I've been having a lot of conversations recently with people about LLMs and how a prototypal inheritance-like approach to working with them seems to be surprisingly effective. Especially for writing code.
Also, this quote jumped out at me: "Insights from the dynamic world can have application in the static."
Ahh yeah - so I've found prototypal inheritance (or what Hofstadter calls The Prototype Principle) is a useful way to think about what's going on with in-context learning and few shot prompting and ways to take it further.
If you provide a "prototype" to a model, you can operate on that prototype and create new instances or variations of it. This is useful for working with code by defining an abstraction or a class, and then having the LLM work with and modify it, generating new code that fits or inherits conceptually from that original prototype.
I've been having a lot of conversations recently with people about LLMs and how a prototypal inheritance-like approach to working with them seems to be surprisingly effective. Especially for writing code.
Also, this quote jumped out at me: "Insights from the dynamic world can have application in the static."