5 ms·

its in the running for the biggest technological change maybe in the last 100 years? whats so confusing about this, thinking machines have been invented

zikduruqe 1y ago
Yeah... we took raw elements from the earth, struck them with bits of lightning, and now they think for us. That in itself is pretty amazing.
- layer8 1y ago
  Our brains are ultimately made out of elements from the food we are eating.
- mikert89 1y ago
  yeah like we are living in the dawn of the future. science fiction is now real. aliens live among us, locked in sillicon.
greesil 1y ago
It certainly looks like thinking
- dgfitz 1y ago
  And magic tricks look like magic. Turns out they’re not magical. I am so floored that at least half of this community, usually skeptical to a fault, evangelizes LLMs so ardently. Truly blows my mind. I’m open to them becoming more than a statistical token predictor, and I think it would be really neat to see that happen. They’re nowhere close to anything other than a next-token-predictor.
  - chpatrick 1y ago
    When you type you're also producing one character at a time with some statistical distribution. That doesn't imply anything regarding your intelligence.
  - BoiledCabbage 1y ago
    > I am so floored that at least half of this community, usually skeptical to a fault, evangelizes LLMs so ardently. Truly blows my mind. ... > I’m open to them becoming more than a statistical token predictor, and I think it would be really neat to see that happen I'm more shocked that so many people seem unable to come to grips with the fact that something can be a next token predictor and demonstrate intelligence. That's what blows my mind, people unable to see that something can be more than the sum of its parts. To them, if something is a token predictor clearly it can't be doing anything impressive - even while they watch it do I'm impressive things.
    - seadan83 1y ago
      > I'm more shocked that so many people seem unable to come to grips with the fact that something can be a next token predictor and demonstrate intelligence. Except LLMs have not shown much intelligence. Wisdom yes, intelligence no. LLMs are language models, not 'world' models. It's the difference of being wise vs smart. LLMs are very wise as they have effectively memorized the answer to every question humanity has written. OTOH, they are pretty dumb. LLMs don't "understand" the output they produce. > To them, if something is a token predictor clearly it can't be doing anything impressive Shifting the goal posts. Nobody said that a next token predictor can't do impressive things, but at the same time there is a big gap between impressive things and other things like "replace very software developer in the world within the next 5 years."
      - bondarchuk 1y ago
        I think what BoiledCabbage is pointing out is that the fact that it's a next-token-predictor is used as an argument for the thesis that LLMs are not intelligent, and that this is wrong, since being a next-token-predictor is compatible with being intelligent. When mikert89 says "thinking machines have been invented", dgfitz in response strongly implies that for a for thinking machines to exist, they must become "more than a statistical token predictor". Regardless of whether or not thinking machines currently exist, dgfitz argument is wrong and BoiledCabbage is right to point that out.
        1y ago
  - tim333 1y ago
    IMO gold?
  - greesil 1y ago
    Maybe thinking needs a Turing test. If nobody can tell the difference between this and actual thinking then it's actually thinking. /s, or is it?
    - sitkack 1y ago
      If I order Chinese takeout, but it gets made by a restaurant that doesn't know what Chinese food tastes like, then is that food really Chinese takeout?
      - chpatrick 1y ago
        If it tastes like great Chinese food (which is a pretty vague concept btw, it's a big country), does it matter?
      - dangus 1y ago
        Useless analogy, especially in the context of a gigantic category of fusion cuisine that is effectively franchised and adapted to local tastes. If I have never eaten a hamburger but own a McDonald’s franchise, am I making an authentic American hamburger? If I have never eaten fries before and I buy some frozen ones from Walmart, heat them up, and throw them in the trash, did I make authentic fries? Obviously the answer is yes and these questions are completely irrelevant to my sentience.
        greesil 1y ago
        Not exactly. When "intelligence" is like your frozen Walmart fries, the analogy works a bit better. Some people are arguing that yes, you can buy some frozen intelligence from your local (internet) store.
    - dangus 1y ago
      This is like watching a Jurassic Park movie and proclaiming “if nobody can tell the difference between a real dinosaur and a CGI dinosaur…” when literally everyone in the theater can tell that the dinosaur is CGI.
  - deleted 1y ago
    [deleted]
  - svara 1y ago
    > I’m open to them becoming more than a statistical token predictor, and I think it would be really neat to see that happen What exactly do you mean by that? I've seen this exact comment stated many times, but I always wonder: What limitations of AI chat bots do you currently see that are due to them using next token prediction?
    - dangus 1y ago
      I feel like the logic of your question is actually inverted from reality. It’s kind of like you’re saying “prove god doesn’t exist” when it’s supposed to be “prove god exists.” If a problem isn’t documented LLMs simply have nowhere to go. It can’t really handle the knowledge boundary [1] at all, since it has no reasoning ability it just hallucinates or runs around in circles trying the same closest solution over and over. It’s awesome that they get some stuff right frequently and can work fast like a computer but it’s very obvious that there really isn’t anything in there that we would call “reasoning.” [1] https://matt.might.net/articles/phd-school-in-pictures/ https://matt.might.net/articles/phd-school-in-pictures/
      - frm88 1y ago
        Thank you for that link. So very true. (I admit, I laughed)
      - svara 1y ago
        Not at all. I don't want to address directly your claim about lack of generalization, because there's a more basic issue with the GP statement. Even though I will say, today's models do seem to generalize quite a bit better than you make it sound. But more importantly, you and GP don't mention any evidence for why that is due to specifically using next token prediction as a mechanism. Why would it not be possible for a highly generalizing model to use next token prediction for its output? That doesn't follow to me at all, which is why the GP statement reads so weird.
        Jensson 1y ago
        > Why would it not be possible for a highly generalizing model to use next token prediction for its output? The issue is that it uses next token prediction for its training, it doesn't matter how it outputs things but it matters how its trained. As long as these models are trained to be next token predictors you will always be able to find flaws with it that are related to it being a next token predictor, so understanding that is how they work really makes them much easier to use. So since it is so easy to get the model to make errors due to it being trained to just predict tokens people argue that is proof they aren't really thinking. Like, any extremely common piece of text when altered slightly will typically still output the same follow-up as the text it has seen millions of times even though it makes no logical sense. That is due to them being next token predictors instead of reasoning machines. You might say its unfair to abuse their weaknesses as next token predictors, but then you admit that being a next token predictor interferes with their ability to reason, which was the argument you said you don't understand.
Spivak 1y ago
and they don't have to revolutionize the world to be revolutionary in our industry. it might be that the use-cases unlocked by this new technology won't move the needle in an industrial revolution sense but it's nonetheless a huge leap for computer science and the kinds of tasks that can be done with software. i don't understand people who seem to have strongly motivated reasoning to dismiss the new tech as just a token predictor or stochastic parrot. it's confusing the means with the result, it's like saying Deep Blue is just search, it's not actually playing chess, it doesn't understand the game—like that matters to people playing against it.
- jurking_hoff 1y ago
  [dead]
- mattbuilds 1y ago
  I personally don't dismiss or advocate for AI/LLMs, I just take what I actually see happening, which doesn't appear revolutionary to me. I've spent some time trying to integrate it into my workflow and I see some use cases here and there but overall it just hasn't made a huge impact for me personally. Maybe it's a skill issue but I have always been pretty effective as a dev and what it solves has never been the difficult or time consuming part of creating software. Of course I could be wrong and it will change everything, but I want to actually see some evidence of that before declaring this the most impactful technology in the last 100 years. I personally just feel like LLMs make the easy stuff easier, the medium stuff slightly more difficult and the hard stuff impossible. But I personally feel that way about a lot of technology that comes along though, so it could just be I'm missing the mark.
  - hodgehog11 1y ago
    > I have always been pretty effective as a dev > LLMs make the easy stuff easier I think this is the observation that's important right now. If you're an expert that isn't doing a lot of boilerplate, LLMs don't have value to you right now. But they can acceptably automate a sizeable number of entry-level jobs. If those get flushed out, that's an issue, as not everyone is going to be a high-level expert. Long-term, the issue is we don't know where the ceiling is. Just because OpenAI is faltering doesn't mean that we've hit that ceiling yet. People talk about the scaling laws as a theoretical boundary, but it's actually the opposite. It shows that the performance curve could just keep going up even with brute force, which has never happened before in the history of statistics. We're in uncharted territory now, so there's good reason to keep an eye on it.
mvdtnz 1y ago
[flagged]
lm28469 1y ago
Bigger than internet and computers? Lmao, I don't even know if I'd place it as high as the GPS. Some people are terminally online and it really shows...
mylifeandtimes 1y ago
Wait-- are you claiming that AI is a bigger technological change than the development of computing devices and a networking infrastructure for those devices?
- gitaarik 1y ago
  Well, is the computer revolution bigger than the electricity revolution? They just build on each other. But it might be interpreted as the next new abstraction that causes major changes in the industry.
_ea1k 1y ago
I'm starting to learn that AI progress is just really hard to talk about. On the one hand, I completely agree with you. I've even said before, here on Hacker News, that AI is underhyped compared to the real world impact that it will have. On the other, I run into people in person that seem to think dabbing a little cursor on a project will suddenly turn everyone into 100x engineers. It just doesn't work that way at all, but good luck dealing with the hypemeisters.

zikduruqe 1y ago

Yeah... we took raw elements from the earth, struck them with bits of lightning, and now they think for us. That in itself is pretty amazing.

layer8 1y ago
Our brains are ultimately made out of elements from the food we are eating.
mikert89 1y ago
yeah like we are living in the dawn of the future. science fiction is now real. aliens live among us, locked in sillicon.

greesil 1y ago

It certainly looks like thinking

dgfitz 1y ago
And magic tricks look like magic. Turns out they’re not magical. I am so floored that at least half of this community, usually skeptical to a fault, evangelizes LLMs so ardently. Truly blows my mind. I’m open to them becoming more than a statistical token predictor, and I think it would be really neat to see that happen. They’re nowhere close to anything other than a next-token-predictor.
- chpatrick 1y ago
  When you type you're also producing one character at a time with some statistical distribution. That doesn't imply anything regarding your intelligence.
- BoiledCabbage 1y ago
  > I am so floored that at least half of this community, usually skeptical to a fault, evangelizes LLMs so ardently. Truly blows my mind. ... > I’m open to them becoming more than a statistical token predictor, and I think it would be really neat to see that happen I'm more shocked that so many people seem unable to come to grips with the fact that something can be a next token predictor and demonstrate intelligence. That's what blows my mind, people unable to see that something can be more than the sum of its parts. To them, if something is a token predictor clearly it can't be doing anything impressive - even while they watch it do I'm impressive things.
  - seadan83 1y ago
    > I'm more shocked that so many people seem unable to come to grips with the fact that something can be a next token predictor and demonstrate intelligence. Except LLMs have not shown much intelligence. Wisdom yes, intelligence no. LLMs are language models, not 'world' models. It's the difference of being wise vs smart. LLMs are very wise as they have effectively memorized the answer to every question humanity has written. OTOH, they are pretty dumb. LLMs don't "understand" the output they produce. > To them, if something is a token predictor clearly it can't be doing anything impressive Shifting the goal posts. Nobody said that a next token predictor can't do impressive things, but at the same time there is a big gap between impressive things and other things like "replace very software developer in the world within the next 5 years."
    - bondarchuk 1y ago
      I think what BoiledCabbage is pointing out is that the fact that it's a next-token-predictor is used as an argument for the thesis that LLMs are not intelligent, and that this is wrong, since being a next-token-predictor is compatible with being intelligent. When mikert89 says "thinking machines have been invented", dgfitz in response strongly implies that for a for thinking machines to exist, they must become "more than a statistical token predictor". Regardless of whether or not thinking machines currently exist, dgfitz argument is wrong and BoiledCabbage is right to point that out.
      - 1y ago
- tim333 1y ago
  IMO gold?
- greesil 1y ago
  Maybe thinking needs a Turing test. If nobody can tell the difference between this and actual thinking then it's actually thinking. /s, or is it?
  - sitkack 1y ago
    If I order Chinese takeout, but it gets made by a restaurant that doesn't know what Chinese food tastes like, then is that food really Chinese takeout?
    - chpatrick 1y ago
      If it tastes like great Chinese food (which is a pretty vague concept btw, it's a big country), does it matter?
    - dangus 1y ago
      Useless analogy, especially in the context of a gigantic category of fusion cuisine that is effectively franchised and adapted to local tastes. If I have never eaten a hamburger but own a McDonald’s franchise, am I making an authentic American hamburger? If I have never eaten fries before and I buy some frozen ones from Walmart, heat them up, and throw them in the trash, did I make authentic fries? Obviously the answer is yes and these questions are completely irrelevant to my sentience.
      - greesil 1y ago
        Not exactly. When "intelligence" is like your frozen Walmart fries, the analogy works a bit better. Some people are arguing that yes, you can buy some frozen intelligence from your local (internet) store.
  - dangus 1y ago
    This is like watching a Jurassic Park movie and proclaiming “if nobody can tell the difference between a real dinosaur and a CGI dinosaur…” when literally everyone in the theater can tell that the dinosaur is CGI.
- deleted 1y ago
  [deleted]
- svara 1y ago
  > I’m open to them becoming more than a statistical token predictor, and I think it would be really neat to see that happen What exactly do you mean by that? I've seen this exact comment stated many times, but I always wonder: What limitations of AI chat bots do you currently see that are due to them using next token prediction?
  - dangus 1y ago
    I feel like the logic of your question is actually inverted from reality. It’s kind of like you’re saying “prove god doesn’t exist” when it’s supposed to be “prove god exists.” If a problem isn’t documented LLMs simply have nowhere to go. It can’t really handle the knowledge boundary [1] at all, since it has no reasoning ability it just hallucinates or runs around in circles trying the same closest solution over and over. It’s awesome that they get some stuff right frequently and can work fast like a computer but it’s very obvious that there really isn’t anything in there that we would call “reasoning.” [1] https://matt.might.net/articles/phd-school-in-pictures/ https://matt.might.net/articles/phd-school-in-pictures/
    - frm88 1y ago
      Thank you for that link. So very true. (I admit, I laughed)
    - svara 1y ago
      Not at all. I don't want to address directly your claim about lack of generalization, because there's a more basic issue with the GP statement. Even though I will say, today's models do seem to generalize quite a bit better than you make it sound. But more importantly, you and GP don't mention any evidence for why that is due to specifically using next token prediction as a mechanism. Why would it not be possible for a highly generalizing model to use next token prediction for its output? That doesn't follow to me at all, which is why the GP statement reads so weird.
      - Jensson 1y ago
        > Why would it not be possible for a highly generalizing model to use next token prediction for its output? The issue is that it uses next token prediction for its training, it doesn't matter how it outputs things but it matters how its trained. As long as these models are trained to be next token predictors you will always be able to find flaws with it that are related to it being a next token predictor, so understanding that is how they work really makes them much easier to use. So since it is so easy to get the model to make errors due to it being trained to just predict tokens people argue that is proof they aren't really thinking. Like, any extremely common piece of text when altered slightly will typically still output the same follow-up as the text it has seen millions of times even though it makes no logical sense. That is due to them being next token predictors instead of reasoning machines. You might say its unfair to abuse their weaknesses as next token predictors, but then you admit that being a next token predictor interferes with their ability to reason, which was the argument you said you don't understand.

Spivak 1y ago

and they don't have to revolutionize the world to be revolutionary in our industry. it might be that the use-cases unlocked by this new technology won't move the needle in an industrial revolution sense but it's nonetheless a huge leap for computer science and the kinds of tasks that can be done with software. i don't understand people who seem to have strongly motivated reasoning to dismiss the new tech as just a token predictor or stochastic parrot. it's confusing the means with the result, it's like saying Deep Blue is just search, it's not actually playing chess, it doesn't understand the game—like that matters to people playing against it.

jurking_hoff 1y ago
[dead]
mattbuilds 1y ago
I personally don't dismiss or advocate for AI/LLMs, I just take what I actually see happening, which doesn't appear revolutionary to me. I've spent some time trying to integrate it into my workflow and I see some use cases here and there but overall it just hasn't made a huge impact for me personally. Maybe it's a skill issue but I have always been pretty effective as a dev and what it solves has never been the difficult or time consuming part of creating software. Of course I could be wrong and it will change everything, but I want to actually see some evidence of that before declaring this the most impactful technology in the last 100 years. I personally just feel like LLMs make the easy stuff easier, the medium stuff slightly more difficult and the hard stuff impossible. But I personally feel that way about a lot of technology that comes along though, so it could just be I'm missing the mark.
- hodgehog11 1y ago
  > I have always been pretty effective as a dev > LLMs make the easy stuff easier I think this is the observation that's important right now. If you're an expert that isn't doing a lot of boilerplate, LLMs don't have value to you right now. But they can acceptably automate a sizeable number of entry-level jobs. If those get flushed out, that's an issue, as not everyone is going to be a high-level expert. Long-term, the issue is we don't know where the ceiling is. Just because OpenAI is faltering doesn't mean that we've hit that ceiling yet. People talk about the scaling laws as a theoretical boundary, but it's actually the opposite. It shows that the performance curve could just keep going up even with brute force, which has never happened before in the history of statistics. We're in uncharted territory now, so there's good reason to keep an eye on it.

mvdtnz 1y ago

[flagged]

lm28469 1y ago

Bigger than internet and computers? Lmao, I don't even know if I'd place it as high as the GPS. Some people are terminally online and it really shows...

mylifeandtimes 1y ago

Wait-- are you claiming that AI is a bigger technological change than the development of computing devices and a networking infrastructure for those devices?

gitaarik 1y ago
Well, is the computer revolution bigger than the electricity revolution? They just build on each other. But it might be interpreted as the next new abstraction that causes major changes in the industry.

_ea1k 1y ago

I'm starting to learn that AI progress is just really hard to talk about. On the one hand, I completely agree with you. I've even said before, here on Hacker News, that AI is underhyped compared to the real world impact that it will have. On the other, I run into people in person that seem to think dabbing a little cursor on a project will suddenly turn everyone into 100x engineers. It just doesn't work that way at all, but good luck dealing with the hypemeisters.