much less success.)
I’m pretty sure you can’t use it without connecting to the private model binary server.
It’s a very small step to a paid docker hub, cough sorry, ollama hub.
It does not just magically conjure LLM model files out of thin air.
Where do those models come from?
https://github.com/ollama/ollama/issues/2390
The registry is not open source.
You think I’m being unfair?
https://github.com/ollama/ollama/issues/914#issuecomment-195...
(Paraphrased)
>> How do I run my own registry?
> email us, let’s talk.
This is only true until the closed-source service they offer is inevitable.
For the price of awareness, we get access to high quality LLMs we can run from our laptops.
It's funny how people are happy to donate to OpenAI, that immediately close up at the first sniff of cash, but there doesn't seem to be any donations toward open and public development, which is the only way to guarantee availability of the results, sadly.
I should add: Mistral, Meta, etc don't release open source models, all we get is the 'binary'.
The problem was, there was no formal legal restrictions put in place at the start that stopped them from hatching a private subsidiary or not remaining open. Just that the initial organization was non-profit and for AI safety.
Which is the only way that could have been stopped.
A failure of initial oversight. A lack of “alignment” one might say.
That is surely true.
> Which is the only way that could have been stopped.
The problem is, no one expects a CEO to do these things, and when the gusher of money erupts there's nothing that can be done, as we saw.
You cover one base, they sneak to another. Legal strictures are unlikely to contain them. Money is all conquering.
Is that what they concluded?
Or did they find they could either have an open source company or $80 Billion and make the decision most of us would make in that situation?
Edit: not that I mind all that much what they're actually doing, it's just the misuse of the word that bristles.
But regardless, part of the answer might be that it might be more attractive for "capable people" to get serious money working for a for-profit AI company at the moment.
[0] https://www.deeplearning.ai/the-batch/japan-ai-data-laws-exp...