6 ms·

Why aren’t you thinking rather that instead of talking to you, “they” would already be talking to the LLM (likely trained on your code, among other data)—while

Why aren’t you thinking rather that instead of talking to you, “they” would already be talking to the LLM (likely trained on your code, among other data)—while you get 0 total billable workload in the first place?

slfnflctd 4y ago
My intuition here is that it's because people don't always say what they mean, or know how to describe what they want. I've been working on a database migration recently, and I look forward to the rare moments when I get to write queries and analyze actual data. The vast majority of my billable hours are spent trying to tease out the client's needs by going over the same ground multiple times, because their answers keep changing and are often unclear. It takes a lot of processing to figure out an implementation for someone who will straight up describe their requirements incorrectly. Especially when a higher-ranking person comes back from vacation and says "no, everything you nailed down in the last two weeks is completely wrong". I don't think any of the current LLMs are going to handle these types of very common situations better than an experienced human any time soon. It's like that last 1% of self driving which may actually require AGI. No one can say for sure because it's not cracked yet. I think most of us will continue to have job security for quite a while.
- anileated 4y ago
  > Especially when a higher-ranking person comes back from vacation and says "no, everything you nailed down in the last two weeks is completely wrong". Yes, and at some point this high-ranking person is fed up with this now-inefficient use of time and money enough that they will just sort this out using an LLM tuned to handle this situation better if not today then tomorrow. Maybe they will pay someone to coach them for a week how to “talk” to LLM, but other than that the one who gets paid in the end is OAI/MS.
  - mejutoco 4y ago
    Imagine how angry this hypothetical person will be when they get the same problem from the LLM, after all those extra steps.
    - anileated 4y ago
      Imagine an LLM tuned to eliminate misunderstanding and ask why at least 5 levels deep… Without fearing to irritate the boss or to create an impression of being not smart, both possibly harmful for human career but irrelevant to unthinking software tool.
      - disgruntledphd2 4y ago
        I too like science fiction. People keep acting like it will be easy to bolt on things like eliminate misunderstandings onto LLMs and quite frankly I would be incredibly surprised if that happens any time soon.
        anileated 4y ago
        Eliminating misunderstanding comes down to willingness to ask more questions if you have low confidence. The main reason this doesn’t happen is subordinates afraid to look stupid or lose jobs. None are concerns to an unthinking machine.
shagie 4y ago
The issue being that neither they, nor the LLM has the proper model for the problem domain and so don't ask the right questions when trying to extract business requirements. Additionally, this is "stateless" to an extent. There's no architectural plan for how it should work when you have an LLM do it. "We're using X now but there are plans to switch to Y in some number of months." This could lead to making an abstraction layer for X and Y so that when the switchover happens there is less work to be done - but that requires forward looking design. If "they" only describe the happy path, there is no one to ask about all the unhappy paths, edge cases and corner cases where the naive implementation of the problem description will fail. Hypothetically, yea, "they" could be trained to think through every possible way the generated code could go wrong and describe how the code should work in that situation in a way that isn't contradictory... but that remains an unsolved problem that has nagged developers for decades. Switching to an LLM doesn't resolve that problem.
- anileated 4y ago
  You don’t need to have a model if you are a sufficiently advanced autocomplete.

slfnflctd 4y ago

My intuition here is that it's because people don't always say what they mean, or know how to describe what they want. I've been working on a database migration recently, and I look forward to the rare moments when I get to write queries and analyze actual data. The vast majority of my billable hours are spent trying to tease out the client's needs by going over the same ground multiple times, because their answers keep changing and are often unclear. It takes a lot of processing to figure out an implementation for someone who will straight up describe their requirements incorrectly. Especially when a higher-ranking person comes back from vacation and says "no, everything you nailed down in the last two weeks is completely wrong". I don't think any of the current LLMs are going to handle these types of very common situations better than an experienced human any time soon. It's like that last 1% of self driving which may actually require AGI. No one can say for sure because it's not cracked yet. I think most of us will continue to have job security for quite a while.

anileated 4y ago
> Especially when a higher-ranking person comes back from vacation and says "no, everything you nailed down in the last two weeks is completely wrong". Yes, and at some point this high-ranking person is fed up with this now-inefficient use of time and money enough that they will just sort this out using an LLM tuned to handle this situation better if not today then tomorrow. Maybe they will pay someone to coach them for a week how to “talk” to LLM, but other than that the one who gets paid in the end is OAI/MS.
- mejutoco 4y ago
  Imagine how angry this hypothetical person will be when they get the same problem from the LLM, after all those extra steps.
  - anileated 4y ago
    Imagine an LLM tuned to eliminate misunderstanding and ask why at least 5 levels deep… Without fearing to irritate the boss or to create an impression of being not smart, both possibly harmful for human career but irrelevant to unthinking software tool.
    - disgruntledphd2 4y ago
      I too like science fiction. People keep acting like it will be easy to bolt on things like eliminate misunderstandings onto LLMs and quite frankly I would be incredibly surprised if that happens any time soon.
      - anileated 4y ago
        Eliminating misunderstanding comes down to willingness to ask more questions if you have low confidence. The main reason this doesn’t happen is subordinates afraid to look stupid or lose jobs. None are concerns to an unthinking machine.

shagie 4y ago

The issue being that neither they, nor the LLM has the proper model for the problem domain and so don't ask the right questions when trying to extract business requirements. Additionally, this is "stateless" to an extent. There's no architectural plan for how it should work when you have an LLM do it. "We're using X now but there are plans to switch to Y in some number of months." This could lead to making an abstraction layer for X and Y so that when the switchover happens there is less work to be done - but that requires forward looking design. If "they" only describe the happy path, there is no one to ask about all the unhappy paths, edge cases and corner cases where the naive implementation of the problem description will fail. Hypothetically, yea, "they" could be trained to think through every possible way the generated code could go wrong and describe how the code should work in that situation in a way that isn't contradictory... but that remains an unsolved problem that has nagged developers for decades. Switching to an LLM doesn't resolve that problem.

anileated 4y ago
You don’t need to have a model if you are a sufficiently advanced autocomplete.