4 ms·

I take issue with this. Typically issues arise because they are novel and are unforeseen. If we did see these issues beforehand they'd be fixed! LLMs by defi

I take issue with this. Typically issues arise because they are novel and are unforeseen. If we did see these issues beforehand they'd be fixed! LLMs by definition are trained by example, so I fail to see how finetuning LLMs on things that have already happened to be helpful for determining the root cause of a novel issue. LLMs seem to lack systemic modelling that humans do. I can see LLMs being practical for this if it is shown that LLMs are capable of modelling scenarios outside of their dataset, but thus far none such examples exist.

reissbaker 2y ago
During my time taking on-call pager rotations at fairly large engineering organizations, I'd say that a distressingly large number of incidents happened for fairly standard reasons ("didn't write tests for this case" + "deployed" + "insufficient monitoring," with things like incorrect concurrency assumptions around DB access, or memory leaks in application code, or insufficient rate limiting / circuitbreaking causing cascading failures being fairly common passengers). In fact, it's actually pretty hard for me to come up with an issue that wasn't basically a fairly common programming error combined with some relatively common infrastructure, build, test, and/or observability problem. Sometimes with some common bureaucratic human problems thrown into the mix too, i.e. "no one owns this service's uptime."
- Infinity315 2y ago
  I think we're at an epistemic impasse here. At what point would/could you be convinced that LLMs are incapable or unsuited here? If LLMs were successfully deployed in a production environment is the day I bite my tongue. What about you? I'm not even sure that LLMs are even capable of solving standard bugs see: [1]. Hallucination seems to be a significant hurdle and any time spent validating the fixes of an LLM is wasted when it could be spent tackling the bug head on. The amount of energy spent espousing garbage requires an order of magnitude more effort to invalidate. [1]. https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-for-intelligence/ https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-f...
  - exe34 2y ago
    > If LLMs were successfully deployed in a production environment is the day I bite my tongue. This shows so much faith in management!
    - Infinity315 2y ago
      Alright, fine. Maybe you don't have faith in management, but perhaps you do have faith in the open market and capitalism. Feel free to point out any error in my logic: There are huge financial incentives--tens if not hundreds of billions of dollars--for developing an LLM which can solve novel bugs. So surely there exists AI companies developing an LLM capable of doing so. If an LLM capable of solving novel bugs exists, AI companies would rush to showing it off to capture tonnes of VC money. AI companies could show off their fancy bug-fixing LLM by closing issues on public Github repos using said LLMs. No such mythical LLM exists. We are thus left with two choices: 1. My logic is flawed or there is an alternative possibility I haven't considered. 2. The LLM capable of doing what OP asserts doesn't exist and can't be made, despite their assertion that it is trivial to fine tune and put into application.
      - dambi0 2y ago
        Even LLMs can see the false dichotomy here
        Infinity315 2y ago
        Then it should be trivial to point out the error. So do it.
        dambi0 2y ago
        Perhaps there are more lucrative applications where LLMs can be applied
        Infinity315 2y ago

reissbaker 2y ago

During my time taking on-call pager rotations at fairly large engineering organizations, I'd say that a distressingly large number of incidents happened for fairly standard reasons ("didn't write tests for this case" + "deployed" + "insufficient monitoring," with things like incorrect concurrency assumptions around DB access, or memory leaks in application code, or insufficient rate limiting / circuitbreaking causing cascading failures being fairly common passengers). In fact, it's actually pretty hard for me to come up with an issue that wasn't basically a fairly common programming error combined with some relatively common infrastructure, build, test, and/or observability problem. Sometimes with some common bureaucratic human problems thrown into the mix too, i.e. "no one owns this service's uptime."

Infinity315 2y ago
I think we're at an epistemic impasse here. At what point would/could you be convinced that LLMs are incapable or unsuited here? If LLMs were successfully deployed in a production environment is the day I bite my tongue. What about you? I'm not even sure that LLMs are even capable of solving standard bugs see: [1]. Hallucination seems to be a significant hurdle and any time spent validating the fixes of an LLM is wasted when it could be spent tackling the bug head on. The amount of energy spent espousing garbage requires an order of magnitude more effort to invalidate. [1]. https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-for-intelligence/ https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-f...
- exe34 2y ago
  > If LLMs were successfully deployed in a production environment is the day I bite my tongue. This shows so much faith in management!
  - Infinity315 2y ago
    Alright, fine. Maybe you don't have faith in management, but perhaps you do have faith in the open market and capitalism. Feel free to point out any error in my logic: There are huge financial incentives--tens if not hundreds of billions of dollars--for developing an LLM which can solve novel bugs. So surely there exists AI companies developing an LLM capable of doing so. If an LLM capable of solving novel bugs exists, AI companies would rush to showing it off to capture tonnes of VC money. AI companies could show off their fancy bug-fixing LLM by closing issues on public Github repos using said LLMs. No such mythical LLM exists. We are thus left with two choices: 1. My logic is flawed or there is an alternative possibility I haven't considered. 2. The LLM capable of doing what OP asserts doesn't exist and can't be made, despite their assertion that it is trivial to fine tune and put into application.
    - dambi0 2y ago
      Even LLMs can see the false dichotomy here
      - Infinity315 2y ago
        Then it should be trivial to point out the error. So do it.
        dambi0 2y ago
        Perhaps there are more lucrative applications where LLMs can be applied
        Infinity315 2y ago