81–90 of 282 posts
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.
Always that’s the reason they go open source it’s the freeium model
Earlier quoted context omitted.
I would assume that the advantage (for Mistal) here is Microsoft paying them money to be the exclusive model hosting partner, so that everyone has to go to Azure to get top-tier hosted models.
It's obviously not exclusive (it's available hosted from both Mistral themselves and Azure). I guess it could possibly be exclusive within some smaller scope, but nothing in the article suggests that. Azure is described as the "first distribution partner", not an exclusive one.
For example, they have a legal agreement with Azure/GCP/AWS already and if they can say it's "just another Cloud provider service" it's stupid how much easier that makes things. Plus, you get stuff like FEDRAMP Moderate just for having your request sent to Azure/GCP/AWS instead? Enormous value.
Getting any service, but especially a startup and one that ingests arbitrary information, to be FEDRAMP certified is the bureaucratic equivalent of inhaling a candy bar.
> Au Large Does anyone have an idea what does "Au" stand for here? Translating "au" to French gives "at", but I'm not sure whether this is what it's supposed to mean. And "Au" doesn't seem to be used anywhere else in the article.
Nietsche's « Beyond Good And Evil» in french would be "Par-delà le bien et le mal" or "Au delà du bien et du mal". In this example, the "where" is beyond.
There is not a lot of advantage to releasing this on Azure where you are directly competing with GPT-4, which will beat you on most tasks.
Changelog is also updated: [1] Feb. 26, 2024 API endpoints: We renamed 3 API endpoints and added 2 model endpoints. open-mistral-7b (aka mistral-tiny-2312): renamed from mistral-tiny. The endpoint mistral-tiny will be deprecated in three months. open-mixtral-8x7B (aka mistral-small-2312): renamed from mistral-small. The endpoint mistral-small will be deprecated in three months. mistral-small-latest (aka mistral-small…
I know marketing folks prefer poetic names, but I wish we had consistent naming like v1.0, 2.0 etc, instead of renaming your product line every year like Apple and Xbox does. Confusing and opaque.
1: Trying to design and impose an ontology, echo that in naming, and then keep it coherent in perpetuity.
2: Accept that definition cannot be solved at the naming level, expect people to read the docs to dereference names, and name it whatever the hell you want.
Honestly, as long as they don't suddenly repurpose names, I have no problem with either approach. They both have their pros and cons.
PS: And jungle does have the benefit of keeping developers from making assumptions about stringN+1 in the future...
There is not a lot of advantage to releasing this on Azure where you are directly competing with GPT-4, which will beat you on most tasks.
It makes even more sense from MS perspective -- now they can offer two competing models on their own infra, becoming the defacto shop for large corporate LLM clients.
Im not sure if anyone cares about my opinion, but I think its worth mentioning that of all the models, Mixtral is IMO the best, and I do not know what Id do without it. Fantastic news, thank you.
I do not have an opportunity to explore these models in my job; hence my curiosity.
Changelog is also updated: [1] Feb. 26, 2024 API endpoints: We renamed 3 API endpoints and added 2 model endpoints. open-mistral-7b (aka mistral-tiny-2312): renamed from mistral-tiny. The endpoint mistral-tiny will be deprecated in three months. open-mixtral-8x7B (aka mistral-small-2312): renamed from mistral-small. The endpoint mistral-small will be deprecated in three months. mistral-small-latest (aka mistral-small…
Earlier quoted context omitted.
It's not a problem from a moral perspective or anything - we all know these models are very expensive to create. 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.
Is this true? I know a whole lot of people that use and fine tune Mistral / variants and they all use OpenAI too. (For other projects or for ChatGPT) 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…
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.