I'm less concerned with people's perception and strictly concerned with value. If we were to define value as the number of things that can be automated or sever

I'm less concerned with people's perception and strictly concerned with value. If we were to define value as the number of things that can be automated or severely improved by the technology or its future versions, there is a misalignment between value and perceived value. The value is lower than perceived because there is an assumption that what's preventing higher value delivery from the investment is for the models to get better at generating responses from prompts. But there are two issues with this position. 1. LLMs still require plenty of assistance where they are writing production ready code and making function-calls, especially if the original API wasn't designed with LLMs in mind. Unless there is a leap in architecture that's going to make all the tools we have, including non-API ones easily accessible by the models to interact with, the amount of glue code required to make it all work increases the potential for features that users can use, but not necessarily deliver higher value to developers in that a lay person still probably can't develop software with an LLM copilot in toe. So yes, no one is going to be impressed even if we see models improve further on benchmarking. 2. Long-Horizon goals. Long-term research or even project management requires interdisciplinary understanding of how all the goals around success relate to each other and most importantly how to assess if an outcome is leading to a goal accomplishment or not. There isn't an architectural foundation for the models to be grounded in a reality that presupposes these abilities. What I fail to see, is how improving next token prediction will materially move the needle on these other aspects of intelligence that aren't necessarily related to generating an output or a series of outputs orchestrated over an evolving set of requirements. Honestly lI think that the LLM portion of the human brain has likely be surpassed by existing models