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Another way to look at it is that it doesnt (afaik) have externsl context, so there are severe limits on what it could possibly infer from some code. Like you s

Another way to look at it is that it doesnt (afaik) have externsl context, so there are severe limits on what it could possibly infer from some code. Like you say, if something unusual is being done because of a library, or business rules or something, "AI" cannot take this into account. There may be some cases where something non-obvious can be distilled out of the code, though I agree that mostly the stuff you can infer without context is mostly self evident from the code anyway Edit: just thinking, the canonical example would be something like the fast inverse square root from quake. Is it going to summarize or is it going to tell you i = 0x5f3759df - (i >> 1); // Shift i right by one and subtract it from 0x5f... (It would be cool if it does work here, even if it does, when someone makes up a new thing like this, it couldn't possibly comprehend why it's being done)

Timpy 4y ago
Fortunately for me, at my current job I don't see a lot of code that makes me say "what the hell is this even trying to do?" The most useful comments are the ones explaining limitations and why this implementation was chosen, or business rules that wouldn't be apparent in the code.
- Izkata 4y ago
  Summarized by the common advice "comments should explain the why, not the what/how".
dogcomplex 4y ago
Seeing as how its knowledge base is pulled from similar code pulled from the internet, I'd find it very likely to get the reference and interpret that as the quake fast inverse square root. Same with general context/library stuff - though obviously that's conditional on the quality of its training data. e.g. it would probably "understand" common devops/organization/OS/library stuff even if it's not part of the language it's presumably reading - just because other users probably left comments on those lines similarly - but it's not gonna necessarily understand your application-specific business logic beyond what's actually happening. Would need some very specific examples though (by definition lol). Even dumb stuff like interpreting "make the div spin around" from some CSS/JS would probably work, as someone somewhere probably coded that similarly.
SanderNL 4y ago
GPT3 knows this is the fast inverse square root. Don't know about codex though, guess it does too.

Timpy 4y ago

Fortunately for me, at my current job I don't see a lot of code that makes me say "what the hell is this even trying to do?" The most useful comments are the ones explaining limitations and why this implementation was chosen, or business rules that wouldn't be apparent in the code.

Izkata 4y ago
Summarized by the common advice "comments should explain the why, not the what/how".

dogcomplex 4y ago

Seeing as how its knowledge base is pulled from similar code pulled from the internet, I'd find it very likely to get the reference and interpret that as the quake fast inverse square root. Same with general context/library stuff - though obviously that's conditional on the quality of its training data. e.g. it would probably "understand" common devops/organization/OS/library stuff even if it's not part of the language it's presumably reading - just because other users probably left comments on those lines similarly - but it's not gonna necessarily understand your application-specific business logic beyond what's actually happening. Would need some very specific examples though (by definition lol). Even dumb stuff like interpreting "make the div spin around" from some CSS/JS would probably work, as someone somewhere probably coded that similarly.

SanderNL 4y ago

GPT3 knows this is the fast inverse square root. Don't know about codex though, guess it does too.