One can dream, but I doubt it. As for all the reasons I don't have much faith, I'd defer to the other comments.
I will say though, optimizing memory usage is easier than ever. Doing a scan of your codebase with an LLM for _large_ memory gains can probably shave a decent chunk off of any application with ease. You don't have to go down the rabbit hole, but taking the top 3 large things it catches would probably result in notable gains for minimal time usage.
Hell, I've hunted down code that was causing an OOM from a coworker that ran a regex that would have to search the entire string of a base64 payload that was often around 24MB, when it very easily could have been a basic string operation on the first 50 characters or so. I caught it myself, but went back after with an LLM about 8 months ago and it also spotted it with a vague point in the direction of where it could be.
There are probably a lot of small slip ups across a codebase that are simple fixes that add up over time, but we never catch because we're not actively profiling.
I will say though, optimizing memory usage is easier than ever. Doing a scan of your codebase with an LLM for _large_ memory gains can probably shave a decent chunk off of any application with ease. You don't have to go down the rabbit hole, but taking the top 3 large things it catches would probably result in notable gains for minimal time usage.
Hell, I've hunted down code that was causing an OOM from a coworker that ran a regex that would have to search the entire string of a base64 payload that was often around 24MB, when it very easily could have been a basic string operation on the first 50 characters or so. I caught it myself, but went back after with an LLM about 8 months ago and it also spotted it with a vague point in the direction of where it could be.
There are probably a lot of small slip ups across a codebase that are simple fixes that add up over time, but we never catch because we're not actively profiling.