Yeah this always get's completely glossed over in these conversations.
People always say: "Things ended up working out in the end"
Things only worked out in the sense that society carried on without all the people who lost their jobs.
The U.S. has recent examples of large scale job destruction.
Michigan: From 2000-2009. Massive job destruction. 330,000 auto workers in 2000. Down to 109,000 in 2009. Estimates are that 1/3-1/2 of all those affected never achieved equal/similar employment. That is, somewhere around ~70k-120k workers never earned as much as they previously did. Since this was msotly contained within one city (Detroit), it's pretty easy for the country to ignore it and go on with their lives.
(Detroit was in decline since the 50's really. 2000-2009 is just a particularly bad snapshot.)
Coal mining towns have experienced the same phenomenon but more gradually. The poverty left behind by the destruction of those jobs has never been addressed.
With AI, we are heading into a situation where potentially a much larger amount of people will be affected. So maybe that changes the calculus on the government stepping in and fixing the problem. But I wouldn't count on it.
> Since this was mostly contained within one city (Detroit)
It's concentrated in Detroit but also distributed throughout the state, as you can observe in the census.gov slides.
The devastation is regional. It's been a wild experience, watching it all fall apart over the last 40+ years. The decay is immense and impossible to convey to someone from a rich state. Someone from the Eastern Bloc might get it, but I've never been able to communicate it to a Californian. Hop in a car and drive from town to town. Once-prosperous communities are boarded up and gradually reclaimed by nature. Department stores are converted into soup kitchens or marijuana dispensaries.
"Things will work themselves out" is not a law of nature, unless we broaden our definition of "things working out" to include outcomes like "everyone young enough flees, everyone else clutches their savings until they eventually die impoverished."
But with AI, even outcomes like that might be overly optimistic. Where will young people flee to? Where can they go, what trade can they learn, to be safe enough to eventually die in comfort?
When I look at Michigan I see both the past and the future, and I am planning accordingly.
I've always attributed it to people being very good at convincing themselves they aren't one of the bad guys. A big paycheck makes it even easier to ignore to what you are a part of.
Where livelihood is concerned, rational individuals with strong morals can do irrational, and immoral things (e.g., work at the Palantir's of the world).
TLDR: incentives don't just shape perception, they form it
> the data centers just move to another country or eventually to space
The same line of reasoning that purports billionaires will flee if their taxes go up.
Spoiler alert: they don't.
Also, data centers in space is not a serious idea. It's been beaten to death that this isn't economical. People like Musk are proposing that as a possibility for the sole reason of keeping regulation away. "Well if you regulate us we will just move into space". They won't because they can't because physics.
When web search first arrived, the same thing happened. That is, some people didn't like using the tool because it wasn't finding what they wanted. This is still true for a lot of folks today, actually.
It's less "git gud; prompt better", and more, "be able to explain (well) what you want as the output". If someone messages the IT guy and says "hey my computer is broken" - what sort of helpful information can the IT guy offer beyond "turn it on and off again"?
So how do you rectify your anecdotal experience against those made by public figures in the industry who we can all agree are at least pretty good engineers? I think that's important because if we want to stay ~anonymous, neither you nor I can verify the reputation of one another (and therefore, one another's relative master of the "Craft").
Here are some well known names who are now saying they regularly use LLM's for development. For many of these folks, that wasn't true 1-2 years ago:
My point being - some random guy on the internet says LLM's have never been useful for them and they only output garbage vs. some of the best engineers in the field using the same tools, and saying the exact opposite of what you are.
>Here are some well known names who are now saying they regularly use LLM's for development. For many of these folks, that wasn't true 1-2 years ago:
This is a huge overstatement that isn't supported by your own links.
- Donald Knuth: the link is him acknowledging someone else solved one of his open problems with Claude. Quote: "It seems that I’ll have to revise my opinions about “generative AI” one of these days."
- Linus Torvalds: used it to write a tool in Python because "I know more about analog filters—and that’s not saying much—than I do about python" and he doesn't care to learn. He's using it as a copy-paste replacement, not to write the kernel.
- John Carmack: he's literally just opining on what he thinks will happen in the future.
You are overstating those sources. That alone makes me doubt that you're engaging in this discussion in good faith.
I read them all, and in none of them do any of the three say that they "regularly use LLMs for development".
Carmack is speculating about how the technology will develop. And Carmack has a vested interest in AI, so I would not put any value on this as an "engineers opinion".
Torvalds has vibe coded one visualizer for a hobby project. That's within what I might use to test out LLM output: simple, inconsequential, contained. There's no indication in that article that Linus is using LLMs for any serious development work.
Knuth is reporting about somebody else using LLMs for mathematical proofs. The domain of mathematical proofs is much more suitable for LLM work, because the LLM can be guided by checking the correctness of proofs.
And Knuth himself only used the partial proof sent in by someone else as inspiration for a handcrafted proof.
I don't mind arguing this case with you, but please don't fabricate facts. That's dishonest
I think Amazon is a better example. It's a thing that some companies prefer not to hire engineers from Amazon because of the culture they bring. Whether you agree with it or not, Amazon has a reputation for a toxic culture and that sort of thing can ruin a smaller or medium size company if it seeps in.
It is funny how you can break diet/nutrition into generations like this.
I think the trends are a reflection of poor education. Fiber/protein/whatever being important components of a diet isn't new information. But the information is new to folks that never had nutrition explained to them.
I don't love talking politics on this site. Hackernews has done a pretty decent job of staying non-political and I think that's been a positive thing.
AI is re-shaping American society in a lot of ways. And this is happening at a time where the U.S. is more politically divided than it's ever been. People who use LLMs regularly (most SWEs at this point) can understand the danger signs. The bad outcomes are not inevitable. But the conversations around this cannot only be held in internet forums and blogposts.
Hackernews is an echo chamber of early adopters of tech. The discussions had here don't percolate to the general population.
I believe many of us have a duty to make this feel real to the less technical people in our lives. Too many folks have an information filter that is one of Fox News/CNN/MSNBC. Fox is the worst on misinformation. The others are also bad. Their viewers will not hear, in any clear way, how the Trump admin is trying to bully AI companies into doing what it wants. This will be a headline or an article. A footnote not given the attention it deserves.
Plainly: there is an attempt to turn AI into a political weapon aimed at the general population. Misinformation and surveillance are already out of control. If you can, imagine that getting worse.
This feels like one of those hinge moments. If you can, have real-life conversations with people around you. Explain what's at stake and why it matters now, not later.
I see that your prompt includes 'Do not use any tools. If you do, write "I USED A TOOL"'
This is not a valid experiment, because GPT models always have access to certain tools and will use them even if you tell them not to. They will fib the chain of thought after the fact to make it look like they didn't use a tool.
This isn't an experiment a consumer of the models can actually run. If you have a chance to read the article I linked, it is difficult even for the model maintainers (openai, anthropic, etc.) to look into the model and see what it actually used in it's reasoning process. The models will purposefully hide information about how they reasoned. And they will ignore instructions without telling you.
The problem really isn't that LLM's can't get math/arithmetic right sometimes. They certainly can. The problem is that there's a very high probability that they will get the math wrong. Python or similar tools was the answer to the inconsistency.
"I should explain that both the “python” and “python_user_visible” tools execute Python code and are stateful. The “python” tool is for internal calculations and won’t show outputs to the user, while “python_user_visible” is meant for code that users can see, like file generation and plots."
But really the most important thing, is that we as end-users cannot with any certainty know if the model used python, or didn't. That's what the alignment faking article describes.
> To avoid timeouts, try using background mode. As our most advanced reasoning model, GPT-5 pro defaults to (and only supports) reasoning.effort: high. GPT-5 pro does not support code interpreter.
You are wrong from the link you shared. It was about ChatGPT not the api.
The documentation makes it unambiguously clear that gpt 5 pro does not support code interpreter. Unless you think they secretly run it which is a conspiracy, is it enough to falsify?
> Unless you think they secretly run it which is a conspiracy
tbh this doesn't sound like a conspiracy to me at all. There's no reason why they couldn't have an internal subsystem in their product which detects math problems and hands off the token generation to an intermediate, more optimized Rust program or something, which does math on the cheap instead of burning massive amounts of GPU resources. This would just be a basic cost optimization that would make their models both more effective and cheaper. And there's no reason why they would need to document this in their API docs, because they don't document any other internal details of the model.
I'm not saying they actually do this, but I think it's totally reasonable to think that they would, and it would not surprise me at all if they did.
Let's not get hung up on the "conspiracy" thing though - the whole point is that these models are closed source and therefore we don't know what we are actually testing when we run these "experiments". It could be a pure LLM or it could be a hybrid LLM + classical reasoning system. We don't know.
“Code interpreter” is a product feature the customer can use that isn’t being discussed.
They can obviously support it internally, and the feature exists for ChatGPT, but they’re choosing not to expose that combo in the API yet because of product rollout constraints.
Alright let's say I'm wrong about the details/nuances. That's still really not the point.
The point is this:
> we as end-users cannot with any certainty know if the model used python, or didn't
These tools can and do operate in ways opposite to their specific instructions all the time. I've had models make edits to files when I wasn't in agent mode (just chat mode). Chat mode is supposedly a sandboxed environment. So how does that happen? And I am sure we've all seen models plainly disregard an instruction for one reason or another.
The models, like any other software tool, have undocumented features.
You as an end-user cannot falsify the use of a python tool regardless of what the API docs say.
I know what falsifiable means--you're misusing it and I simply adopted your misuse. A claim is falsifiable or not ... it can't be made falsifiable. The way you're using it is "Can we come up with a test to show that it's false"--no, we can't, because it's not false.
Again, there's nothing that one can do to prove that something that isn't false is false. Sheesh. I won't respond to you again as there's no need to simply repeat it.
Please don't cross into posting like this, no matter how wrong someone else is or you feel they are. It's not what this site is for, and destroys what it is for.
Please don't cross into posting like this, no matter how wrong someone else is or you feel they are. It's not what this site is for, and destroys what it is for.
Well, your first Google result is a blog post that makes my point.
> For example, baby boomers are the generation with the most dramatic increase in harmful alcohol abuse. In contrast, Gen Z prefers the sober lifestyle as they are known to consume alcohol much less than any of their older counterparts, including millennials.
People always say: "Things ended up working out in the end"
Things only worked out in the sense that society carried on without all the people who lost their jobs.
The U.S. has recent examples of large scale job destruction.
Michigan: From 2000-2009. Massive job destruction. 330,000 auto workers in 2000. Down to 109,000 in 2009. Estimates are that 1/3-1/2 of all those affected never achieved equal/similar employment. That is, somewhere around ~70k-120k workers never earned as much as they previously did. Since this was msotly contained within one city (Detroit), it's pretty easy for the country to ignore it and go on with their lives.
(Detroit was in decline since the 50's really. 2000-2009 is just a particularly bad snapshot.)
Coal mining towns have experienced the same phenomenon but more gradually. The poverty left behind by the destruction of those jobs has never been addressed.
With AI, we are heading into a situation where potentially a much larger amount of people will be affected. So maybe that changes the calculus on the government stepping in and fixing the problem. But I wouldn't count on it.
Sources for Michigan numbers:
https://lehd.ces.census.gov/doc/workshop/2010/LEDautopres031...
https://research.upjohn.org/cgi/viewcontent.cgi?article=1205...
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