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At this point, I don't even know what an AGI is. The word has just been semantically saturated for me.
What I do know, based on having followed the field since before GPT-2 days, and personally fucked around since GPT-3, is that for at least a year or so, SOTA LLMs have been smarter and more useful than the average person. Perhaps one might consider even the ancient GPT 3.5 to have met this (low) bar.
They can't write? Have you seen the quality of the average /r/WritingPrompts post?
They can't code? Have you seen the average code monkey?
They can't do medicine/math/..? Have you tried?
The average human, when confronted with a problem outside their core domain of expertise, is dumb as rocks compared to an LLM.
I don't even know how I managed before LLMs were a thing. It hasn't been that long, I've spent the overwhelming majority of my life without them. If cheap and easy access to them were to magically vanish, my willingness to pay to get back access would be rather high.
Ah, it's all too easy to forget how goddamn useful it can be to have access to an alien intelligence in one's pocket. Even if it's a spiky, inhuman form of intelligence.
On the topic of them being cheap/free, it's a damn shame that AI Studio is moving to API access only. Google was very flustered by the rise of ChatGPT and the failure of Bard, it was practically begging people to give Gemini a try instead. I was pleasantly surprised and impressed since the 1.5 Pro days, and I'm annoyed that their gambit has paid off, that demand even among normies and casual /r/ChatGPT users increased to the point that even a niche website meant for powerusers got saturated.
I'm sorry but being a better writer than literal redditors on /r/WritingPrompts is not a high bar to pass.
And yet it is a bar that most humans cannot pass. We know this because redditors are humans (and, in fact, since they are selected for being literate and interested in creative writing, they must be above average human writing ability). That's the point of the grandparent; ChatGPT blew right past the Turing Test, and people didn't notice because they redefined it from "can pass for the average human at a given task" to "can pass for the top human at a given task".
There are plenty of tasks (e.g. speaking multiple languages) where ChatGPT exceeds the top human, too. Given how much cherrypicking the "AI is overhyped" people do, it really seems like we've actually redefined AGI to "can exceed the top human at EVERY task", which is kind of ridiculous. There's a reasonable argument that even lowly ChatGPT 3.0 was our first encounter with "general" AI, after all. You can have "general" intelligence and still, you know, fail at things. See: humans.
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Why do you consistently assume that people who don't share your views of LLM capabilities just haven't seen what they can do/what humans can do? For example:
Yes I have (and of course, I've used LLMs as well). That's why I say LLMs suck at code. I'm not some ignorant caricature like you seem to think, who is judging things without having proper frame of reference for them. I actually know what I'm talking about. I don't gainsay you when you say that an LLM is good at medical diagnoses, because that's not my field of expertise. But programming is, and they simply are not good at programming in my opinion. Obviously reasonable people can disagree on that evaluation, but it really irks me that you are writing like anyone who disagrees with your take is too inexperienced to give a proper evaluation.
At @self_made_human's request, I'm answering this. I strongly believe LLMs to be a powerful force-multiplier for SWEs and programmers. I'm relatively new in my latest position, and most of the devs there were pessimistic about AI until I started showing them what I was doing with it, and how to use it properly. Some notes:
LLMs will be best where you know the least. If you're working on a 100k codebase that you've been dealing with for 10+ years in a language you've known for 20+ years, then the alpha on LLMs might be genuinely small. But if you have to deal with a new framework or language that's at least somewhat popular, then LLMs will speed you up massively. At the very least it will be able to rapidly generate discrete chunks of code to build a toolbelt like a Super StackOverflow.
Using LLMs are a skill, and if you don't prompt it correctly then it can veer towards garbage. You'll want to learn things like setting up a system prompt and initial messages, chaining queries from higher level design decisions down to smaller tasks, and especially managing context are all important. One of the devs at my workplace tried to raw-dog the LLM by dumping in a massive codebase with no further instruction while asking for like 10 different things simultaneously, and claimed AI was worthless when the result didn't compile after one attempt. Stuff like that is just a skill issue.
Use recent models, not stuff like 4o-mini. A lot of the devs at my current workplace tried experimenting with LLMs when they first blew up in early 2023, but those models were quite rudimentary compared to what we have today. Yet a lot of tools like Roo Cline or whatever have defaulted to old, crappy models to keep costs down, but that just results in bad code. You should be using one of 1) Claude Opus, 2) ChatGPT o3, or 3) Google Gemini 2.5 pro.
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Or even consider a comment from your fellow programmer, @TheAntipopulist:
https://www.themotte.org/post/2154/culture-war-roundup-for-the-week/333796?context=8#context
Notice how he didn't say that they're good at coding? He said that they're useful for his job.
LLMs are useful for SWEs, at least for some types some of the time. There is value here but they're poor programmers and to use them effectively you have to be relatively competent.
Its also very easy to fool yourself into thinking that they're much more valuable than they really are, likely due to how eloquently and verbosely they answer queries and requests.
I'd like to think I'm reasonably good at coding considering it's my job. However, it's somewhat hard to measure how effective a programmer or SWE is (Leetcode style questions are broadly known to be awful at this, yet it's what most interviewers ask for and judge candidates by).
Code is pretty easy to evaluate at a baseline. The biggest questions are "does it compile", and "does it give you the result you want" can be evaluated in like 10 seconds for most prompts, and that's like 90% of programming done right there. There's not a lot of room for BS'ing. There are of course other questions that take longer to answer, like "will this be prone to breaking due to weird edge cases", "is this reasonably performant", and "is this well documented". However, those have always been tougher questions to answer, even for things that are 100% done by professional devs.
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@TheAntipopulist I'll let you speak for yourself instead of us reading the tea leaves.
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Hang on. You're assuming I'm implying something in this comment that I don't think is a point I'm making. Notice I said average.
The average person who writes code. Not an UMC programmer who works for FAANG.
I strongly disagree that LLMs "suck at code". The proof of the pudding is in the eating; and for code, if it compiles and has the desired functionality.
More importantly, even from my perspective of not being able to exhaustively evaluate talent at coding (whereas I can usually tell if someone is giving out legitimate medical advice), there are dozens of talented, famous programmers who state the precise opposite of what you are saying. I don't have an exhaustive list handy, but at the very least, John Carmack? Andrej Karpathy? Less illustrious, but still a fan, Simon Willison?
Why should I privilege your claims over theirs?
Even the companies creating LLMs are use >10% of LLM written code for their own internal code bases. Google and Nvidia have papers about them being superhumanly good at things like writing optimized GPU kernels. Here's an example from Stanford:
https://crfm.stanford.edu/2025/05/28/fast-kernels.html
Or here's an example of someone finding 0day vulnerabilities in Linux using o3.
I (barely) know how to write code. I can't do it. I doubt even the average, competent programmer can find zero-days in Linux.
Of course, I'm just a humble doctor, and not an actual employable programmer. Tell me, are the examples I provided not about LLMs writing code? If they are, then I'm not sure you've got a leg to stand on.
TLDR: Other programmers, respected ones to boot, disagree strongly with you. Some of them even write up papers and research articles proving their point.
Yes, that is indeed what I meant as well.
I agree. And it doesn't. Code generated by LLMs routinely hallucinates APIs that simply don't exist, has grievous security flaws, or doesn't achieve the desired objective. Which is not to say humans never make such mistakes (well, they never make up non-existent APIs in my experience but the other two happen), but they can learn and improve. LLMs can't do that, at least not yet, so they are doing worse than humans.
I'm not saying you should! I'm not telling you that mine is the only valid opinion; I did after all say that reasonable people can disagree on this. My issue is solely that your comment comes off as dismissing anyone who disagrees with you as too inexperienced to have an informed opinion. When you say "They can't code? Have you seen the average code monkey?", it implies "because if you had, you wouldn't say that LLMs are worse". That is what I object to, not your choice to listen to other programmers who have different opinions than mine.
Please post an example of what you claim is a "routine" failure by a modern model (2.5 Pro, o3, Claude 3.7 Sonnet). This should be easy! I want to understand how you could possibly know how to program and still believe what you're writing (unless you're just a troll, sigh).
I've tried to have this debate with you in the past and I'm not doing it again, as nothing has changed. I'm not even trying to debate it with self_made_human really - I certainly wouldn't believe me over Carmack if I was in his shoes. My point here is that one should not attribute "this person disagrees with my take" to "they don't know what they're talking about".
Right, and I asked you for evidence last time too. Is that an unreasonable request? This isn't some ephemeral value judgement we're debating; your factual claims are in direct contradiction to my experience.
Right, and I gave it then. Which is why I am not going to bother doing it this time. Like I said, nothing has changed.
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Yes. The number of times I've gotten a better differential diagnosis from an LLM than in an ER is too damn high.
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