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If the "godlike AI" could find bugs before you wrote the code, it may as well just write the code instead of you.

by paxy 9y ago

wavefunction 9y ago
It might be interesting to apply machine learning to already written code, correlating common mistakes to specific developers so that the IDE might warn the developer that they're entering some area or process where they tend to make mistakes.
- gruez 9y ago
  the problem with that is you get an opaque metric that's not very helpful, see: https://news.ycombinator.com/item?id=16569767 https://news.ycombinator.com/item?id=16569767
lou1306 9y ago
I mean, probably many elementary code smells (e.g. those related to null references) just pop up over and over again in a sufficiently large code base, so an AI could reasonably be trained detect them and thus prevent some of the bugs that arise from them. But for application-level bugs, we're SOL... And luckily so, otherwise we would be jobless in a few years or so.
- RangerScience 9y ago
  > And luckily so, otherwise we would be jobless in a few years or so. I don't think so. You know those painful conversations with people who "have a great idea", but can't actually make it? It's not because they don't have technical skills (although they don't) - it's because they're not trained in thinking to the level of detail that implementation actually requires. Someone needs to "program the AI" (whatever that ends up meaning). That'll still be us, even if it doesn't require any code, because at some point what code actually is telling something what you want it to do. It's "the same" leap as from machine code to compilers, domain-specific languages, garbage collection, etc. You describe what you want to happen at some level of abstraction, and something interprets that to actually make it happen. The level of detail you, as the programmer, have to directly describe goes down over time, but you still deal with far more details than most other people.
SatvikBeri 9y ago
An analogy here is NP problems - it might be a lot easier to detect bugs than to generate bug-free code. Compilers actually do this on a regular basis, detecting bugs like typos and type errors.
- eftychis 9y ago
  I think the joke here is the implication the AI can guess your code. But yeah it would be hilarious if there was a complexity class on predicting what the problem solver is going to write.

If the "godlike AI" could find bugs before you wrote the code, it may as well just write the code instead of you.

by paxy 9y ago

If the "godlike AI" could find bugs before you wrote the code, it may as well just write the code instead of you.

It might be interesting to apply machine learning to already written code, correlating common mistakes to specific developers so that the IDE might warn the developer that they're entering some area or process where they tend to make mistakes.

gruez 9y ago
the problem with that is you get an opaque metric that's not very helpful, see: https://news.ycombinator.com/item?id=16569767 https://news.ycombinator.com/item?id=16569767

lou1306 9y ago

I mean, probably many elementary code smells (e.g. those related to null references) just pop up over and over again in a sufficiently large code base, so an AI could reasonably be trained detect them and thus prevent some of the bugs that arise from them. But for application-level bugs, we're SOL... And luckily so, otherwise we would be jobless in a few years or so.

RangerScience 9y ago
> And luckily so, otherwise we would be jobless in a few years or so. I don't think so. You know those painful conversations with people who "have a great idea", but can't actually make it? It's not because they don't have technical skills (although they don't) - it's because they're not trained in thinking to the level of detail that implementation actually requires. Someone needs to "program the AI" (whatever that ends up meaning). That'll still be us, even if it doesn't require any code, because at some point what code actually is telling something what you want it to do. It's "the same" leap as from machine code to compilers, domain-specific languages, garbage collection, etc. You describe what you want to happen at some level of abstraction, and something interprets that to actually make it happen. The level of detail you, as the programmer, have to directly describe goes down over time, but you still deal with far more details than most other people.

SatvikBeri 9y ago

An analogy here is NP problems - it might be a lot easier to detect bugs than to generate bug-free code. Compilers actually do this on a regular basis, detecting bugs like typos and type errors.

eftychis 9y ago
I think the joke here is the implication the AI can guess your code. But yeah it would be hilarious if there was a complexity class on predicting what the problem solver is going to write.