I am rooting for Mistral with their different approach: not really competing on the largest and advanced models, instead doing custom engineering for customers and generally serving the needs of EU customers.
Mistral has been releasing some cool stuff. Definitively behind on frontier models but they are working a different angle. Was just talking at work about how hard model training is for a small company so we’d probably never do it. But with tools like this, and the new unsloth release, training feels more in reach.
This is definitely the smart path for making $$ in AI. I noticed MongoDB is also going into this market with https://www.voyageai.com/ targeting business RAG applications and offering consulting for company-specific models.
Huh. I initially thought this is just another finetuning end point. But apparently they are partnering up with customers on the pretraining side as well. But RL as well? Jeez RL env are really hard to get right. Best wishes I guess.
How many proprietary use cases truly need pre-training or even fine-tuning as opposed to RAG approach? And at what point does it make sense to pre-train/fine tune? Curious.
And yet your blog says you think NFTs are alive. Curious.
But seriously, RAG/retrieval is thriving. It'll be part of the mix alongside long context, reranking, and tool-based context assembly for the forseeable future.
I am rooting for Mistral with their different approach: not really competing on the largest and advanced models, instead doing custom engineering for customers and generally serving the needs of EU customers.
their ocr model is goated
Go Mistral !
Mistral has been releasing some cool stuff. Definitively behind on frontier models but they are working a different angle. Was just talking at work about how hard model training is for a small company so we’d probably never do it. But with tools like this, and the new unsloth release, training feels more in reach.
This is definitely the smart path for making $$ in AI. I noticed MongoDB is also going into this market with https://www.voyageai.com/ targeting business RAG applications and offering consulting for company-specific models.
Huh. I initially thought this is just another finetuning end point. But apparently they are partnering up with customers on the pretraining side as well. But RL as well? Jeez RL env are really hard to get right. Best wishes I guess.
How many proprietary use cases truly need pre-training or even fine-tuning as opposed to RAG approach? And at what point does it make sense to pre-train/fine tune? Curious.
RAG is dead
And yet your blog says you think NFTs are alive. Curious.
But seriously, RAG/retrieval is thriving. It'll be part of the mix alongside long context, reranking, and tool-based context assembly for the forseeable future.
Wait, what does NFTs have to do with RAG?
Nothing, I think they're just pointing out a seeming lack of awareness of what really is or isn't dead.
I, for one, find NFT-shilling to be a strong signal that I should downgrade my trust in everything else a person says.
Using tools and skills to retrieve data or files is anything but dead.
Is it??
In what, X's hype circles? Embeddings are used in production constantly.
How does this compare to fine tuning?
The fine tuning endpoint is deprecated according to the API docs. Is this the replacement?
https://docs.mistral.ai/api/endpoint/deprecated/fine-tuning
Interesting to see. I thought they were promoting fine tuning
They mention pretraining too, which surprises me. I thought that was prohibitively expensive?
It's feasible for small models but, I thought small models were not reliable for factual information?
Id training or FT > context? Anyone have experience.
Is it possible to retrain daily or hourly as info changes?