12 ms·

99% of humans in a particular specialization, sure. It's the 1% who become experts in that specialization who are able to advance the state of the art. But it's

by chongli 7mo ago

99% of humans in a particular specialization, sure. It's the 1% who become experts in that specialization who are able to advance the state of the art. But it's a different 1% for every area of expertise! Add it all up and you get a lot more than 1% of humans contributing to the sum of knowledge. And of course, if you don't limit yourself to "advancing the state of the art at the far frontiers of human knowledge" but allow for ordinary people to make everyday contributions in their daily lives, you get even more. Sure, much of this knowledge may not be widespread (it may be locked up within private institutions) but its impact can still be felt throughout the economy.

coldtea 7mo ago
>99% of humans in a particular specialization, sure. It's the 1% who become experts in that specialization who are able to advance the state of the art How? By also "synthesizing the data they were trained on" (their experience, education, memories, etc.).
- chongli 7mo ago
  No, that's not all we're doing. If that's all humans ever did, we'd still be living in the stone age.
  - sally_glance 7mo ago
    Can we be sure? Maybe it's just very rare for experience, education and memories to line up in exactly the way that allows synthesizing something innovative. So it requires a few billion candidates and maybe a couple of generations too.
    - chongli 7mo ago
      I want to point back to my remark about everyday people. if you don't limit yourself to "advancing the state of the art at the far frontiers of human knowledge" but allow for ordinary people to make everyday contributions in their daily lives, you get even more This isn't a throwaway comment. I do this all the time myself, at work. Everywhere I've worked, I do this. I challenge the assumptions and try to make things better. It's not a rare thing at all, it's just not revolutionary. Revolutions are rare. Perhaps only a handful of them have ever happened in any one particular field. But you simply will not ever go from Aristotelian physics to Newtonian physics to General Relativity by merely "synthesizing the data they were trained on", as the previous comment supposed. Edit: I should also say something about experimentation. You can't do it from an armchair, which is all an LLM has access to (at present). Real people learn things all the time by conducting experiments in the world and observing the results, without necessarily working as formal scientists. Babies learn a lot by experimenting, for example. This is one particular avenue of new knowledge which is entirely separate from experience, education, memories, etc. because an experiment always has the potential to contradict all of that.
      - sally_glance 7mo ago
        Experimentation leads to experience, so I feel like this was included by the parent comment. And in the case of writing software, agents are able to experiment today. They run tests, check log output, search DBs... Sure, they can't have apples fall on their heads like Newton had but they can totally observe the apple falling on someones head in a video.
        chongli 7mo ago
        Experimentation leads to experience Of course it does, but only after the fact. You don't have any experience of the result of the experiment before you perform it. Sure, they can't have apples fall on their heads like Newton had but they can totally observe the apple falling on someones head in a video I have strong doubts that LLMs have any understanding whatsoever of what's happening in images (let alone videos). The claim (I've sometimes heard) that they possess a world model and are able to interpret an image according to that model is an extremely strong one, that's strongly contradicted by the fact that they: a) continue to hallucinate in pretty glaring ways, and b) continue to mis-identify doctored (adversarial) images that no human would mis-identify (because they don't drastically alter the subject).
        sally_glance 7mo ago
        In software, they can and do perform experiments (make a change then observe the log output). I don't think they possess a "world model" or that it's worth spending too much thought on... My reasoning is more along the lines that our brains are also just [very advanced] inference machines. We also hallucinate and mis-identify images (there are image/video classification tasks where humans have lower scores). For me the most glaring difference to how humans work is the lack of online learning. If that prevents them from being able to innovate, I'm not so sure.
        chongli 7mo ago
        Software is not the world. It’s a tiny bit of what humans do. The lack of online learning is a critical fault. Much of what humans learn (such as anything based on mathematics) has a dependency tree of stuff to learn. But even mundane stuff involves a lot of dependent learning. For example, ask an LLM to write a cookbook and it can synthesize from recipes that are already out there but good luck having it invent new cooking techniques that require experimentation or invention (new heat source, new cooking utensils, etc).
  - coldtea 7mo ago
    That's begging the question though. Where's the proof we don't do exactly this? The mind as a prediction engine is one of the handful most accepted theories.
    - chongli 7mo ago
      Well, humans do experiments for one, as I explained elsewhere in the discussion. Experiments give us access to new knowledge from the world itself, which is not merely a synthesis of what we already know. Real progress in science is made by the hard collection and cataloguing of data every single day, not by armchair philosophizing.
Calazon 7mo ago
If 1% of the people in each specialization are advancers, and you add up all the specializations together, then 1% of the total number of people are advancers. Even this assumes that everyone has a specialization in which 1% of people contribute to the sum of human knowledge. I would probably challenge that. There are a lot of people in the world who do not do knowledge-oriented work at all.
- chongli 7mo ago
  You don’t need to do knowledge work to advance the state of the art. You could be working in a shoe factory and discover a better way to tie your shoes. Your math assumes each person has exactly one thing they do in life. The shoe factory worker could also be a gardener. He might not make any advancements in gardening, but his contribution means that if you add up all the fields of specialization the sum is greater than the population of humans. Take 1% of that sum and it’s greater than 1% of humans. 1% of people in a specialization is not the same as 1% of specialists. In fact, I would say it’s a much higher proportion of specialists making contributions (especially through collaboration). Oh, and don’t get caught up on the 1% number. I used it as shorthand for whatever small number it is. Maybe it’s only 10 people in some hyper-specialized field. But that doesn’t matter. Some other field may have thousands of contributors. You don’t have to be a specialist in a field to make a contribution to that field, for example: glassmakers advanced the science of astronomy by making the telescope possible.

by chongli 7mo ago

coldtea 7mo ago

>99% of humans in a particular specialization, sure. It's the 1% who become experts in that specialization who are able to advance the state of the art How? By also "synthesizing the data they were trained on" (their experience, education, memories, etc.).

chongli 7mo ago
No, that's not all we're doing. If that's all humans ever did, we'd still be living in the stone age.
- sally_glance 7mo ago
  Can we be sure? Maybe it's just very rare for experience, education and memories to line up in exactly the way that allows synthesizing something innovative. So it requires a few billion candidates and maybe a couple of generations too.
  - chongli 7mo ago
    I want to point back to my remark about everyday people. if you don't limit yourself to "advancing the state of the art at the far frontiers of human knowledge" but allow for ordinary people to make everyday contributions in their daily lives, you get even more This isn't a throwaway comment. I do this all the time myself, at work. Everywhere I've worked, I do this. I challenge the assumptions and try to make things better. It's not a rare thing at all, it's just not revolutionary. Revolutions are rare. Perhaps only a handful of them have ever happened in any one particular field. But you simply will not ever go from Aristotelian physics to Newtonian physics to General Relativity by merely "synthesizing the data they were trained on", as the previous comment supposed. Edit: I should also say something about experimentation. You can't do it from an armchair, which is all an LLM has access to (at present). Real people learn things all the time by conducting experiments in the world and observing the results, without necessarily working as formal scientists. Babies learn a lot by experimenting, for example. This is one particular avenue of new knowledge which is entirely separate from experience, education, memories, etc. because an experiment always has the potential to contradict all of that.
    - sally_glance 7mo ago
      Experimentation leads to experience, so I feel like this was included by the parent comment. And in the case of writing software, agents are able to experiment today. They run tests, check log output, search DBs... Sure, they can't have apples fall on their heads like Newton had but they can totally observe the apple falling on someones head in a video.
      - chongli 7mo ago
        Experimentation leads to experience Of course it does, but only after the fact. You don't have any experience of the result of the experiment before you perform it. Sure, they can't have apples fall on their heads like Newton had but they can totally observe the apple falling on someones head in a video I have strong doubts that LLMs have any understanding whatsoever of what's happening in images (let alone videos). The claim (I've sometimes heard) that they possess a world model and are able to interpret an image according to that model is an extremely strong one, that's strongly contradicted by the fact that they: a) continue to hallucinate in pretty glaring ways, and b) continue to mis-identify doctored (adversarial) images that no human would mis-identify (because they don't drastically alter the subject).
        sally_glance 7mo ago
        In software, they can and do perform experiments (make a change then observe the log output). I don't think they possess a "world model" or that it's worth spending too much thought on... My reasoning is more along the lines that our brains are also just [very advanced] inference machines. We also hallucinate and mis-identify images (there are image/video classification tasks where humans have lower scores). For me the most glaring difference to how humans work is the lack of online learning. If that prevents them from being able to innovate, I'm not so sure.
        chongli 7mo ago
        Software is not the world. It’s a tiny bit of what humans do. The lack of online learning is a critical fault. Much of what humans learn (such as anything based on mathematics) has a dependency tree of stuff to learn. But even mundane stuff involves a lot of dependent learning. For example, ask an LLM to write a cookbook and it can synthesize from recipes that are already out there but good luck having it invent new cooking techniques that require experimentation or invention (new heat source, new cooking utensils, etc).
- coldtea 7mo ago
  That's begging the question though. Where's the proof we don't do exactly this? The mind as a prediction engine is one of the handful most accepted theories.
  - chongli 7mo ago
    Well, humans do experiments for one, as I explained elsewhere in the discussion. Experiments give us access to new knowledge from the world itself, which is not merely a synthesis of what we already know. Real progress in science is made by the hard collection and cataloguing of data every single day, not by armchair philosophizing.

Calazon 7mo ago

If 1% of the people in each specialization are advancers, and you add up all the specializations together, then 1% of the total number of people are advancers. Even this assumes that everyone has a specialization in which 1% of people contribute to the sum of human knowledge. I would probably challenge that. There are a lot of people in the world who do not do knowledge-oriented work at all.

chongli 7mo ago
You don’t need to do knowledge work to advance the state of the art. You could be working in a shoe factory and discover a better way to tie your shoes. Your math assumes each person has exactly one thing they do in life. The shoe factory worker could also be a gardener. He might not make any advancements in gardening, but his contribution means that if you add up all the fields of specialization the sum is greater than the population of humans. Take 1% of that sum and it’s greater than 1% of humans. 1% of people in a specialization is not the same as 1% of specialists. In fact, I would say it’s a much higher proportion of specialists making contributions (especially through collaboration). Oh, and don’t get caught up on the 1% number. I used it as shorthand for whatever small number it is. Maybe it’s only 10 people in some hyper-specialized field. But that doesn’t matter. Some other field may have thousands of contributors. You don’t have to be a specialist in a field to make a contribution to that field, for example: glassmakers advanced the science of astronomy by making the telescope possible.