6 ms·

In my experience, in many cases, the so-called "first draft" (of code, content, etc.) is more just helpful for a mental warm-up. It isn't actually suitable. Th

In my experience, in many cases, the so-called "first draft" (of code, content, etc.) is more just helpful for a mental warm-up. It isn't actually suitable. The time it takes to write/code/etc. isnt in the typing, that's trivial. It's in modelling the problem (, audience) and solving it. ChatGPT isnt in the game of modelling problems and solving them, it possesses only superficial semantic characteristics of the questions posed That its answers satisfy the requirements would require ChatGPT to ask you questions (and much else besides)

ExxKA 4y ago
This
TillE 4y ago
The similar thought I had yesterday was that ChatGPT is pretty good at generating sample code that doesn't otherwise exist. It can be really useful if you treat it like that. Of course I've also had it call functions and use constants which don't exist, and fail to correct itself even after repeated prompting. So even that only goes so far.
- Shorel 4y ago
  Imagine if ChatGPT (or any other competitor) had access to a compiler and a set of tests for the program, a la HackerRank. You then give it the prompt and a lot of test cases to pass in order to consider the task complete. I can see this concept being implemented and working before the end of the year.
  - pja 4y ago
    Google / Deepmind has already done this last year. They published the paper at the end of 2022 I think. (searches) yep: https://www.deepmind.com/blog/competitive-programming-with-alphacode https://www.deepmind.com/blog/competitive-programming-with-a... It relies on test availability of good test cases to verify the code functionality: they generate many, many possible programs, throw out all the ones that aren't syntactically correct, compile the ones that are & then test them. This works reasonably well for programming competitions & the code generated will probably improve over time. The issue for "real-world" problems is that you can't verify the code without the test cases & writing good tests that ensure the code does what you want can be as much work as writing the code itself in the first place - the tests form a kind of mathematical co-domain to the code after all & only a small subset of problems are so simply defined that you can pin them down with just one or two tests.
nerpderp82 4y ago
> ChatGPT isnt in the game of modelling problems and solving them, it possesses only superficial semantic characteristics of the questions posed You can give it the datamodel and a semantic description and it will do a pretty good job of reprojecting your data. People talk about chatgpt as being a fixed thing, it isn't. ChatGPT is the Apple II of LLMs. 3-4 moore units from now every issue that people think is a "gotcha" for chatgpt will have evaporated.
- ResearchCode 4y ago
  Still waiting for those autonomous cars.
  - burnished 4y ago
    They are already here. We can haggle over error rate and incidents per million miles or what have you but that is more an argument about safety and suitability.
    - ResearchCode 4y ago
      Those must be some big gotchas, because self-driving cars have not replaced a job here, yet. Large language models show more promise for replacing non-programming office workers.
      - burnished 4y ago
        'Replaced all forms of relevant labor, or threaten to' isnt really what I am addressing or care to address. We have recognizably autonomous vehicles - that is the statement I am addressing and would ask you to, as well.
- kietay 4y ago
  In your analogy to the Apple II, is there a fundamental problem people claimed for early computers, which didn’t just boil down to “they need to be faster”? There are fundamental limitations to what an LLM can achieve.
frabcus 4y ago
You can get it to ask more questions…

ExxKA 4y ago

This

TillE 4y ago

The similar thought I had yesterday was that ChatGPT is pretty good at generating sample code that doesn't otherwise exist. It can be really useful if you treat it like that. Of course I've also had it call functions and use constants which don't exist, and fail to correct itself even after repeated prompting. So even that only goes so far.

Shorel 4y ago
Imagine if ChatGPT (or any other competitor) had access to a compiler and a set of tests for the program, a la HackerRank. You then give it the prompt and a lot of test cases to pass in order to consider the task complete. I can see this concept being implemented and working before the end of the year.
- pja 4y ago
  Google / Deepmind has already done this last year. They published the paper at the end of 2022 I think. (searches) yep: https://www.deepmind.com/blog/competitive-programming-with-alphacode https://www.deepmind.com/blog/competitive-programming-with-a... It relies on test availability of good test cases to verify the code functionality: they generate many, many possible programs, throw out all the ones that aren't syntactically correct, compile the ones that are & then test them. This works reasonably well for programming competitions & the code generated will probably improve over time. The issue for "real-world" problems is that you can't verify the code without the test cases & writing good tests that ensure the code does what you want can be as much work as writing the code itself in the first place - the tests form a kind of mathematical co-domain to the code after all & only a small subset of problems are so simply defined that you can pin them down with just one or two tests.

nerpderp82 4y ago

> ChatGPT isnt in the game of modelling problems and solving them, it possesses only superficial semantic characteristics of the questions posed You can give it the datamodel and a semantic description and it will do a pretty good job of reprojecting your data. People talk about chatgpt as being a fixed thing, it isn't. ChatGPT is the Apple II of LLMs. 3-4 moore units from now every issue that people think is a "gotcha" for chatgpt will have evaporated.

ResearchCode 4y ago
Still waiting for those autonomous cars.
- burnished 4y ago
  They are already here. We can haggle over error rate and incidents per million miles or what have you but that is more an argument about safety and suitability.
  - ResearchCode 4y ago
    Those must be some big gotchas, because self-driving cars have not replaced a job here, yet. Large language models show more promise for replacing non-programming office workers.
    - burnished 4y ago
      'Replaced all forms of relevant labor, or threaten to' isnt really what I am addressing or care to address. We have recognizably autonomous vehicles - that is the statement I am addressing and would ask you to, as well.
kietay 4y ago
In your analogy to the Apple II, is there a fundamental problem people claimed for early computers, which didn’t just boil down to “they need to be faster”? There are fundamental limitations to what an LLM can achieve.

frabcus 4y ago

You can get it to ask more questions…