5 ms·

By AI?

Symmetry 4y ago
Yes >Prompt: Someone said "Models are still expensive to run, hard to use, and frequently wrong" Does this also apply to human worker? >GPT4: This statement, while referring to AI models, can also apply to human workers in certain contexts. Here's a breakdown of each aspect mentioned: > Expensive to run: Human workers may have higher costs associated with hiring, salaries, benefits, and overhead expenses. However, the costs of human workers can be justified in many cases due to their adaptability, creativity, and ability to learn. > Hard to use: Human workers can be more difficult to manage compared to AI models, due to factors like communication, collaboration, and personal differences. However, humans are capable of adapting to new situations and understanding complex, nuanced scenarios. > Frequently wrong: Humans, like AI models, are not infallible and can make mistakes or errors in judgment. However, humans possess the ability to learn from their mistakes, improve over time, and apply critical thinking to avoid making the same errors in the future. > So, while there are similarities between the statement's implications for AI models and human workers, it is important to remember that both have their unique strengths and weaknesses. The best approach often involves combining the capabilities of AI and human workers to achieve optimal results.
- danielmarkbruce 4y ago
  Better than the vague explanation I'd have come up with to support my comment.
  - LesZedCB 4y ago
    ok, i guess this isn't something we are supposed to admit, but there are many things i have learned over the years which have been distilled to thought-bites, right? i often want to comment just short things, slogans almost. these AI have been invaluable in beefing up my slogans into longer statements with the un-distilled facts laid out in bullet points. it's pretty helpful as an argument de-compression tool. but that has pretty serious epistemological concerns. and to the people who are concerned about that - well i think that's funny... maybe take a walk down the science of how poor memory really is. i guess i just have a very attenuated view of human (including my own) rationality. it's waaaaay more inflated for the average human than we're willing to admit. i made a comment early on in December about the oncoming epistemological crisis and damn has it been really fun to watch unfold the last few months.
    - luckylion 4y ago
      An advanced specialized Model could probably create fleshed out arguments from your thought-bites and subtly manipulate you by weaving other positions you don't/didn't have into the argument. "You're right, because xyz is correct and that makes your argument correct", making you more likely to accept xyz as correct, because we like being right and if accepting xyz makes you right in this very moment, that's a small price to pay. it feels like that would require much more sophistication, but then again who hasn't been amazed how intelligent ChatGPT & friends feel?
      - LesZedCB 4y ago
        the RLHF has indeed made them quite sycophantic. i don't believe in any of the 'latent space wario' stuff, but i really enjoy using it explicitly to get clarification and explanation from opposing viewpoints. i would love to see some experiment where a debate is held/moderated by an LLM which can help find common ground in highly contentious viewpoints. the post-mortem from each side would be a fascinating read.
- mirekrusin 4y ago
  Why people arguing agains AI importance are using some cherry picked examples from currently available models while being blind to rate it improves? It's like saying wikipedia is shit because it currently has only 50 articles at some point in the past.
  - notahacker 4y ago
    > It's like saying wikipedia is shit because it currently has only 50 articles at some point in the past. On the other hand, the people drawing inferences from the exponential curve of Wikipedia's editor base growth about its potential to be a resource of unmatched accuracy were even more wrong, and it hit its quality ceiling pretty early...
    - mirekrusin 4y ago
      You don't need always increasing editor base - you need it to be above sustainability threshold.
      - notahacker 4y ago
        Well Wikipedia is both clearly above the sustainability threshold and failed to use its critical mass of editors to exponentially improve its accuracy as opposed to creating more maintenance tasks and arguments about which version is better. Does this sound like a plausible future for LLMs once the low hanging fruit is picked off? I'd say yes. Certainly anyone predicting that the exponential growth of Wikipedia would replace actual human researchers would have been miles off, and not because people stopped trying to improve it...
        mirekrusin 4y ago
        Are you seriously saying wikipedia was a failed project? Unlike wikipedia, with AI there is a threshold where it can start improving itself entering self improvement loop. Similar to how computers can improve next generations of computers (with a lot of human effort) AI can improve AI at some point (with minimal or no human effort).

By AI?

Yes >Prompt: Someone said "Models are still expensive to run, hard to use, and frequently wrong" Does this also apply to human worker? >GPT4: This statement, while referring to AI models, can also apply to human workers in certain contexts. Here's a breakdown of each aspect mentioned: > Expensive to run: Human workers may have higher costs associated with hiring, salaries, benefits, and overhead expenses. However, the costs of human workers can be justified in many cases due to their adaptability, creativity, and ability to learn. > Hard to use: Human workers can be more difficult to manage compared to AI models, due to factors like communication, collaboration, and personal differences. However, humans are capable of adapting to new situations and understanding complex, nuanced scenarios. > Frequently wrong: Humans, like AI models, are not infallible and can make mistakes or errors in judgment. However, humans possess the ability to learn from their mistakes, improve over time, and apply critical thinking to avoid making the same errors in the future. > So, while there are similarities between the statement's implications for AI models and human workers, it is important to remember that both have their unique strengths and weaknesses. The best approach often involves combining the capabilities of AI and human workers to achieve optimal results.

danielmarkbruce 4y ago
Better than the vague explanation I'd have come up with to support my comment.
- LesZedCB 4y ago
  ok, i guess this isn't something we are supposed to admit, but there are many things i have learned over the years which have been distilled to thought-bites, right? i often want to comment just short things, slogans almost. these AI have been invaluable in beefing up my slogans into longer statements with the un-distilled facts laid out in bullet points. it's pretty helpful as an argument de-compression tool. but that has pretty serious epistemological concerns. and to the people who are concerned about that - well i think that's funny... maybe take a walk down the science of how poor memory really is. i guess i just have a very attenuated view of human (including my own) rationality. it's waaaaay more inflated for the average human than we're willing to admit. i made a comment early on in December about the oncoming epistemological crisis and damn has it been really fun to watch unfold the last few months.
  - luckylion 4y ago
    An advanced specialized Model could probably create fleshed out arguments from your thought-bites and subtly manipulate you by weaving other positions you don't/didn't have into the argument. "You're right, because xyz is correct and that makes your argument correct", making you more likely to accept xyz as correct, because we like being right and if accepting xyz makes you right in this very moment, that's a small price to pay. it feels like that would require much more sophistication, but then again who hasn't been amazed how intelligent ChatGPT & friends feel?
    - LesZedCB 4y ago
      the RLHF has indeed made them quite sycophantic. i don't believe in any of the 'latent space wario' stuff, but i really enjoy using it explicitly to get clarification and explanation from opposing viewpoints. i would love to see some experiment where a debate is held/moderated by an LLM which can help find common ground in highly contentious viewpoints. the post-mortem from each side would be a fascinating read.
mirekrusin 4y ago
Why people arguing agains AI importance are using some cherry picked examples from currently available models while being blind to rate it improves? It's like saying wikipedia is shit because it currently has only 50 articles at some point in the past.
- notahacker 4y ago
  > It's like saying wikipedia is shit because it currently has only 50 articles at some point in the past. On the other hand, the people drawing inferences from the exponential curve of Wikipedia's editor base growth about its potential to be a resource of unmatched accuracy were even more wrong, and it hit its quality ceiling pretty early...
  - mirekrusin 4y ago
    You don't need always increasing editor base - you need it to be above sustainability threshold.
    - notahacker 4y ago
      Well Wikipedia is both clearly above the sustainability threshold and failed to use its critical mass of editors to exponentially improve its accuracy as opposed to creating more maintenance tasks and arguments about which version is better. Does this sound like a plausible future for LLMs once the low hanging fruit is picked off? I'd say yes. Certainly anyone predicting that the exponential growth of Wikipedia would replace actual human researchers would have been miles off, and not because people stopped trying to improve it...
      - mirekrusin 4y ago
        Are you seriously saying wikipedia was a failed project? Unlike wikipedia, with AI there is a threshold where it can start improving itself entering self improvement loop. Similar to how computers can improve next generations of computers (with a lot of human effort) AI can improve AI at some point (with minimal or no human effort).