1) verify identical query results
2) run repeatedly to get average, worst, best, etc duration of runs
Sped up so many legacy things that none of us were ever going to bother with.
Is the harness for the AI set up with any sort of instructions to generally prefer broadly-applicable first-principals query performance analysis over unintuitive results that may be local maxima due to certain things specific to that env?
Even with humans I've had to unwind "optimizations" before that worked great for low-volume envs by taking advantage of 'be inefficient in the small scale with memory to save CPU and wall clock time' or such in a way that caused pain deployed.
Source: C. Northcote Parkinson, "Parkinson's Law and Other Studies in Administration" (1957)
I’m assuming he’s using it to mean “cruft” or “low value features” but maybe there’s some meaning I’m missing.
I originally heard it in the context of picking paint color for the bike shed, which is probably more on point for software engineers, most of whom would not be involved in any discussion around building a nuclear reactor.
Can only assume english might not be your first language.
Thankfully until this thread I’d never seen anyone use the term this way.
> Can only assume english might not be your first language.
This not-subtle insult does not add anything here.
An insult would suggest it's also related to autism.
People will recognize a glimmer of something they can attach to, prompt and get a few pages of junk about this narrow topic, and then contribute it in a way that further reduces the signal-noise ratio of the discussion or project.
Like, dude, we have the same tools. We can get the same slop from the tap at any time.