←back to thread

Isaac Asimov describes how AI will liberate humans and their creativity (1992)

(www.openculture.com)
170 points bookofjoe | 5 comments | 10 Apr 25 14:30 UTC | HN request time: 0.333s | source
Show context
slibhb ◴[10 Apr 25 15:26 UTC] No.43644865[source]▶
LLMs are statistical models trained on human-generated text. They aren't the perfectly logical "machine brains" that Asimov and others imagined.

The upshot of this is that LLMs are quite good at the stuff that he thinks only humans will be able to do. What they aren't so good at (yet) is really rigorous reasoning, exactly the opposite of what 20th century people assumed.

replies(5): >>43645899 #>>43646817 #>>43647147 #>>43647395 #>>43650058 #
1. Lerc ◴[11 Apr 25 02:53 UTC] No.43650058[source]▶
"LLMs are statistical models"

I see this referenced over and over again to trivialise AI as if it is a fait acompli.

I'm not entirely sure why invoking statistics feels like a rebuttal to me. Putting aside the fact that LLMs are not purely statistics, even if they were what proof is there that you cannot make a statistical intelligent machine. It would not at all surprise me to learn that someone has made a purely statistical Turing complete model. To then argue that it couldn't think you are saying computers can never think, and by that and the fact that we think you are invoking a soul, God, or Penrose.

replies(3): >>43650367 #>>43653955 #>>43674231 #
2. lelandbatey ◴[11 Apr 25 03:54 UTC] No.43650367[source]▶
In this one case it's not meant to trivialize, it's meant to point out that LLMs don't behave the way we thought that AI would behave. We thought we'd have 100% logically-sound thinking machines because we built them on top of digital logic. We thought they'd be obtuse, we thought they'd be "book smart but not wise". LLMs are just different from that; hallucinations, the whole "fancy words and great sentences but no substance to a paragraph", all that is different from the rigid but perfect brains we thought AI would bring. That's what "statistical machine" seems to be trying to point out.

It was assumed that if you asked the same AI the same question, you'd get the same answer every time. But that's not how LLMs work (I know you can see them the same every time and get the same output but at we don't do that so how we experience them is different).

replies(1): >>43650455 #
3. Lerc ◴[11 Apr 25 04:13 UTC] No.43650455[source]▶
That's a very archaic view of AI, like 70's era symbolic AI.
4. vacuity ◴[11 Apr 25 14:06 UTC] No.43653955[source]▶
Personally, I have a negative opinion of LLMs, but I agree completely. Many people are motivated to reject LLMs solely because they see them as "soulless machines". Judge based on the facts of the matter, and make your values clear if you must bring them into it, but don't pretend you're not applying values when you are. You can do worse: kneejerk emotional reactions are just pointless.
5. slibhb ◴[13 Apr 25 17:08 UTC] No.43674231[source]▶
I did not in any way "trivialise AI". LLMS are amazing and a massive accomplishment. I just wanted to contrast them to Asimov's conception of AI.

> I'm not entirely sure why invoking statistics feels like a rebuttal to me. Putting aside the fact that LLMs are not purely statistics, even if they were what proof is there that you cannot make a statistical intelligent machine. It would not at all surprise me to learn that someone has made a purely statistical Turing complete model. To then argue that it couldn't think you are saying computers can never think, and by that and the fact that we think you are invoking a soul, God, or Penrose.

I don't follow this. I don't believe that LLMs are capable of thinking. I don't believe that computers, as they exist now, are capable of thinking (regardless of the program they run). I do believe that it is possible to build machines that can think -- we just don't know how.

To me, the strange move you're making is assuming that we will "accidentally" create thinking machines while doing AI research. On the contrary, I think we'll build thinking, conscious machines after understanding our own consciousness, or at least the consciousness of other animals, and not before.