Earlier quoted context omitted.
"Specifically, the DSPy compiler will internally trace your program and then craft high-quality prompts for large LMs" I'm having trouble understanding the value provided here. A prompt is a string. Why abstract that string away from me like this? My instinct is that this will make it harder, not easier, for me to understand what's going on and make necessary changes.
"A neural network layer is just a matrix. Why abstract that matrix and learn it?" Well, because it's not your job to figure out how to hardcode delicate string or floats that work well for a given architecture & backend. We want developers to iterate quickly on system designs: How should we break down the task? Where do we call LMs? What should they do? --- If you can guess the right prompts right away for each LLM,…
If prompts can be learned, then eventually it will be better to learn them than to manually tune them. However, these ideas need not be mutually exclusive. When we reject the tyranny of the “or” and we can have a prompt prior we manually tune and then update it with a learning process, right?
P.S. whoever wrote the title, I think it’s pretty silly to write “The Framework…” for anything because this presumes you have the only member of some category, which is never true!