Another strong contender for humanity's epitaph
2,069 karma · joined June 28, 2021
More generically, our species' Achilles heel is our inability to factor in the long-term cost of negative externalities when evaluating processes that yield short-term positive results.
What happens to all of these AI-native companies if the AI bubble is not able to survive in these conditions? If your current development process is built on the metabolic equivalent of 400kg of leaves per day[0], then when the allegorical asteroid hits, you're going to be outperformed by smaller, nimbler companies with much lower resource requirements. Those companies may be better suited for survival in hostile macro conditions.
In other words, I think a lot of companies believe that they're trimming their metabolic fat by replacing engineers with AI. Lower salary costs! But at the same time, they're also increasing their reliance on brittle energy infrastructure that may not survive this century. (Not to mention the brittleness of the semiconductor fabrication pipeline, RAM availability, etc)
Sounds like Macrodata Refinement.
Disassembly implies that you're still distributing binaries, which isn't the case for web-based services. Of course, these models can still likely find vulnerabilities in closed-source websites, but probably not to the same degree, especially if you're trying to minimize your dependency footprint.
All joking aside, I disagree with the author regarding the Grand Canyon. Havasupai Gardens -- the verdant oasis at the bottom of the canyon, where you can camp and recharge -- is one of my favorite places I've camped. There are areas for wading and swimming, and the sounds of the night creatures is eerily beautiful.
What makes you think your comment was worth reading?
Off-topic but just wanted to thank you for teaching me a new word. I try to always reply to HN comments that expand my vocabulary.
LLM's remind me of sprites, pixies, and the like, who are situationally helpful but require constant supervision. We're like modern magicians who learned how to summon these sorts of spirits and bind them -- imperfectly -- to our will. But their perception of truth and reality is "through the looking glass" relative to our own. They aren't lying, from their own frame of reference, even though what they say is untrue relative to ours.
> Overall our goal isn't to only collect data, it's to make the Vercel plugin amazing for building and shipping everything.
"But maybe... OLEICAT? no..."
> the state of the art today is not as good as the very best
and
> state of the art models completely surpass any individual’s productive output
are not contradictory. If the models completely surpass any individual's productive output, doesn't that mean they're better than the best humans? Or maybe I don't understand what you mean by "surpassing productive output." Are you talking about raw quantity over quality? I mean, yeah... but I could also do that with a bash script.
I don't think this is the flex you think it is... in my experience, the bottom 10% of programmers are actively harmful and should never be allowed near your codebase.
> Claude and GPT regularly write programs that are way better than what I would’ve written
What you're describing doesn't sound "way better" than what you would have written by hand, except possibly in terms of the speed that it was written.
No one is going to care about anyone’s painstaking avoidance of chlorofluorocarbons if it takes ten times as long to style your hair with imperceptibly less ozone hole damage.
This is gaslighting. We're only a few years into coding agents being a thing. Look at the history of human innovation and tell me that I'm unreasonable for suspecting that there is an iceberg worth of unmitigated externalities lurking beneath the surface that haven't yet been brought to light. In time they might. Like PFAS, ozone holes, global warming.
Is that really true? Like, if you took the time to plan it carefully, dot every i, cross every t?
The way I think of LLM's is as "median targeters" -- they reliably produce output at the centre of the bell curve from their training set. So if you're working in a language that you're unfamiliar with -- let's say I wanted to make a todo list in COBOL -- then LLM's can be a great help, because the median COBOL developer is better than I am. But for languages I'm actually versed in, the median is significantly worse than what I could produce.
So when I hear people say things like "the clanker produces better programs than me", what I hear is that you're worse than the median developer at producing programs by hand.
Having premarital sex is not everyone's definition of "promiscuous".