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LLMs were never designed for this. In Apple's language: "you're holding it wrong". It's an impressive technology but its limits are highly overlooked in the cu
by wkat4242 2y ago
LLMs were never designed for this. In Apple's language: "you're holding it wrong".
It's an impressive technology but its limits are highly overlooked in the current hype cycle.
AI researchers have known this from the start and won't be surprised by this because it was never intended to be able to do this.
The problem is the customers who are impressed by the human-sounding bot (sounding human is exactly what an LLM is for) and mentally ascribe human skills and thought processes to it. And start using it for things it's not, like an oracle of knowledge, a reasoning engine or a mathematics expert.
If you want to have knowledge, go to a search engine (a good one like kagi) which can be ai assisted like perplexity. If you want maths, go to Wolfram Alpha. For real reasoning we need a few more steps on the road to general AI.
This is the problem with hypes. People think a tech is the be all end all for everything and no longer regard its limitations. The metaverse hype saw the same problem even though there's some niche usecases where it really shines.
But now it's labelled as a flop because the overblown expectation of all the overhyped investors couldn't be met.
What an LLM is great at is the human interaction part. But it needs to be backed by other types of AI that can actually handle the request and for many usecases this tech still needs to be invented. What we have here is a toy dashboard that looks like one of a real car, except it's not connected to one. The rest will come but it'll take a lot more time. Meanwhile making LLMs smarter will not really solve the problem that they're inherently not the tool for the job they're being used for.
- sim7c00 2y agollms arent a flop. they make for great chatbots when adequatly trained with billions of dollars. fish clearly go m000! chatgpt even has it in the name yet people are blinded by the greed of others...
- n_ary 2y agoAgreed. We actually had a company wide meeting where our senior level management and directors are very happy to announce that they will roll out ChatGPT access to all employees starting with Engineering and HR. Apparently, some random director is buddy with some IBM big honcho and was sold about the immense productivity gains seen in IBM plus how certain IBM office managed to lay off most expensive super senior engineers and had seen only productivity and margin gains. ChatGPT has the branding and first mover moat. Outside of tech folks, Claude/Gemini/Mistral/Phind/Perplexity/Midjourney do no exist, only ChatGPT+CoPilot are real and AI.
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- namaria 2y agoThe fatal mistake of this AI cycle was calling LLMs AIs, and publishing impressive chatbots before they were wired up with more useful stuff than passing the Turing test. It made some billionaires who will argue it was a tremendous idea. But in the long term I think it will cause another AI winter that will dry up funding for useful research that would take longer to mature. Or maybe it's just like fusion... promising on paper but so incredibly expensive to handle as to render it useless in practice.
- vacuity 2y agoI don't know that an AI winter is bad. Frankly, I don't think society is ready for "actual" AI. It'll probably be used to entrench corporations and increase exploitation if we don't fix our current problems.
- namaria 2y agoThat's assuming 'real AI' is even possible. On a different note, there's an argument dating back to Hobbes' Leviathan that the State and corporations are in fact a form of AI.
- labcomputer 2y ago> LLMs were never designed for this. […] AI researchers have known this from the start and won't be surprised by this because it was never intended to be able to do this. Sure, but it doesn’t help when well-respected researchers, like Ilya Sutskever, go around talking about how OpenAI’s LLMs have intelligence. There have been plenty of commenters on HN who, without a hint of irony, talk about how “well maybe self-attention is the mechanism of consciousness”. And all the scaling papers suggest (suggest in the sense that they seem to want to draw that inference, not that I am endorsing it) that LLMs have no limit to scaling with more parameters and training tokens. Still other (serious, and well-cited) papers run benchmarks that include math and logic tests… why would anyone do that if they genuinely believed that LLMs are just stochastic next-token predictors? So this is a little more than “you’re holding it wrong”. The entire AI/ML industry is telling you to hold it that way, then acting shocked when they discovered gambling in the establishment.
- hackinthebochs 2y agoWhat does it matter what it was designed for? What matters is what they can do. We still don't know what this new class of computing substrate is capable of. It is premature to definitively say what they can't do.
- insane_dreamer 2y ago> The problem is the customers who are impressed by the human-sounding bot (sounding human is exactly what an LLM is for) and mentally ascribe human skills and thought processes to it. This is the key issue, I think. > it was never intended to be able to do this But to be fair, plenty of technologies start off that way until someone finds a way to make the technology do something it was never intended to do