I mean, I’ll be honest, beyond the allegations of Dunning Kruger, I think this is actually just a grammatical mixup. I didn’t mean to write it the way you read it, and that may be my fault.
“If” AI replaces human programmers wholesale, new human code will stop being created
It starts with “if”. As in, it’s not a prediction of the future, it’s a response to the hypothetical future of AI being advocated for by techbros and corporations.
And “wholesale” doesn’t mean universally, it just means a lot.
And “new human code will stop being created” is true - I wasn’t saying all human code will stop being created. But AI replacing humans will stop humans from creating code. Many human projects will end, be reduced in scope, or won’t start, as AI is forced into projects that it isn’t yet ready for.
New human code will stop being created is a true - if ambiguous - statement. I do apologize for the ambiguity.
But given that AI does not perform well with retraining on AI output - and I’m sorry but I’d be happy to hear from anyone who can tell me that’s not a given - the ouroborous eats its own tail in more ways than one.
Less human code means less AI training. More AI creating code with less human input therefore leads to less developments and advancements in programming in general.
I appreciate that you didn’t mean to say what you said, but words mean things. I can only respond to what you say, not what you meant.
Especially here, where the difference entirely changes whether you’re right or not.
Because no, “less human code” doesn’t mean “less AI training”. It could mean a slowdown in how fast you can expand the training dataset, but again, old code doesn’t disappear just because you used it for training before. You don’t need a novel training dataset to train. The same data we have plus a little bit of new data is MORE training data, not less.
And less human code is absolutely not the same thing as “new human code will stop being created”. That’s not even a slip of the tongue, those are entirely different concepts.
There is a big difference between arguing that the pace of improvement will slow down (which is probably true even without any data scarcity) and saying that a lack of new human created code will bring AI training to a halt. That is flat out not a thing.
That this leads to “less developments and advancements in programming in general” is also a wild claim. How many brilliant programmers need to get replaced by AI before that’s true? Which fields are generating “developments and advancements in programming”? Are those fields being targeted by AI replacements? More or less than other fields? Does that come from academia or the private sector? Is the pace of development slowing down specifially in that area? Is AI generating “developments and advancements” of its own? Is it doing so faster or slower than human coders? Not at all?
People say a lot of stuff here. Again, on both sides of the aisle. If you know the answers to any of those questions you shouldn’t be arguing on the Internet, you should be investing in tech stock. Try to do something positive with the money after, too.
I’d say it’s more likely you’re just wildly extrapolating from relatively high level observations, though.
Hah, alright. I tried to bring this back to productive conversation, but we don’t share the same fundamentals on this topic, nor do we apparently share an understanding of grammatical conventions, or an understanding of how to productively address miscommunications. For example, one of my first responses started by clarifying that “it’s not that AI will successfully replace programmers”
I understand that the internet is so full of extreme, polarizing takes, and it’s hard to discuss nuance on here.
I’m not trying to give you homework for this conversation - we can absolutely wrap this up.
I just highly recommend that you look into the technological issues of AI training on AI output. If you do discover that I’m wrong, I absolutely do not ask you to return and educate me.
But believe it or not I would be extremely excited to learn I’m wrong, as overcoming that obstacle would be huge for the development of this technology.
Hm. That’s rolling the argument back a few steps there. None of the stuff we’ve talked about in the past few posts has anything to do with the impact of AI-on-AI training.
I mean, you could stretch the idea and argue that there is a filtering problem to be solved or whatever, but that aside everything I’m saying would still be true if AI training exploded any time it’s accidentally given a “Hello world” written by a machine.
A lack of new human created code will bring AI training to a halt. That’s just not a thing
I didn’t roll back anything. The entire conversation has ultimately been us disagreeing on this one point, and we clearly can’t overcome that with more back and forth, so I’m happy to agree to disagree. Cheers.
But that point is not the same as LLMs degrading when trained on its own data.
Again, it may be the same as the problem of “how do you separate AI generated data from human generated data”, so a filtering issue.
But it’s not the same as the problem of degradation due to self-training. Which I’m fairly sure you’re also misrepresenting, but I REALLY don’t want to get into that.
But hey, if you don’t want to keep talking about this that’s your prerogative. I just want to make it very clear that the reasons why that’s… just not a thing have nothing to do with training on AI-generated data. Your depiction is a wild extrapolation even if you were right about how poisonous AI-generated data is.
I mean, I’ll be honest, beyond the allegations of Dunning Kruger, I think this is actually just a grammatical mixup. I didn’t mean to write it the way you read it, and that may be my fault.
“If” AI replaces human programmers wholesale, new human code will stop being created
It starts with “if”. As in, it’s not a prediction of the future, it’s a response to the hypothetical future of AI being advocated for by techbros and corporations.
And “wholesale” doesn’t mean universally, it just means a lot.
And “new human code will stop being created” is true - I wasn’t saying all human code will stop being created. But AI replacing humans will stop humans from creating code. Many human projects will end, be reduced in scope, or won’t start, as AI is forced into projects that it isn’t yet ready for.
New human code will stop being created is a true - if ambiguous - statement. I do apologize for the ambiguity.
But given that AI does not perform well with retraining on AI output - and I’m sorry but I’d be happy to hear from anyone who can tell me that’s not a given - the ouroborous eats its own tail in more ways than one.
Less human code means less AI training. More AI creating code with less human input therefore leads to less developments and advancements in programming in general.
I appreciate that you didn’t mean to say what you said, but words mean things. I can only respond to what you say, not what you meant.
Especially here, where the difference entirely changes whether you’re right or not.
Because no, “less human code” doesn’t mean “less AI training”. It could mean a slowdown in how fast you can expand the training dataset, but again, old code doesn’t disappear just because you used it for training before. You don’t need a novel training dataset to train. The same data we have plus a little bit of new data is MORE training data, not less.
And less human code is absolutely not the same thing as “new human code will stop being created”. That’s not even a slip of the tongue, those are entirely different concepts.
There is a big difference between arguing that the pace of improvement will slow down (which is probably true even without any data scarcity) and saying that a lack of new human created code will bring AI training to a halt. That is flat out not a thing.
That this leads to “less developments and advancements in programming in general” is also a wild claim. How many brilliant programmers need to get replaced by AI before that’s true? Which fields are generating “developments and advancements in programming”? Are those fields being targeted by AI replacements? More or less than other fields? Does that come from academia or the private sector? Is the pace of development slowing down specifially in that area? Is AI generating “developments and advancements” of its own? Is it doing so faster or slower than human coders? Not at all?
People say a lot of stuff here. Again, on both sides of the aisle. If you know the answers to any of those questions you shouldn’t be arguing on the Internet, you should be investing in tech stock. Try to do something positive with the money after, too.
I’d say it’s more likely you’re just wildly extrapolating from relatively high level observations, though.
Hah, alright. I tried to bring this back to productive conversation, but we don’t share the same fundamentals on this topic, nor do we apparently share an understanding of grammatical conventions, or an understanding of how to productively address miscommunications. For example, one of my first responses started by clarifying that “it’s not that AI will successfully replace programmers”
I understand that the internet is so full of extreme, polarizing takes, and it’s hard to discuss nuance on here.
I’m not trying to give you homework for this conversation - we can absolutely wrap this up.
I just highly recommend that you look into the technological issues of AI training on AI output. If you do discover that I’m wrong, I absolutely do not ask you to return and educate me.
But believe it or not I would be extremely excited to learn I’m wrong, as overcoming that obstacle would be huge for the development of this technology.
Hm. That’s rolling the argument back a few steps there. None of the stuff we’ve talked about in the past few posts has anything to do with the impact of AI-on-AI training.
I mean, you could stretch the idea and argue that there is a filtering problem to be solved or whatever, but that aside everything I’m saying would still be true if AI training exploded any time it’s accidentally given a “Hello world” written by a machine.
I didn’t roll back anything. The entire conversation has ultimately been us disagreeing on this one point, and we clearly can’t overcome that with more back and forth, so I’m happy to agree to disagree. Cheers.
But that point is not the same as LLMs degrading when trained on its own data.
Again, it may be the same as the problem of “how do you separate AI generated data from human generated data”, so a filtering issue.
But it’s not the same as the problem of degradation due to self-training. Which I’m fairly sure you’re also misrepresenting, but I REALLY don’t want to get into that.
But hey, if you don’t want to keep talking about this that’s your prerogative. I just want to make it very clear that the reasons why that’s… just not a thing have nothing to do with training on AI-generated data. Your depiction is a wild extrapolation even if you were right about how poisonous AI-generated data is.