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In my day to day I write code libraries. Some of that code is boring, but some is making something very simple out of something very complicated.

Since I do this commercially, not for science, and since I don't agree with software patents (on principle), I don't "describe" the method anywhere.

Now it's possible that in that code is some novel thing. Perhaps am insight, perhaps an algorithm or technique. (I don't really think there is, such is my modesty, but its possible.)

Obviously from a "science" point of view, my work is meaningless. And perhaps that speaks to the point of academic science versus the "real world". Their goal is to "write stuff down" - not "do stuff" as much as "record stuff".

In the context of the above quote, I believe we might be doing scientific things (even novel things) but if we're not actively sharing that knowledge it's not "science".

Now of course lots of us -do- document things in blogs etc. But this informal writing on the internet is adding to a haystack, in which there might be gems, but how can they ever be found?



> Now of course lots of us -do- document things in blogs etc. But this informal writing on the internet is adding to a haystack, in which there might be gems, but how can they ever be found?

Give Copilot and the others some time to chew through GitHub, I guess. Perhaps one day, an LLM will write the successor to Chrome.


I suspect we may have hit peak LLM. Or if not yet, then just about. The AI that is capable of writing Chrome will be something other than an LLM.


There's no peak. Just an eternal slowing down clibing that still tends towards AGI, but probably not before the heat-death of the Universe.


While that may well apply to the overall AI program as such, I don't suspect it is descriptive of LLM.

Throwing more parameters at LLMs is no longer yielding appreciable improvements, and once you have thrown all the data at them you can find, that dimension is done also.




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