Earlier quoted context omitted.
If you can't explain something in simple terms, you don't understand it well enough
Some ideas are too complex to explain accurately in simple terms. You can give someone a simple explanation of quantum chromodynamics and have them walk away feeling like they learned something, but only by glossing over or misrepresenting critical details. You’d basically just be lying to them.
New sphere-packing record stems from an unexpected source
31–40 of 226 posts
Re: New sphere-packing record stems from an unexpected source
#32Re: New sphere-packing record stems from an unexpected source
#33Neat. I spent a month trying to use sphere packing approaches for a better compression algorithm (I had a large amount of vectors, they were grouped through clustering). Turned out that theoretical approaches only really work for uniform data and not any sort of real-world data. EDIT: groped -> grouped
I'm sure you've already explored this, but is there some precompression operation that you could do to the vectors such that they're no longer sparse, and therefore relatively uniform?
Re: New sphere-packing record stems from an unexpected source
#34Earlier quoted context omitted.
I've found it's best to explain my job using unintelligible jargon. There are three choices, really: You can give a quick explanation in terms they understand, which makes your job sound easy and makes them wonder how anybody gets paid to do it. You can explain what you do and why it's important in terms they understand, but it'll take so long they'll get bored and wish they hadn't asked. Or you can give a quick expl…
If you can't explain something in simple terms, you don't understand it well enough
Re: New sphere-packing record stems from an unexpected source
#35Earlier quoted context omitted.
I've found it's best to explain my job using unintelligible jargon. There are three choices, really: You can give a quick explanation in terms they understand, which makes your job sound easy and makes them wonder how anybody gets paid to do it. You can explain what you do and why it's important in terms they understand, but it'll take so long they'll get bored and wish they hadn't asked. Or you can give a quick expl…
If you can't explain something in simple terms, you don't understand it well enough
Re: New sphere-packing record stems from an unexpected source
#36Re: New sphere-packing record stems from an unexpected source
#37I have trouble explaining to my parents how my job is a real thing. I can only imagine trying to explain ‘I study shapes, but only ones that don’t jut inwards’.
Re: New sphere-packing record stems from an unexpected source
#38Earlier quoted context omitted.
Thereby minimizing how often anyone asks you - which makes that the best long-term option?
That would only work if you were getting repeat inquiries from the same person. Otherwise it's just the longest possible option for each new inquiry. I always opt for excruciating detail because it's what I enjoy the most.
Sounds like none of the people you answered, in excruciating detail, cared to warn other people about what would happen if they asked you.
Re: New sphere-packing record stems from an unexpected source
#39I have trouble explaining to my parents how my job is a real thing. I can only imagine trying to explain ‘I study shapes, but only ones that don’t jut inwards’.
I've found it's best to explain my job using unintelligible jargon. There are three choices, really: You can give a quick explanation in terms they understand, which makes your job sound easy and makes them wonder how anybody gets paid to do it. You can explain what you do and why it's important in terms they understand, but it'll take so long they'll get bored and wish they hadn't asked. Or you can give a quick expl…
"I teach computers what sounds different aminals make."
Re: New sphere-packing record stems from an unexpected source
#40Earlier quoted context omitted.
I'm sure you've already explored this, but is there some precompression operation that you could do to the vectors such that they're no longer sparse, and therefore relatively uniform?
They weren't sparse, they were dense but the "density" was quite non-uniform (think typical learned ML vectors). Not too far from an N-dimensional gaussian (I ended up reading research on quantizing Gaussian distributions, but that didn't help either as we didn't have a perfectly gaussian thing).
Here's some work on low-latency neural compression that you might find interesting: https://arxiv.org/abs/2107.03312