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Someone said, "The AI you use today is the worst AI that you will ever use."
I agree with the substance, but would argue the author fails to "understand how AI works" in an important way: LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another Modern chat-tuned LLMs are not simply statistical models trained on web scale datasets.…
What would labeling even do for an LLM? (Not including multimodal)
The whole point of attention is that it uses existing text to determine when tokens are related to other tokens, no?
Earlier quoted context omitted.
Yeah, but should we have psychosis force multipliers?
We have that now, in social media. If you create some way for large numbers of people with the same nutty beliefs to easily communicate, you get a psychosis force multiplier. Before social media, nuttyness tended to be diluted by the general population.
> Few phenomena demonstrate the perils that can accompany AI illiteracy as well as “Chatgpt induced psychosis,” the subject of a recent Rolling Stone article about the growing number of people who think their LLM is a sapient spiritual guide. Some users have come to believe that the chatbot they’re interacting with is a god—“ChatGPT Jesus,” as a man whose wife fell prey to LLM-inspired delusions put it—while others a…
> Few phenomena demonstrate the perils that can accompany AI illiteracy as well as “Chatgpt induced psychosis,” the subject of a recent Rolling Stone article about the growing number of people who think their LLM is a sapient spiritual guide. People have been caught in that trap ever since the invention of religion. This is not a new problem.
I agree with the substance, but would argue the author fails to "understand how AI works" in an important way: LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another Modern chat-tuned LLMs are not simply statistical models trained on web scale datasets.…
What really happens: "for some reason" higher up management thinks AI will let idiots run extremely complex companies. It doesn't. What AI actually does is like any other improved tool: it's a force multiplier. It allows a small number of highly experienced, very smart people, do double or triple the work they can do now. In other words: for idiot management, AI does nothing (EXCEPT enable the competition) Of course,…
Now that they have AI, I can see it become an 'idiocy multiplier'. Already software is starting to break in subtle ways, it's slow, laggy, security processes have become a nightmare.
I agree with the substance, but would argue the author fails to "understand how AI works" in an important way: LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another Modern chat-tuned LLMs are not simply statistical models trained on web scale datasets.…
Personally my inaccurate estimate is much lower than yours. When non-instruction tuned versions of GPT-3 were available, my perception is that most of the abilities and characteristics that we associate with talking to an LLM were already there - just more erratic, e.g., you asked a question and the model might answer or might continue it with another question (which is also a plausible continuation of the provided text). But if it did "choose" to answer, it could do so with comparable accuracy to the instruction-tuned versions.
Instruction tuning made them more predictable, and made them tend to give the responses that humans prefer (e.g. actually answering questions, maybe using answer formats that humans like, etc.), but I doubt it gave them many abilities that weren't already there.