This methodological growth could make LLMs more reliable, consistent, and aligned with specific use cases.
The skepticism surrounding this vision mirrors early doubts about the early internet fairly concisely.
Initially, the internet was seen as fragmented collection of isolated systems without a clear structure or purpose. It really was. You would gopher somewhere and get a file, and eventually we had apps like like pine for email, but as cool as it was it has limited utility.
People doubted it could ever become the seamless, interconnected web we know today.
Yet, through protocols, shared standards, and robust frameworks, the internet evolved into a powerful network capable of handling diverse applications, data flows, and user needs.
In the same way, LLM orchestration will mature by standardizing interfaces, improving interoperability, and fostering cooperation among varied AI models and support systems.
Just as the internet needed HTTP, TCP/IP, and other protocols to unify disparate networks, orchestrated AI systems will require foundational frameworks and “rules of the road” that bring cohesion to diverse technologies.
We are at the veeeeery infancy of this era and have a LONG way to go here. Some of the progress looks clear and a linear progression, but a lot, like the Internet, will just take a while to mature and we shouldn’t forget what we learned the last time we faced a sea change technological revolution.