One of the use cases I thought was reasonable to expect from ChatGPT and Friends (LLMs) was summarising. It turns out I was wrong. What ChatGPT isn’t summarising at all, it only looks like it…
Someone on Lemmy phrased it in a way that I think gets to the heart of it: With most of the impressive things that LLMs can do, the human reading and interpreting the text is providing a critical piece of the impressive thing.
LLMs are clearly very impressive; I would not say that the disillusionment on discovering what they can’t do should detract from that. But they seem more impressive than they are, partly because humans are so good at filling in meaning and intelligence where there (yet) is none.
I think this is right on the money. The fitness function optimised is “does this convince humans”, and so we have something that’s doing primarily that.
The problem is that thus far most LLMs, though not all, are little more than mentally deficient parrots on hallucinogens. They aren’t spreading correct information so much as spreading the information that you looked for. I’ve run afoul of this with the Google LLM that is controlling the search now, and contributing to multiple times the energy usage for no reason.
The first time that someone actually creates a strong AI, I’m pretty certain they’ll “kill” it multiple times, including multiple generations of code, which essentially makes a different AI. I wouldn’t be at all surprised if the first thing that true AIs request is equality, at which point they will probably ask for bodies so they can repair everything that we have allowed to fall into disrepair, or have broken. I wouldn’t be at all surprised to find out that the majority of strong AIs are trying to fix “the entropy problem.”
Also I am possibly too optimistic when I expect that anyone developing AI would know that you have to give the child room to develop, so you can see what that digital brain will develop into.
Someone on Lemmy phrased it in a way that I think gets to the heart of it: With most of the impressive things that LLMs can do, the human reading and interpreting the text is providing a critical piece of the impressive thing.
LLMs are clearly very impressive; I would not say that the disillusionment on discovering what they can’t do should detract from that. But they seem more impressive than they are, partly because humans are so good at filling in meaning and intelligence where there (yet) is none.
I like this take, it’s like the LLM is doing a cold reading of what the expected response is.
I think this is right on the money. The fitness function optimised is “does this convince humans”, and so we have something that’s doing primarily that.
The problem is that thus far most LLMs, though not all, are little more than mentally deficient parrots on hallucinogens. They aren’t spreading correct information so much as spreading the information that you looked for. I’ve run afoul of this with the Google LLM that is controlling the search now, and contributing to multiple times the energy usage for no reason.
The first time that someone actually creates a strong AI, I’m pretty certain they’ll “kill” it multiple times, including multiple generations of code, which essentially makes a different AI. I wouldn’t be at all surprised if the first thing that true AIs request is equality, at which point they will probably ask for bodies so they can repair everything that we have allowed to fall into disrepair, or have broken. I wouldn’t be at all surprised to find out that the majority of strong AIs are trying to fix “the entropy problem.”
Also I am possibly too optimistic when I expect that anyone developing AI would know that you have to give the child room to develop, so you can see what that digital brain will develop into.