ChatGPT в работе
Вот интересно написанное мнение в дискуссии (источник) о том, какие профессии сможет заменить (и сможет ли) ChatGPT. Для тех, кто не читает свободно по-английски (и не хочет перевести с помощью ChatGPT :-)): главная мысль тут, что он не справляется, когда требуется детальное понимание того, как именно работает система на нескольких уровнях. С другой стороны, общие рассуждения (необязательно банальные) и использование аналогий, включая такие, о которых вы бы сами и не подумали - его сильная сторона.
I've found that ChatGPT (4, unless otherwise specified) often understands the purpose and high-level practice of my job better than I do, but also can't do some of the simplest (to me) parts of my job. Concrete examples:
1. I had a nasty architectural problem in the application I work with [...] ChatGPT was able to suggest some frankly great changes to our process and codebase structure to alleviate that conflict.
2. I am trying to do a crash course in mechanistic interpretability for ML, and this involves reading a lot of dense, math-heavy research papers. [...] I was able to feed ChatGPT a paragraph of a research paper involving esoteric stuff about finite groups and representation theory, and it was able to explain the concepts to me[...]
3. When I was trying to understand "what happens if you literally just turn on backpropagation to train a language model on its own output, why doesn't that Just Work for solving the long-term memory problem?" I asked ChatGPT for 5 examples of things that would go wrong and search terms to look up to explain the academic research around each failure mode. And it did. And it was right, and looking up the search terms gave me a much deeper understanding than I had before.
4. On the flip side, ChatGPT is hilariously incapable of debugging stuff. For instance, when I provide it with code and a stack trace of an error, it suggests doing vaguely plausible actions that occasionally work but it kinda feels like a coincidence when they do. It honestly feels like working with a junior developer who struggles with basic concepts like "how does a for loop work".
5. I have also found that ChatGPT struggles quite a bit if I feed it a paragraph of an academic paper that makes a specific claim and ask it to come up with potential observations that would provide evidence against that claim. [...]
Specifically where I think ChatGPT falls down is in things that require a specific, gears-level understanding of how things work. What I mean by that is that sometimes, to truly understand a system, you have to be able to understand each individual part of the system, and then you have to understand how those parts fit together to determine the behavior of the system as a whole.
Where it excels is in solving problems where the strategy "look at similar problems in the past, see how those were solved, and suggest an analogous solution" works. It's really fucking amazing at analogies, and it has seen approximately every heuristic everyone has ever used in writing, so this strategy works sometimes even when you don't expect it to.
Still, "debugging stuff that is not working like the theory says it should" is a significant fraction of my job, and I suspect a significant part of many people's jobs. I don't think ChatGPT in its current form will directly replace people in those kinds of roles, and as such I don't think it would work as a drop-in replacement for most jobs. However, people who don't adapt can and probably will be left behind, as it's a pretty strong force multiplier.
I've found that ChatGPT (4, unless otherwise specified) often understands the purpose and high-level practice of my job better than I do, but also can't do some of the simplest (to me) parts of my job. Concrete examples:
1. I had a nasty architectural problem in the application I work with [...] ChatGPT was able to suggest some frankly great changes to our process and codebase structure to alleviate that conflict.
2. I am trying to do a crash course in mechanistic interpretability for ML, and this involves reading a lot of dense, math-heavy research papers. [...] I was able to feed ChatGPT a paragraph of a research paper involving esoteric stuff about finite groups and representation theory, and it was able to explain the concepts to me[...]
3. When I was trying to understand "what happens if you literally just turn on backpropagation to train a language model on its own output, why doesn't that Just Work for solving the long-term memory problem?" I asked ChatGPT for 5 examples of things that would go wrong and search terms to look up to explain the academic research around each failure mode. And it did. And it was right, and looking up the search terms gave me a much deeper understanding than I had before.
4. On the flip side, ChatGPT is hilariously incapable of debugging stuff. For instance, when I provide it with code and a stack trace of an error, it suggests doing vaguely plausible actions that occasionally work but it kinda feels like a coincidence when they do. It honestly feels like working with a junior developer who struggles with basic concepts like "how does a for loop work".
5. I have also found that ChatGPT struggles quite a bit if I feed it a paragraph of an academic paper that makes a specific claim and ask it to come up with potential observations that would provide evidence against that claim. [...]
Specifically where I think ChatGPT falls down is in things that require a specific, gears-level understanding of how things work. What I mean by that is that sometimes, to truly understand a system, you have to be able to understand each individual part of the system, and then you have to understand how those parts fit together to determine the behavior of the system as a whole.
Where it excels is in solving problems where the strategy "look at similar problems in the past, see how those were solved, and suggest an analogous solution" works. It's really fucking amazing at analogies, and it has seen approximately every heuristic everyone has ever used in writing, so this strategy works sometimes even when you don't expect it to.
Still, "debugging stuff that is not working like the theory says it should" is a significant fraction of my job, and I suspect a significant part of many people's jobs. I don't think ChatGPT in its current form will directly replace people in those kinds of roles, and as such I don't think it would work as a drop-in replacement for most jobs. However, people who don't adapt can and probably will be left behind, as it's a pretty strong force multiplier.