This is the same kind of short-sighted dismissal I see a lot in the religion vs science argument. When they hinge their pro-religion stance on the things science can’t explain, they’re defending an ever diminishing territory as science grows to explain more things. It’s a stupid strategy with an expiration date on your position.
All of the anti-AI positions, that hinge on the low quality or reliability of the output, are defending an increasingly diminished stance as the AI’s are further refined. And I simply don’t believe that the majority of the people making this argument actually care about the quality of the output. Even when it gets to the point of producing better output than humans across the board, these folks are still going to oppose it regardless. Why not just openly oppose it in general, instead of pinning your position to an argument that grows increasingly irrelevant by the day?
DeepSeek exposed the same issue with the anti-AI people dedicated to the environmental argument. We were shown proof that there’s significant progress in the development of efficient models, and it still didn’t change any of their minds. Because most of them don’t actually care about the environmental impacts. It’s just an anti-AI talking point that resonated with them.
The more baseless these anti-AI stances get, the more it seems to me that it’s a lot of people afraid of change and afraid of the fundamental economic shifts this will require, but they’re embarrassed or unable to articulate that stance. And it doesn’t help that the luddites haven’t been able to predict a single development. Just constantly flailing to craft a new argument to criticize the current models and tech. People are learning not to take these folks seriously.
Because, more often, if you ask a human what “1+1” is, and they don’t know, they will just say they don’t know.
AI will confidently insist its 3, and make up math algorythms to prove it.
And every company is pushing AI out on everyone like its always 10000% correct.
Its also shown its not intelligent. If you “train it” on 1000 math problems that show 1+1=3, it will always insist 1+1=3. It does not actually know how to add numbers, despite being a computer.
Maybe the marketers should be a bit more picky about what they slap “AI” on and maybe decision makers should be a little less eager to follow whatever Better Auto complete spits out, but maybe that’s just me and we really should be pretending that all these algorithms really have made humans obsolete and generating convincing language is better than correspondence with reality.
I’m not sure the anti-AI marketing stance is any more solid of a position. Though it’s probably easier to defend, since it’s so vague and not based on anything measurable.
Calling AI measurable is somewhat unfounded. Between not having a coherent, agreed-upon definition of what does and does not constitute an AI (we are, after all, discussing LLMs as though they were AGI), and the difficulty that exists in discussing the qualifications of human intelligence, saying that a given metric covers how well a thing is an AI isn’t really founded on anything but preference. We could, for example, say that mathematical ability is indicative of intelligence, but claiming FLOPS is a proxy for intelligence falls rather flat. We can measure things about the various algorithms, but that’s an awful long ways off from talking about AI itself (unless we’ve bought into the marketing hype).
So you’re saying the article’s measurements about AI agents being wrong 70% of the time is made up? Or is AI performance only measurable when the results help anti-AI narratives?
I would definitely bet it’s made up and poorly designed.
I wish that weren’t the case because having actual data would be nice, but these are almost always funded with some sort of intentional slant, for example nic vape safety where they clearly don’t use the product sanely and then make wild claims about how there’s lead in the vapes!
Homie you’re fucking running the shit completely dry for longer then any humans could possible actually hit the vape, no shit it’s producing carcinogens.
Go burn a bunch of paper and directly inhale the smoke and tell me paper is dangerous.
I mean, sure, in that the expectation is that the article is talking about AI in general. The cited paper is discussing LLMs and their ability to complete tasks. So, we have to agree that LLMs are what we mean by AI, and that their ability to complete tasks is a valid metric for AI. If we accept the marketing hype, then of course LLMs are exactly what we’ve been talking about with AI, and we’ve accepted LLMs features and limitations as what AI is. If LLMs are prone to filling in with whatever closest fits the model without regard to accuracy, by accepting LLMs as what we mean by AI, then AI fits to its model without regard to accuracy.
Except you yourself just stated that it was impossible to measure performance of these things. When it’s favorable to AI, you claim it can’t be measured. When it’s unfavorable for AI, you claim of course it’s measurable. Your argument is so flimsy and your understanding so limited that you can’t even stick to a single idea. You’re all over the place.
It questionable to measure these things as being reflective of AI, because what AI is changes based on what piece of tech is being hawked as AI, because we’re really bad at defining what intelligence is and isn’t. You want to claim LLMs as AI? Go ahead, but you also adopt the problems of LLMs as the problems of AIs. Defining AI and thus its metrics is a moving target. When we can’t agree to what is is, we can’t agree to what it can do.
Again, you only say it’s a moving target to dispel anything favorable towards AI. Then you do a complete 180 when it’s negative reporting on AI. Makes your argument meaningless, if you can’t even stick to your own point.
This is the same kind of short-sighted dismissal I see a lot in the religion vs science argument. When they hinge their pro-religion stance on the things science can’t explain, they’re defending an ever diminishing territory as science grows to explain more things. It’s a stupid strategy with an expiration date on your position.
All of the anti-AI positions, that hinge on the low quality or reliability of the output, are defending an increasingly diminished stance as the AI’s are further refined. And I simply don’t believe that the majority of the people making this argument actually care about the quality of the output. Even when it gets to the point of producing better output than humans across the board, these folks are still going to oppose it regardless. Why not just openly oppose it in general, instead of pinning your position to an argument that grows increasingly irrelevant by the day?
DeepSeek exposed the same issue with the anti-AI people dedicated to the environmental argument. We were shown proof that there’s significant progress in the development of efficient models, and it still didn’t change any of their minds. Because most of them don’t actually care about the environmental impacts. It’s just an anti-AI talking point that resonated with them.
The more baseless these anti-AI stances get, the more it seems to me that it’s a lot of people afraid of change and afraid of the fundamental economic shifts this will require, but they’re embarrassed or unable to articulate that stance. And it doesn’t help that the luddites haven’t been able to predict a single development. Just constantly flailing to craft a new argument to criticize the current models and tech. People are learning not to take these folks seriously.
Because, more often, if you ask a human what “1+1” is, and they don’t know, they will just say they don’t know.
AI will confidently insist its 3, and make up math algorythms to prove it.
And every company is pushing AI out on everyone like its always 10000% correct.
Its also shown its not intelligent. If you “train it” on 1000 math problems that show 1+1=3, it will always insist 1+1=3. It does not actually know how to add numbers, despite being a computer.
Haha. Sure. Humans never make up bullshit to confidently sell a fake answer.
Fucking ridiculous.
Maybe the marketers should be a bit more picky about what they slap “AI” on and maybe decision makers should be a little less eager to follow whatever Better Auto complete spits out, but maybe that’s just me and we really should be pretending that all these algorithms really have made humans obsolete and generating convincing language is better than correspondence with reality.
I’m not sure the anti-AI marketing stance is any more solid of a position. Though it’s probably easier to defend, since it’s so vague and not based on anything measurable.
Calling AI measurable is somewhat unfounded. Between not having a coherent, agreed-upon definition of what does and does not constitute an AI (we are, after all, discussing LLMs as though they were AGI), and the difficulty that exists in discussing the qualifications of human intelligence, saying that a given metric covers how well a thing is an AI isn’t really founded on anything but preference. We could, for example, say that mathematical ability is indicative of intelligence, but claiming FLOPS is a proxy for intelligence falls rather flat. We can measure things about the various algorithms, but that’s an awful long ways off from talking about AI itself (unless we’ve bought into the marketing hype).
So you’re saying the article’s measurements about AI agents being wrong 70% of the time is made up? Or is AI performance only measurable when the results help anti-AI narratives?
I would definitely bet it’s made up and poorly designed.
I wish that weren’t the case because having actual data would be nice, but these are almost always funded with some sort of intentional slant, for example nic vape safety where they clearly don’t use the product sanely and then make wild claims about how there’s lead in the vapes!
Homie you’re fucking running the shit completely dry for longer then any humans could possible actually hit the vape, no shit it’s producing carcinogens.
Go burn a bunch of paper and directly inhale the smoke and tell me paper is dangerous.
Agreed. 70% is astoundingly high for today’s models. Something stinks.
I mean, sure, in that the expectation is that the article is talking about AI in general. The cited paper is discussing LLMs and their ability to complete tasks. So, we have to agree that LLMs are what we mean by AI, and that their ability to complete tasks is a valid metric for AI. If we accept the marketing hype, then of course LLMs are exactly what we’ve been talking about with AI, and we’ve accepted LLMs features and limitations as what AI is. If LLMs are prone to filling in with whatever closest fits the model without regard to accuracy, by accepting LLMs as what we mean by AI, then AI fits to its model without regard to accuracy.
Except you yourself just stated that it was impossible to measure performance of these things. When it’s favorable to AI, you claim it can’t be measured. When it’s unfavorable for AI, you claim of course it’s measurable. Your argument is so flimsy and your understanding so limited that you can’t even stick to a single idea. You’re all over the place.
It questionable to measure these things as being reflective of AI, because what AI is changes based on what piece of tech is being hawked as AI, because we’re really bad at defining what intelligence is and isn’t. You want to claim LLMs as AI? Go ahead, but you also adopt the problems of LLMs as the problems of AIs. Defining AI and thus its metrics is a moving target. When we can’t agree to what is is, we can’t agree to what it can do.
Again, you only say it’s a moving target to dispel anything favorable towards AI. Then you do a complete 180 when it’s negative reporting on AI. Makes your argument meaningless, if you can’t even stick to your own point.