51–60 of 326 posts
Earlier quoted context omitted.
This last sentence is the most important. You can describe your dB schema in words and get laravel migration, models, controllers and if you wanted policies, form requests etc all near perfect. You can get a V1 in 10-20 minutes then go about handling all the actual logic
So rails scaffold from 20 years ago but with a chance of hallucinations?
GitHub touts a 55% improvement in coding speed based on a study conducted in-house that tested the participants’ ability to paste a pre-written prompt and then check the output: https://github.blog/2022-09-07-research-quantifying-github-c... The effectiveness of a Copilot-like tool trialed at FB showed that 8% of code contributed by participants was sourced from suggestions, but the latter study made no promise about…
My personal feeling is that utilising LLM assistance often isn't faster, but it can take less "stamina", tiring me less.
Earlier quoted context omitted.
This last sentence is the most important. You can describe your dB schema in words and get laravel migration, models, controllers and if you wanted policies, form requests etc all near perfect. You can get a V1 in 10-20 minutes then go about handling all the actual logic
Yeah the copilot doesn’t need to be integrated into every keystroke, just able to analyze the context and kickstart the code. Getting up to speed with new libraries is so much easier with AI instead of the bad old days of trial-and-error-and-marked-as-duplicate
Earlier quoted context omitted.
I don’t think you’re a dimwit but I read your post[1] with an example and I am curious to whether you feel you’re losing something by telling the LLM it’s wrong and to try again, rather than going through the exploratory/iterative learning process yourself. For example, would you have known to ask about GeoJSON if you had not come across and learned about it pre-LLM? More succinctly: do you feel you’re learning more…
Absolutely I could have learned more from that particular project if I'd spent more time with it rather than getting the LLM to do the work... but that's why I like it as an example: since it was effectively a distraction (a "side quest") the alternative wasn't learning more, it was not doing it at all (and learning nothing). I'm able to get really great results out of LLMs because I have 20+ years of experience help…
It's the same for me. Lots of experience knowing what to ask for. It does a better job in summarizing knowledge and getting me a relatively coherent explanation. Much faster than using Google Search to find and connect the dots from dozens of pages.
I just don't see much benefit in its reasoning and code assistance features besides basic stuff.
Earlier quoted context omitted.
Yeah the copilot doesn’t need to be integrated into every keystroke, just able to analyze the context and kickstart the code. Getting up to speed with new libraries is so much easier with AI instead of the bad old days of trial-and-error-and-marked-as-duplicate
Can Copilot analyze my whole codebase these days or just the file I've opened? Honest question as I've stopped to use it a long time ago.
Local maxima go BRRRRRRR AI will get there eventually, but this current paradigm seems increasingly only useful for spam and shitty clip art. Even so, everyone is throwing absurd amounts of investment capital at it in the hopes that something useful will happen. It's a pretty clear depiction of the investor class being so detached from the technical reality of what they're investing in that they just sit around light…
I think the nomenclature of calling generative AI an "AI" is just hype and that leads to disappointment. After all, it's much more exciting for investors than calling it the world's most expensive textual/audio/visual autocomplete. But that's really what this generatoon currently is. And it can feel like magic, because we're pattern-seeking and pattern-matching creatures, so something that seems to intuit the pattern…
i think this is a super important for anyone playing in the LLM space to calculate.
currently “AI” providers are selling electricity at a loss to demonstrate product “value”, so even while asking questions is “free” today, there’s actually a finite resource under the hood that needs to have the bill paid in the end.
an estimate, but from historic trends, free bills come due in around 7 years
Does the author mean that Copilot filled in the other `switch` cases? (Because that looks like "Here, let me plagiarize that for you. We'll call it 'AI' and 'boilerplate'.")
Local maxima go BRRRRRRR AI will get there eventually, but this current paradigm seems increasingly only useful for spam and shitty clip art. Even so, everyone is throwing absurd amounts of investment capital at it in the hopes that something useful will happen. It's a pretty clear depiction of the investor class being so detached from the technical reality of what they're investing in that they just sit around light…
I've been finding this stuff genuinely useful for two years now, across Copilot and ChatGPT and Claude 3 Opus and similar tools. Either I'm a dimwit, easily conned by hype and shiny tools to the point that I can imagine benefits for two years that simply aren't there... or there's something to them.
Earlier quoted context omitted.
My personal feeling is that utilising LLM assistance often isn't faster, but it can take less "stamina", tiring me less.
Especially when renaming variables that are “immune” to normal refactoring. Copilot handles that pretty well and I don’t have to spend all that focus on such a menial task.
Especially those that are a bit tedious and almost mechanical, but not quite mechanical enough to do with a simple search-and-replace.