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Yeah but even then they won't describe it using the same sort of language that everyone else developing these things does. How many parameters? What kind of corpus was it trained on? MoE, single model, or something else? Will the weights be available?

It doesn't even use the words "LLM", "multimodal" or "transformer" which are clearly the most relevant terms here... "foundation model" isn't wrong but it's also the most abstract way to describe it.



None of those matters (except multimodal). If you are running a business, the only thing that matters is

a) How does it perform on my set of evals

b) What is the cost/latency of serving it to my consumers.

It shouldn't matter to me how many parameters, corpus it is trained on, whether it's LLM or Transformer or something else


> How does it perform on my set of evals

What kinds of eval? Personally, I have no idea what kind of data you can throw at a "foundation model" and what kind of response you will get.

The only thing it says is that there's machine learning involved... Once you get enough context to understand it's not a spin-off of a TV series.


"Foundation model" is not Amazon lingo, though, but pretty standard industry term at this point. If you're doing any sort of AI in prod, you know what it means.


> How many parameters? What kind of corpus was it trained on?

It's rare for the leading model providers to answer these questions.

As someone who applies these models daily, I agree with the dead comment from meta_x_ai. Your questions are interesting/relevant to a person developing these models, but less important to the average person utilizing these models through Bedrock.


Amazon is not a "leading model provider".




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