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Cake day: June 12th, 2023

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  • CEOs have very little to do with the failure or success of most large companies. If they work very hard they can pull a company out of a death spiral, or start it down one, but failure or success takes years if not decades of steady improvement or decline. All the examples of “failures” given in the article are terrible and don’t demonstrate at all that those CEOs were bad.

    One of the worst problems with businesses in the US currently is this culture of fetishizing CEOs. They’re paid far too much for what they actually bring to companies, and people grossly exaggerate how much of an impact CEOs have on companies. If you want proof of his just take a look at literally any company Elon Musk is a CEO of. The fact that none of those companies (particularly Twitter) have filed for bankruptcy yet shows exactly how little a truly terrible CEO actually impacts things.



  • LLMs are basically just really fancy search engines. The reason the initial code is garbage is that it’s cut and pasted together from random crap the LLM found on the net under various keywords. It gets more performant when you ask because then the LLM is running a different search. The first search was “assemble some pieces of code to accomplish X”, while the second search was “given this sample of code find parts of it that could be optimized”, two completely different queries.

    As noted in another comment the true fatal flaw of LLMs is that they don’t really have a threshold for just saying " I don’t know that" as they are inherently probabilistic in nature. When asked something they can’t find an answer for they assemble a lexically probable response from similar search results even in cases where it’s wildly wrong. The more uncommon and niche your search is the more likely this is to happen. In other words they work well for finding very common information, and increasingly worse the less common that information is.