"If all of this was done to better humanity, AI development would be done in public, data would be legally obtained, models would be released for free, access wouldn't be gatekept behind ever increasing subscription costs."
The vast majority of AI development is public. There are papers literally every single day to read. In fact everything you need to build Claude and GPT models is public. Thanks to Google, DeepSeek, and all the other research labs. There are more research labs than there are closed shops. In fact there really is only one Anthropic, and lately maybe OpenAI. Google still releases papers all the time on AI.
There are more open source models than closed source models and all of them are accessible without a subscription. Yeah you still need to pay for them, but hey as we build out infrastructure and more time is put into efficient models today will easily run on person compute of the future.
What do you mean with "open-source"? Of course, the inference code for all the open weight models is publically available - see llama.cpp or hf transformers.
There are, however, very few models where also the full training pipeline is available. Olmo by AI2 comes to mind.
> I am going to state a bet: In 5 to 10 years, once all the vibe coders get hooked into LLMs, there's going to be so much unmaintainable, wrongly architectured crap code in every codebase they touch, that by then they are unable to get any work done without consulting their LLM. And if that heap of collected technical debt becomes so large that even the LLM fails
In 5-10 years AI is going to be so much better than even the best human coder that this is a moot point. If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
I can understand hating AI, but it seems like many who are against genAI have a strange delusional disbelief of how good the models are, and the trend-line we are on. They think that their special skills will never be eclipsed by an AI model. If you are going on a crusade against genAI and LLM’s at least be honest about what you’re up against.
>If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
In my organization, this is already happening. We've been using LLMs to boost our test coverage without touching our human code, then use that as a scaffold to let it go through and refactor, clean up, and optimize, and then validating against both our tests and gold standard test datasets.
In our case, it's made a legacy codebase far more readable to our junior engineers, and the performance improvements (from using an autoresearch-style approach) has resulted in a six figure decrease in our compute spend for the production service we trialed this on.
In my opinion by Opus 4.7 Claude was better at coding than most programmers. While there is certainly more slop being produced now overall, I believe the quality of important projects like Linux and proprietary software created by large companies, where advanced AI will be piloted by skilled engineers, will improve in quality, maybe dramatically, over the next decade.
I am still 100% willing to concede that Opus 4.8 or even how good Mythos is supposed to be is not yet at the general reasoning ability of top 5% coders or any smart human with a few years of domain experience. However the rate of improvement is so consistent and unrelenting that it seems silly to assume that it will just stop short of human level. Even if algorithmic, research and data quality improvements suddenly stopped, we still have years of better GPU’s and scaling
Your statement seems to be implying (correctly) that LLMs can program, but just not as well as humans. If they're able to program presumably without "thinking" as you seem to be (implicitly) narrowly defining it, then why do you think that limits them to always being sub-par?
It seems like if they can do it, that there's no reason they can't eventually be trained to do it better up to and beyond human performance. It seems strange to suggest that thinking unlocks some nominal margin of "better" specifically that can't be overcome.
All of that aside, even if they can't outperform the top human programmers...what if they get to within a margin where they're still better than most? Isn't a 95th percentile programmer that can run 24/7 and continuously refine its work still going to ultimately come out on top?
What LLM’s can do now, 99.999% of people 3 years ago would say would only be possible with “thinking”. To claim that LLM’s aren’t thinking is sensible if your definition of thinking is inextricably linked to the chemical processes that occur in human brains, but then it ceases to be a useful definition with respect to evaluating a system’s ability to process information, form connections, and reason via abstraction. It is objectively true that LLM’s can do the latter things.
The issue about AI is that it's gobbling so much information that at some point you couldn't tell the difference. Programming specifically is something that inherently documents itself, meaning while human communication and context and memes and culture is something that evolves and exists many times outside of textual mediums, as soon as any new piece of code is born it is now part of the AI's dataset. And it doesn't help that a vast majority of our code is pretty damn repetitive, especially if you insert code written in the span of two decades and more into the future.
Tldr : The better we get at coding, the more code we write, the better AI gets at coding.
> If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
What funny nonsense. This is like saying AI will replace artists because it's better than your average artist.
Software engineering is as much an artform as it is infrastructure. AI cannot approximate even a poor engineer because it cannot capture the full context of a problem to be solved.
There is an artistic element to coding but claiming it is some sort of unquantifiable abstract mystical thing is silly. There are many metrics, objective and easily measured, that AI can match humans on in code generation.
None of those 'objective' metrics matter as long as the outcomes is incredibly visible and damaging. You say that AI is matching humans, but what people see is apps getting worse with more bugs than ever, an inability to reach anyone that actually gives a shit and second order effects on things like general computing.
It doesn't help that most of these 'metrics' are literally invented by and ran by the companies that benefit the most from said metrics.
I've seen this shit at major companies before, because the c-suite loves to invent metrics that make their product look good even if it ignores reality.
The median != the frontier. When looking at all the crappy vibe coded apps and saying they’re worse than the normal expectations of pre-AI applications, you’re comparing some default app-generator model (Gemini flash or worse) with the security integrity of enterprise apps (which still have security flaws). This is very different from comparing Opus 4.8 to the median coder, given the same context, parameters, access to tools, time, and feedback loops.
The frontier has been on the horizon for the past 5 years, where people say it's going to replace all engineers and we'll be in some sort of software heaven. Until when and IF we reach that point, the only thing that matters are the negative outcomes we currently experience as a result.
I have read the article, but at some point, the statement "GenAI: Capitalism in Perfection" did not make sense to me, please don't bash me. I disagree with most of the author's points.
I do not understand what the problem is. There are both closed and open models. You can run your own machine with dozens of open models. You can train your own model. You can do everything on your own.
Of course, there are limitations. For example, you cannot magically have all the best hardware at your disposal, but that limitation also exists in normal programming.
I sincerely disagree that AI is worse than the crypto/NFT hype… pig butchering is one of the most disgusting practices imaginable and it was turned into a legitimate low effort vehicle for scammers due to web3 and the hype train.
AI is definitely on a scale of magnitude more but it has inherent value outside of “scarcity”. It’s actually quite the opposite with sheer supply/demand balance. Also investing in crypto made me less money than investing in myself by using AI to learn and challenge myself to think differently.
I'm not sure an article that gives one paragraph summaries of the common anti-LLM talking points is really a substantial contribution to the conversation. This is essentially a snarked up version of a "Criticisms" section one would expect to find in a Wikipedia article on modern generative AI. It's fairly hollow unless you've had your head in the sand and are just getting up to speed on the current conversation.
The thing I don't like about AI doomerism posts is the intellectual dishonesty. We're going to cure cancers we haven't cured before, using AI. We're going to make better diagnoses faster. Adults will be able to accomplish more tasks due to the reduction in the barrier of specialized knowledge and skill. Kids that grow up today will be able to solve their own problems 100x faster and easier than we do today. Companies will be able to triage, diagnose, and fix issues faster and easier than ever before. We will likely spend less money, do less work, and gain more in goods, services, solutions, and health, than ever before.
AI is going to transform people's lives for the better, because every single solitary advancement in human technology in history has had both benefits and drawbacks. If the only thing you can come up with is drawbacks, you're being willfully ignorant.
The author speaks about the benefits of ML image processing algorithms "which have been used in countless industries in numerous settings to solve hard, real world problems". So it doesn't seem fair to paint this person as someone ignoring the benefits completely, as you seem to be doing.
Having said that, expecting writers to devote equal time to the pros and cons of an argument can set up a false equivalence. It tells the reader that the benefits and drawbacks must be somewhat equal, even when they're not.
> If the only thing you can come up with is drawbacks, you're being willfully ignorant.
Does this also go the other way? If you can't come up with any drawbacks, you're being "wilfully ignorant"? You may want to amend your post!
LLMs (what's being hyped up as "AI" by the likes of Google, OpenAI, Anthropic, etc) are not the same category of product as the kind of AI that's going to help cure cancers.
Trying to conflate them, and use that to defend LLMs, is what's intellectually dishonest.
There is still, to this very day, not a good reason for most businesses to run their workloads in the cloud (startups being a notable exception). So, your argument isn't as compelling as you think.
I generally try not to be outright dismissive of articles/blogposts, but I don't see a ton of value in reading about someone being against opening Pandora's Box after the box has been opened. It can never be shut and we are going to have to figure out how to live with the consequences of it.
I gave the article a chance regardless and it's nothing I've not read before.
Indoor smoking in restaurants used to be legal, we made it illegal. Slavery used to be legal, we made it illegal. Don’t say that it’s not possible to stop bad things that are already happening.
It’s kind of a pointless article. Also framed wrong. Generative AI doesn’t “stand for” anything. It’s just a cool technology. Author’s time would be better spent criticizing big tech perhaps.
Actively detaching yourself from the problems of a technology doesn't suddenly make it a pointless exercise. It just puts into question whether you have any moral compass whatsoever.
"If all of this was done to better humanity, AI development would be done in public, data would be legally obtained, models would be released for free, access wouldn't be gatekept behind ever increasing subscription costs."
The vast majority of AI development is public. There are papers literally every single day to read. In fact everything you need to build Claude and GPT models is public. Thanks to Google, DeepSeek, and all the other research labs. There are more research labs than there are closed shops. In fact there really is only one Anthropic, and lately maybe OpenAI. Google still releases papers all the time on AI.
There are more open source models than closed source models and all of them are accessible without a subscription. Yeah you still need to pay for them, but hey as we build out infrastructure and more time is put into efficient models today will easily run on person compute of the future.
Is there any mainstream model that is actually open-source (not just open-weight)?
What do you mean with "open-source"? Of course, the inference code for all the open weight models is publically available - see llama.cpp or hf transformers.
There are, however, very few models where also the full training pipeline is available. Olmo by AI2 comes to mind.
There are more ants than humans in the world, too.
But which one is driving major changes to the world?
Just because you can point to an absolute number of open source models doesn't mean much when the models that 99.9% of the world cares about aren't.
> I am going to state a bet: In 5 to 10 years, once all the vibe coders get hooked into LLMs, there's going to be so much unmaintainable, wrongly architectured crap code in every codebase they touch, that by then they are unable to get any work done without consulting their LLM. And if that heap of collected technical debt becomes so large that even the LLM fails
In 5-10 years AI is going to be so much better than even the best human coder that this is a moot point. If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
I can understand hating AI, but it seems like many who are against genAI have a strange delusional disbelief of how good the models are, and the trend-line we are on. They think that their special skills will never be eclipsed by an AI model. If you are going on a crusade against genAI and LLM’s at least be honest about what you’re up against.
>If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
In my organization, this is already happening. We've been using LLMs to boost our test coverage without touching our human code, then use that as a scaffold to let it go through and refactor, clean up, and optimize, and then validating against both our tests and gold standard test datasets.
In our case, it's made a legacy codebase far more readable to our junior engineers, and the performance improvements (from using an autoresearch-style approach) has resulted in a six figure decrease in our compute spend for the production service we trialed this on.
In my opinion by Opus 4.7 Claude was better at coding than most programmers. While there is certainly more slop being produced now overall, I believe the quality of important projects like Linux and proprietary software created by large companies, where advanced AI will be piloted by skilled engineers, will improve in quality, maybe dramatically, over the next decade.
I am still 100% willing to concede that Opus 4.8 or even how good Mythos is supposed to be is not yet at the general reasoning ability of top 5% coders or any smart human with a few years of domain experience. However the rate of improvement is so consistent and unrelenting that it seems silly to assume that it will just stop short of human level. Even if algorithmic, research and data quality improvements suddenly stopped, we still have years of better GPU’s and scaling
Programming requires thinking and LLMs can't think. Therefore LLMs cannot be better than humans at programming.
Your statement seems to be implying (correctly) that LLMs can program, but just not as well as humans. If they're able to program presumably without "thinking" as you seem to be (implicitly) narrowly defining it, then why do you think that limits them to always being sub-par?
It seems like if they can do it, that there's no reason they can't eventually be trained to do it better up to and beyond human performance. It seems strange to suggest that thinking unlocks some nominal margin of "better" specifically that can't be overcome.
All of that aside, even if they can't outperform the top human programmers...what if they get to within a margin where they're still better than most? Isn't a 95th percentile programmer that can run 24/7 and continuously refine its work still going to ultimately come out on top?
What LLM’s can do now, 99.999% of people 3 years ago would say would only be possible with “thinking”. To claim that LLM’s aren’t thinking is sensible if your definition of thinking is inextricably linked to the chemical processes that occur in human brains, but then it ceases to be a useful definition with respect to evaluating a system’s ability to process information, form connections, and reason via abstraction. It is objectively true that LLM’s can do the latter things.
Programming is just telling a computer what to do. LLMs gave turned out to be pretty good at that. What is thinking, anyway?
Well I guess that settles it. Losing to LLMs in CTF challenges must be in my head.
>Programming requires thinking
The issue about AI is that it's gobbling so much information that at some point you couldn't tell the difference. Programming specifically is something that inherently documents itself, meaning while human communication and context and memes and culture is something that evolves and exists many times outside of textual mediums, as soon as any new piece of code is born it is now part of the AI's dataset. And it doesn't help that a vast majority of our code is pretty damn repetitive, especially if you insert code written in the span of two decades and more into the future.
Tldr : The better we get at coding, the more code we write, the better AI gets at coding.
> In 5-10 years AI is going to be so much better than even the best human coder
How, if it learns from humans?
> If anything AI will be used to correct all the crappy human made code that is still being pushed due to the vanity of coders still pretending that they are better than AI at coding.
What funny nonsense. This is like saying AI will replace artists because it's better than your average artist.
Software engineering is as much an artform as it is infrastructure. AI cannot approximate even a poor engineer because it cannot capture the full context of a problem to be solved.
There is an artistic element to coding but claiming it is some sort of unquantifiable abstract mystical thing is silly. There are many metrics, objective and easily measured, that AI can match humans on in code generation.
None of those 'objective' metrics matter as long as the outcomes is incredibly visible and damaging. You say that AI is matching humans, but what people see is apps getting worse with more bugs than ever, an inability to reach anyone that actually gives a shit and second order effects on things like general computing.
It doesn't help that most of these 'metrics' are literally invented by and ran by the companies that benefit the most from said metrics. I've seen this shit at major companies before, because the c-suite loves to invent metrics that make their product look good even if it ignores reality.
The median != the frontier. When looking at all the crappy vibe coded apps and saying they’re worse than the normal expectations of pre-AI applications, you’re comparing some default app-generator model (Gemini flash or worse) with the security integrity of enterprise apps (which still have security flaws). This is very different from comparing Opus 4.8 to the median coder, given the same context, parameters, access to tools, time, and feedback loops.
The frontier has been on the horizon for the past 5 years, where people say it's going to replace all engineers and we'll be in some sort of software heaven. Until when and IF we reach that point, the only thing that matters are the negative outcomes we currently experience as a result.
I have read the article, but at some point, the statement "GenAI: Capitalism in Perfection" did not make sense to me, please don't bash me. I disagree with most of the author's points.
I do not understand what the problem is. There are both closed and open models. You can run your own machine with dozens of open models. You can train your own model. You can do everything on your own.
Of course, there are limitations. For example, you cannot magically have all the best hardware at your disposal, but that limitation also exists in normal programming.
I sincerely disagree that AI is worse than the crypto/NFT hype… pig butchering is one of the most disgusting practices imaginable and it was turned into a legitimate low effort vehicle for scammers due to web3 and the hype train.
AI is definitely on a scale of magnitude more but it has inherent value outside of “scarcity”. It’s actually quite the opposite with sheer supply/demand balance. Also investing in crypto made me less money than investing in myself by using AI to learn and challenge myself to think differently.
I'm not sure an article that gives one paragraph summaries of the common anti-LLM talking points is really a substantial contribution to the conversation. This is essentially a snarked up version of a "Criticisms" section one would expect to find in a Wikipedia article on modern generative AI. It's fairly hollow unless you've had your head in the sand and are just getting up to speed on the current conversation.
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The thing I don't like about AI doomerism posts is the intellectual dishonesty. We're going to cure cancers we haven't cured before, using AI. We're going to make better diagnoses faster. Adults will be able to accomplish more tasks due to the reduction in the barrier of specialized knowledge and skill. Kids that grow up today will be able to solve their own problems 100x faster and easier than we do today. Companies will be able to triage, diagnose, and fix issues faster and easier than ever before. We will likely spend less money, do less work, and gain more in goods, services, solutions, and health, than ever before.
AI is going to transform people's lives for the better, because every single solitary advancement in human technology in history has had both benefits and drawbacks. If the only thing you can come up with is drawbacks, you're being willfully ignorant.
> We're going to cure cancers we haven't cured before
“You’re absolutely right – I applied the invasive treatment to the wrong leg. Would you like me to try again?”
> Kids that grow up today will be able to solve their own problems 100x faster and easier than we do today.
Not if they stop thinking on their own.
> We will likely spend less money
How exactly does the tool that costs hundreds of dollars per month help me spend less money?
The author speaks about the benefits of ML image processing algorithms "which have been used in countless industries in numerous settings to solve hard, real world problems". So it doesn't seem fair to paint this person as someone ignoring the benefits completely, as you seem to be doing.
Having said that, expecting writers to devote equal time to the pros and cons of an argument can set up a false equivalence. It tells the reader that the benefits and drawbacks must be somewhat equal, even when they're not.
> If the only thing you can come up with is drawbacks, you're being willfully ignorant.
Does this also go the other way? If you can't come up with any drawbacks, you're being "wilfully ignorant"? You may want to amend your post!
LLMs (what's being hyped up as "AI" by the likes of Google, OpenAI, Anthropic, etc) are not the same category of product as the kind of AI that's going to help cure cancers.
Trying to conflate them, and use that to defend LLMs, is what's intellectually dishonest.
Unless that is done, it’s merely fiction. While the negative impact of LLM is already here. Slop, aggressive scraping, workflow disruption at scale,…
2005: "Why would I run my workloads in the cloud? I have 400 certifications!"
There is still, to this very day, not a good reason for most businesses to run their workloads in the cloud (startups being a notable exception). So, your argument isn't as compelling as you think.
Try reading the article next time.
I generally try not to be outright dismissive of articles/blogposts, but I don't see a ton of value in reading about someone being against opening Pandora's Box after the box has been opened. It can never be shut and we are going to have to figure out how to live with the consequences of it.
I gave the article a chance regardless and it's nothing I've not read before.
Indoor smoking in restaurants used to be legal, we made it illegal. Slavery used to be legal, we made it illegal. Don’t say that it’s not possible to stop bad things that are already happening.
It’s kind of a pointless article. Also framed wrong. Generative AI doesn’t “stand for” anything. It’s just a cool technology. Author’s time would be better spent criticizing big tech perhaps.
Actively detaching yourself from the problems of a technology doesn't suddenly make it a pointless exercise. It just puts into question whether you have any moral compass whatsoever.