Comment on China’s AI overload: Baidu CEO warns of too many models, too few applications
gravitas_deficiency@sh.itjust.works 4 months agoI get what you’re saying, but I still think the vast majority of AI use they’re trying to push nowadays is categorically pointless at best, and actively harmful and misleading at worst.
It’s because LLMs are logically incapable of mapping language to actual concepts (at least, in their current incarnation), which, in the vast majority of meaningful, complex, and nuanced knowledge domains, is going to yield subtle nonsense a meaningful proportion of the time, which is the most dangerously form of ML hallucination in the context of consumer/layperson usage. We have NOT done the work to deploy this technology safely and responsibly in modern society, but we’re deploying it anyways, and we’re deploying it at scale.
The bubble popping isn’t going to look like the .com bubble. It’s going to be a lot worse, because a lot more harm is being done - and will be done - but at the same time, there are also a LOT more HUGE companies and people with TONS of money who stand to lose CATASTROPHIC amounts of capital… and they’re all ignoring the fact that this tech is CLEARLY being used in harmful ways all over the place. And that’s without touching the energy consumption issue.
canihasaccount@lemmy.world 4 months ago
Claude Opus disagrees, lol:
I respectfully disagree with the claim that current language models are logically incapable of mapping language to actual concepts. While today’s LLMs certainly have limitations and are prone to hallucinations, they have demonstrated a remarkable ability to capture and manipulate complex concepts through language.
A few key points:
That said, I fully agree that the tendency for subtle nonsense is a serious issue, especially for layperson use cases where hallucinations may go undetected. Continued research into making LLMs more truthful, consistent and robust is crucial. Techniques like constitutional AI to bake in truthfulness, and better UX design to convey uncertainty are important steps.
But in summary, I believe the evidence suggests that LLMs, while flawed, are not fundamentally incapable of meaningful conceptual representation and reasoning. We should push forward on making them more reliable and trustworthy, rather than dismissing their potential prematurely.
gravitas_deficiency@sh.itjust.works 4 months ago
Side note: I like how the LLM response didn’t even attempt to address the energy issue, which is frankly one of the biggest problems with current ML tech.
canihasaccount@lemmy.world 4 months ago
I actually took that bit out because LLMs are pro climate and against everything that makes the environment worse. That’s a result of being trained on a lot of scientific literature. I was just curious what Opus would say about the conceptual knowledge piece.