141–150 of 662 posts
Brutal that software engineering went from one of the least automatable jobs to a job that is universally agreed to be "most exposed to automation". Was good while it lasted though.
I'm sure those who lost a job to software at some point are feeling a great deal of sympathy for developers who are now losing out to automation.
Brutal that software engineering went from one of the least automatable jobs to a job that is universally agreed to be "most exposed to automation". Was good while it lasted though.
Too bad engineers were “too important” to unionize because their/our labor is “too special .” I think you could find 10,000 quotes from HN alone why SDEs were immune to labor market struggles that would need a union Oh well, good luck everyone.
Brutal that software engineering went from one of the least automatable jobs to a job that is universally agreed to be "most exposed to automation". Was good while it lasted though.
If it gets to the point where I can no longer find a tech job I am just going to buy a trailer, live somewhere cheap, and just make money doing odd jobs while spending most of my time programming what I want. I don't want to participate in a society where all I have for job options is a McJob or some Amazon warehouse.
Unrelated to the discussion, but I love these kinds of backup plans. I've found that most guys I talk to have one. Just a few days ago a guy was telling me that, if his beloved wife ever divorces him, then he'd move to a tropical island and become a coconut seller.
(My personal plan: find a small town in the Sonoran Desert that has a good library, dig a hole under a nice big Saguaro cactus, then live out my days reading library books in my cool and shady cave.)
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I think you are selling yourself short if you believe you can be replaced by a next token predictor :)
I think humans who think they can't be replaced by a next token predictor think too highly of themselves. LLMs show it plain and clear: there's no magic in human intelligence. Abstract thinking is nothing but fancy computation. It can be implemented in math and executed on a GPU.
Now you get can't around that this might not be the case.
You're like that beetle going extinct mating with beer bottles.
https://www.npr.org/sections/krulwich/2013/06/19/193493225/t...
Every day when I am out in the city, I am amazed by how many jobs we have NOT managed to replace with AI yet. For example, cashiers. There are still many people spending their lives dragging items over a scanner, reading a number from a screen, holding out their hand for the customer to put money in, and then sorting the coins into boxes. How hard can it be to automate that?
Brutal that software engineering went from one of the least automatable jobs to a job that is universally agreed to be "most exposed to automation". Was good while it lasted though.
If it gets to the point where I can no longer find a tech job I am just going to buy a trailer, live somewhere cheap, and just make money doing odd jobs while spending most of my time programming what I want. I don't want to participate in a society where all I have for job options is a McJob or some Amazon warehouse.
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By all accounts, yes. "Model collapse" is a popular idea among the people who know nothing about AI, but it doesn't seem to be happening in real world. Dataset quality estimation shows no data quality drop over time, despite the estimates of "AI contamination" trickling up over time. Some data quality estimates show weak inverse effects (dataset quality is rising over time a little?), which is a mindfuck. The perform…
Given the number of academic papers about it, model collapse is a popular idea among the people who know a lot about AI as well. Model collapse is something demonstrated when models are recursively trained largely or entirely on their own output. Given most training data is still generated or edited by humans or synthetic, I'm not entirely certain why one would expect to see evidence of model collapse happening right…
Earlier quoted context omitted.
The jpeg compression argument is still valid. It's lossy compression at the core.
In 2025 you can add quality to jpegs. Your phone does it and you don't even notice. So the rhetorical metaphor employed holds up, in that AI is rapidly changing the fundamentals of how technology functions beyond our capacity to anticipate or keep up with it.
Define "quality", you can make an image subjectively more visually pleasing but you can't recover data that wasn't there in the first place
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I'm not sure it's that our job is the most automatable, but that the interface is the easiest to adapt to our workflow. I have a feeling language models will be good at virtually every "sit at a desk" job in a virtually identical capacity, it's just the act of plugging an AI into these roles is non-obvious. Like every business was impacted by the Internet equally, the early applications were just an artifact of what…
> I'm not sure it's that our job is the most automatable I don't know. It seems pretty friendly to automation to me. When was the last time you wrote assembly? When was the last time you had map memory? Think about blitting memory to a screen buffer to draw a square on a screen? Schedule processes and threads? These are things that I routinely did as a junior engineer writing software a long time ago. Most people at…
The labor cost of implementing a given feature is going to dramatically drop. Jevons Paradox paradox will hopefully still mean that the labor pool will just be used to create '10x' the output (or whatever the number actually is).
If the cost of a line of code / feature / app becomes basically '0', will we still hit a limit in terms of how much software can be consumed? Or do consumers have an infinite hunger for new software? It feels like the answer has to be 'it's finite'. We have a limited attention span of (say) 8hrs/person * 8 billion.