3 ms·

That's because you need actual logic and thought to be able to decide when to be critical and when to agree. Chatbots can't do that. They can only predict what

by Loughla 7mo ago

That's because you need actual logic and thought to be able to decide when to be critical and when to agree. Chatbots can't do that. They can only predict what comes next statistically. So, I guess you're asking if the average Internet comment agrees with you or not. I'm not sure there's much value there. Chatbots are good at tasks (make this pdf an accessible word document or sort the data by x), not decision making.

kvirani 7mo ago
I'm not convinced that "actual logic and thought" aren't just about inferring what comes next statistically based on experience.
- plagiarist 7mo ago
  Then the machines still need a more sophisticated "experience" compared to what they have currently.
- righthand 7mo ago
  Communicating is usually about inferring. I dont think token to token. And I don’t think “well statistically I could say ‘and’ next but I will say ‘also’ instead to give my speech some flash”. If I decided on swapping a word I would have made my decision long ago, not in the moment. Thought and logic are not me pouring through my brain finding a statistical path to any answer. Often I stop and say “I dont know”.
- Swizec 7mo ago
  > I'm not convinced that "actual logic and thought" aren't just about inferring what comes next statistically based on experience. Often they are the exact opposite. Entire fields of math and science talk about this. Causation vs correlation, confirmation bias, base rate fallacy, bayesian reasoning, sharp shooter fallacy, etc. All of those were developed because “inferring from experience” leads you to the wrong conclusion.
  - theptip 7mo ago
    Bayesian reasoning is just another algorithm for predicting from experience (aka your prior). I took the GP to be making a general point about the power of “next x prediction” rather than the algorithm a human would run when you say they are “inferring from experience”. (I may be assuming my own beliefs of course.) Eg even LeCun’s rejection of LLMs to build world models is still running a predictor, just in latent space (so predicting next world-state, instead of next-token). And of course, under the Predictive Processing model there is a comprehensive explanation of human cognition as hierarchical predictors. So it’s a plausible general model.
    - Swizec 7mo ago
      > under the Predictive Processing model there is a comprehensive explanation of human cognition as hierarchical predictors It’s plausible! But keep in mind humans have been explaining ourselves in terms of the current most advanced technology for centuries. We used to be kinda like clockwork, then a bit like a steam engine, then a lot like computers, and now we’re just like AI. That’s why you blow a gasket or fuse, release some steam, reboot your life, do brain dump, feel like a cog in the machine, get your wires crossed, etc
- theptip 7mo ago
  Exactly. Lots can be explained just with more abstract predictors, plus some mechanisms for stochastic rollout and memory.
- dinkumthinkum 7mo ago
  Is this just Internet smart contrarianism or a real thing? Are logic gates in a digital circuit just behaving statistically according to their experience?
- hluska 7mo ago
  You know, you might really enjoy consumer behaviour. When you get into the depths of it, you’ll end up running straight into that idea like you’re doing a 100 metre dash in a 90 metre gym. It’s quite interesting how arguably the best funded group under the psychology umbrella runs directly into this. One of my favourite examples is how heuristics will lead otherwise reasonable people to make decisions that are not in their interest.
righthand 7mo ago
I said this pretty much and got major downvotes…
- dTal 7mo ago
  Because it's an outmoded cliche that never held much philosophical weight to begin with and doesn't advance the discussion usefully. "It's a stochastic parrot" is not a useful predictor of actual LLM capabilities and never was. Last year someone posted on HN a log of GPT-5 reverse engineering some tricky assembly code, a challenge set by another commentator as an example of "something LLMs could never do". But here we are a year later still wading through people who cannot accept that LLMs can, in a meaningful sense, "compute".
  - righthand 7mo ago
    It’s entirely useful discussion because as soon as you forget that it’s not really having a conversation with you, it’s a deep dive into delusion that you’re talking to a smart robot and ignoring the fact that these smart robots were trained on a pile of mostly garbage. When I have a conversation with another human, I’m not expecting them to brute force an answer to the topic. As soon as you forget that Llms are just brute forcing token by token then people start living in fantasy land. The whole “it’s not a stochastic parrot” is just “you’re holding it wrong”.
    - layla5alive 7mo ago
      Its not that LLMs are stochastic parrots and humans are not. Its that many humans often sail through conversations stochastic parroting because they're mentally tired and "phoning it in" - so there are times when talking to the LLM, which has a higher level of knowledge, feels more fruitful on a topic than talking to a human who doesn't have the bandwidth to give you their full attention, and also lack the depth and breadth of knowledge. I can go deep on many topics with LLMs that most humans can't or won't keep up on. In the end, I'm really only talking to myself most of the time in either case, but the LLM is a more capable echo, and it doesn't tire of talking about any topic - it can dive deep into complex details, and catching its hallucinations is an exercise in itself.

by Loughla 7mo ago

kvirani 7mo ago

I'm not convinced that "actual logic and thought" aren't just about inferring what comes next statistically based on experience.

plagiarist 7mo ago
Then the machines still need a more sophisticated "experience" compared to what they have currently.
righthand 7mo ago
Communicating is usually about inferring. I dont think token to token. And I don’t think “well statistically I could say ‘and’ next but I will say ‘also’ instead to give my speech some flash”. If I decided on swapping a word I would have made my decision long ago, not in the moment. Thought and logic are not me pouring through my brain finding a statistical path to any answer. Often I stop and say “I dont know”.
Swizec 7mo ago
> I'm not convinced that "actual logic and thought" aren't just about inferring what comes next statistically based on experience. Often they are the exact opposite. Entire fields of math and science talk about this. Causation vs correlation, confirmation bias, base rate fallacy, bayesian reasoning, sharp shooter fallacy, etc. All of those were developed because “inferring from experience” leads you to the wrong conclusion.
- theptip 7mo ago
  Bayesian reasoning is just another algorithm for predicting from experience (aka your prior). I took the GP to be making a general point about the power of “next x prediction” rather than the algorithm a human would run when you say they are “inferring from experience”. (I may be assuming my own beliefs of course.) Eg even LeCun’s rejection of LLMs to build world models is still running a predictor, just in latent space (so predicting next world-state, instead of next-token). And of course, under the Predictive Processing model there is a comprehensive explanation of human cognition as hierarchical predictors. So it’s a plausible general model.
  - Swizec 7mo ago
    > under the Predictive Processing model there is a comprehensive explanation of human cognition as hierarchical predictors It’s plausible! But keep in mind humans have been explaining ourselves in terms of the current most advanced technology for centuries. We used to be kinda like clockwork, then a bit like a steam engine, then a lot like computers, and now we’re just like AI. That’s why you blow a gasket or fuse, release some steam, reboot your life, do brain dump, feel like a cog in the machine, get your wires crossed, etc
theptip 7mo ago
Exactly. Lots can be explained just with more abstract predictors, plus some mechanisms for stochastic rollout and memory.
dinkumthinkum 7mo ago
Is this just Internet smart contrarianism or a real thing? Are logic gates in a digital circuit just behaving statistically according to their experience?
hluska 7mo ago
You know, you might really enjoy consumer behaviour. When you get into the depths of it, you’ll end up running straight into that idea like you’re doing a 100 metre dash in a 90 metre gym. It’s quite interesting how arguably the best funded group under the psychology umbrella runs directly into this. One of my favourite examples is how heuristics will lead otherwise reasonable people to make decisions that are not in their interest.

righthand 7mo ago

I said this pretty much and got major downvotes…

dTal 7mo ago
Because it's an outmoded cliche that never held much philosophical weight to begin with and doesn't advance the discussion usefully. "It's a stochastic parrot" is not a useful predictor of actual LLM capabilities and never was. Last year someone posted on HN a log of GPT-5 reverse engineering some tricky assembly code, a challenge set by another commentator as an example of "something LLMs could never do". But here we are a year later still wading through people who cannot accept that LLMs can, in a meaningful sense, "compute".
- righthand 7mo ago
  It’s entirely useful discussion because as soon as you forget that it’s not really having a conversation with you, it’s a deep dive into delusion that you’re talking to a smart robot and ignoring the fact that these smart robots were trained on a pile of mostly garbage. When I have a conversation with another human, I’m not expecting them to brute force an answer to the topic. As soon as you forget that Llms are just brute forcing token by token then people start living in fantasy land. The whole “it’s not a stochastic parrot” is just “you’re holding it wrong”.
  - layla5alive 7mo ago
    Its not that LLMs are stochastic parrots and humans are not. Its that many humans often sail through conversations stochastic parroting because they're mentally tired and "phoning it in" - so there are times when talking to the LLM, which has a higher level of knowledge, feels more fruitful on a topic than talking to a human who doesn't have the bandwidth to give you their full attention, and also lack the depth and breadth of knowledge. I can go deep on many topics with LLMs that most humans can't or won't keep up on. In the end, I'm really only talking to myself most of the time in either case, but the LLM is a more capable echo, and it doesn't tire of talking about any topic - it can dive deep into complex details, and catching its hallucinations is an exercise in itself.