In the world of app development, the model is just a tiny fraction of the entire stack. It's comparable to the role data science used to play. Training a model is only a small part of the end-to-end data science life cycle. There are many other aspects to consider. So, although people tend to think of the model as the application, there's actually a lot more to it.
Recently a16z released a diagram showing the “Emerging Architectures for LLM Applications.” In this episode, we expand on things covered in that diagram to a more general mental model for the new AI app stack. We cover a variety of things from model “middleware” for caching and control to app orchestration.
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Emerging Architectures for LLM Applications
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