"The 10M context ability wipes out most RAG stack complexity immediately."
I'm skeptical, my past experience is just becaues the context has room to stuff whatever you want in it, the more you stuff in the context the less accurate your results are. There seems to be this balance of providing enough that you'll get high quality answers, but not too much that the model is overwhelmed.
I think a large part of developing better models is not just a better architectures that support larger and larger context sizes, but also capable models that can properly leverage that context. That's the test for me.
I'm skeptical, my past experience is just becaues the context has room to stuff whatever you want in it, the more you stuff in the context the less accurate your results are. There seems to be this balance of providing enough that you'll get high quality answers, but not too much that the model is overwhelmed.
I think a large part of developing better models is not just a better architectures that support larger and larger context sizes, but also capable models that can properly leverage that context. That's the test for me.