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Don't sleep on Mistral. Highly underrated as a general service LLM. Cheaper, too. Their emphasis on bespoke modelling over generalized megaliths will pay off. There are all kinds of specialized datasets and restricted access stores that can benefit from their approach. Especially in highly regulated EU. Not everyone is obsessed with code generation. There is a whole world out there.
Don't sleep on Mistral. Highly underrated as a general service LLM. Cheaper, too. Their emphasis on bespoke modelling over generalized megaliths will pay off. There are all kinds of specialized datasets and restricted access stores that can benefit from their approach. Especially in highly regulated EU. Not everyone is obsessed with code generation. There is a whole world out there.
> Pre-training allows organizations to build domain-aware models by learning from large internal datasets. > Post-training methods allow teams to refine model behavior for specific tasks and environments. How do you suppose this works? They say "pretraining" but I'm certain that the amount of clean data available in proper dataset format is not nearly enough to make a "foundation model". Do you suppose what they are…
Pre-training: refining the weights in an existing model using more training data.
Post-training: Adding some training data to the prompt (RAG, basically).
Don't sleep on Mistral. Highly underrated as a general service LLM. Cheaper, too. Their emphasis on bespoke modelling over generalized megaliths will pay off. There are all kinds of specialized datasets and restricted access stores that can benefit from their approach. Especially in highly regulated EU. Not everyone is obsessed with code generation. There is a whole world out there.
Is this the best Grok alternative?
Don't sleep on Mistral. Highly underrated as a general service LLM. Cheaper, too. Their emphasis on bespoke modelling over generalized megaliths will pay off. There are all kinds of specialized datasets and restricted access stores that can benefit from their approach. Especially in highly regulated EU. Not everyone is obsessed with code generation. There is a whole world out there.
Yes, since it's not American, it will be the de-facto choice for most big European companies.
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
Don't sleep on Mistral. Highly underrated as a general service LLM. Cheaper, too. Their emphasis on bespoke modelling over generalized megaliths will pay off. There are all kinds of specialized datasets and restricted access stores that can benefit from their approach. Especially in highly regulated EU. Not everyone is obsessed with code generation. There is a whole world out there.
The problem they have is that this is not a moat - their approach is easily reproducible.
If they can pull ahead in having the most number of pre-trained models (one for this ERP, one for that CRM, etc) and then being able to close sales to companies using these products and sell them on post-trained (give us your specific ERP customisations and we'll give you access to a model that is tailored to your business), then THAT is a moat.
But they need to do this without fanfare. Just close sales, and keep closing, basically. After all, even if other AI providers copy the process, the moat would already have been established for Mistral.
Earlier quoted context omitted.
Yes, since it's not American, it will be the de-facto choice for most big European companies.
Why would that be? Most big EU companies use ms teams or google workspace, for example.
Don't sleep on Mistral. Highly underrated as a general service LLM. Cheaper, too. Their emphasis on bespoke modelling over generalized megaliths will pay off. There are all kinds of specialized datasets and restricted access stores that can benefit from their approach. Especially in highly regulated EU. Not everyone is obsessed with code generation. There is a whole world out there.
> Their emphasis on bespoke modelling over generalized megaliths will pay off. Isn't the entire deal with LLMs that they are trained as megaliths? How can bespoke modelling overcome the treasure trove of knowledge that megaliths can generically bring in, even in bespoke scenarios?
Think of it as a base model (the megalith) which then has the weights adjusted towards a specific use-case (SAP, for example).
Earlier quoted context omitted.
Why would that be? Most big EU companies use ms teams or google workspace, for example.
They use those because the decision to use them was made years ago. Things have changed since then