I would love, _love_ to know more about your data formats, your tools, what the JSON looks like, basically as much as you're willing to share. :)
For about a month now I've been working on a suite of tools for dealing with JSON specifically written for the imagined audience of "for people who like CLIs or TUIs and have to deal with PILES AND PILES of JSON and care deeply about performance".
For me, I've been writing them just because it's an "itch". I like writing high performance/efficient software, and there's a few gaps that it bugged me they existed, that I knew I could fill.
I'm having fun and will be happy when I finish, regardless, but it would be so cool if it happened to solve a problem for someone else.
> Is the actual ‘intrinsic’ vector space uncomputable? Too slow to find?
OMG yes. It's also an unsolved problem, once can approximate it. I've written several non-parametric blind arbitrary dimension DR algorithms and been obsessed with the space most of my life. If you think O(n^2) feels slow, try O(n^3)...:) For more, read about mean shift clustering, or the new hot stuff: topological data analysis/bar codes/mapper algorithm.
kinda/yes. To translate to more intuitive concepts: the matrices don't contain much variance in as many degrees of freedom as they could.
Think of a point cloud of a piece of paper floating in the wind. It would be a 3xn list of points, but "really" it's a 2d piece of paper.
Just like I can rewrite the number 27 as 333 or 8+19 or (2^3)+(2^4)+3.. Given a single matrix one can find myriad ways to rewrite it as a sequence of matrices that have the same (or similar) numeric value, but with interesting or desirable properties. :D
My favorite example (which is used in signal processing) is to take your ugly matrix and rewrite it as a set of smaller matrices where most of the elements are zero, or a power of 2.
It turns out, computers can multiply by zeros and powers of two very fast
Hi! I in _no way_ mean to detract or malign or "anything negative" the parent comment (communication is hard!!), BUT I really compliment that exact sentence. :)
My background contains signal processing, "pre-deep learning ML", systems engineering, and firmware, and that sentence jumped out at me as crystal clear in my mind, despite not knowing what HuggingFace is or PyTorch.
Correct me if I'm wrong: These huge models involve lots of weights used in large matrices. The contribution of this work is to plug in some matrix factorization and learn a lower dimensional representation, instead of a large second matrix.
Fantastic!
Also makes me wonder what other performance improvements await through proper application of established and well known Mathematics. :D
For even more peace of mind, (and only when you can afford it, obviously) try decoupling your disk purchases a bit from when you're going to need them.
When you see a good price or a sale on a particular disk, grab it add it to your own personal "prebought disk pool". When it's time to either replace a disk or spin up a whole new array, now you have the benefit of diversification across time.
Being as you're offering use of the site for free, would you be open to the idea of also offering publicly available DB dumps? There's plenty of fun projects that I can imagine doing if I had that data locally.
For about a month now I've been working on a suite of tools for dealing with JSON specifically written for the imagined audience of "for people who like CLIs or TUIs and have to deal with PILES AND PILES of JSON and care deeply about performance".
For me, I've been writing them just because it's an "itch". I like writing high performance/efficient software, and there's a few gaps that it bugged me they existed, that I knew I could fill.
I'm having fun and will be happy when I finish, regardless, but it would be so cool if it happened to solve a problem for someone else.