@jonathanhogg @kirtai @lispi314 and as someone who's spent a tonne of time investing in a certain stack to make things easier for other people to solve the same problem... things can wind up esoteric and difficult to onboard with (like imagine APL). It would unironically be quicker for them to use boilerplate even if long term that may not be true.
gnuxie@social.applied-langua.ge
@gnuxie@social.applied-langua.ge
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My experience with generative-AI has been that, at its very best, it is subtly wrong in ways that only an expert in the relevant subject would recognise. -
My experience with generative-AI has been that, at its very best, it is subtly wrong in ways that only an expert in the relevant subject would recognise.@lispi314 @jonathanhogg @kirtai you have to buy into an ideology of doing things this way. And if you're investing a lot of time in e.g. libraries for a given programming language, we already kind of know that our programming languages kinda suck and better be made irrelevant, so it also feels inefficient even when you do buy into it. -
My experience with generative-AI has been that, at its very best, it is subtly wrong in ways that only an expert in the relevant subject would recognise.@lispi314 @jonathanhogg @kirtai I mean we didn't get here unintentionally. It's expensive and self sacrificial to invest a lot of time in infrastructure like programming languages and libraries (wherever you land in the stack) and make it very simple to solve the problems you are solving (and others to solve them too). It's also really hard, because not only is the problem you are solving an engineering problem but now also building the infrastructure to solve the problem. And the limiting factor is exploration not sitting down and hypothesising, researching, and cooking up some crap. Which yes is also part of the process too.