claytonjy

7 ms·

61.
by claytonjy 2y ago
do we know roughly how common use of this or similar technologies are in various markets? I was under the impression this was quite common, though I have no evidence and would love to be shown otherwise!
62.
by claytonjy 2y ago
Looks interesting, but I'm having a hard time understanding what this does that isn't covered by the ruff rules checking for uses of private functions or classes. It seems you can define an extra level of who's allowed to imp
63.
by claytonjy 2y ago
Is there any reason to still use Rye, now? looks like this release adds all the things I would have missed from Rye, but I don't think I use all of Rye's features
64.
by claytonjy 2y ago
That's wild, I usually offer candidates closer to 15 minutes (out of an hour interview), and have insisted upon the same when interviewing. Been doing both for a decade, mostly startups.
65.
by claytonjy 2y ago
I used OSMRouter maybe 7 or 8 years ago to process a couple billion routes and it was about as simple as GP described. Just need Docker and an index file. the US one was massive so I kept needing a bigger VM just to load it, but once I did
66.
by claytonjy 2y ago
What installation issues have you had with Numpy lately? Python packaging is a mess, but compared to issues with Torch or Nvidia stuff, Numpy has been a cakewalk whether using pip, conda, poetry, rye, etc.
67.
by claytonjy 2y ago
My first thought was CI providers, where we often have to specify a "service" to allow `docker build`. I don't know much about the internals there; would this bug allow me to do bad stuff on shared CI runners?
68.
by claytonjy 2y ago
as sibling mentioned the 188GB is for a pair . The memory bump is from enabling the 6th block of memory that is otherwise disabled on H100s. I assume an "NVL box" is still 8 total GPUs, so more like 8x H100 NVL (94GB, 800W)
69.
by claytonjy 2y ago
Slurm is definitely still dominant, but OpenAI has been using k8s for training for many years now¹, and there are various ways to run slurm on top of Kubernetes, including the recent SUNK from coreweave² at my company we use slurm "dir
70.
by claytonjy 2y ago
What did you move to instead?
71.
by claytonjy 2y ago
Would love to hear more about the scale issues you saw. How many workflows or actions was too many? which components started breaking down, what were their failure modes?
72.
by claytonjy 2y ago
That's fair, but they stopped saying it about CV models in 2012. We've been saying this about foundational forecasting models since...2019 at least, probably earlier. But it is a harder problem!
73.
by claytonjy 2y ago
if I knew it was good, why would I tell you that?
74.
by claytonjy 2y ago
And like all deep learning forecasting models thus far, it makes for a nice paper but is not worth anyone using for a real problem. Much slower than the classical methods it fails to beat.
75.
by claytonjy 2y ago
An issue we've had when looking into some of these is that, they provide a layer of software abstraction we're not looking for. I don't want to use some providers bespoke library to wrap my model code; I just want to use NVID
76.
by claytonjy 2y ago
The middlemen you're talking about do two things: buy lots of reserved compute on the hyperscalers, and then pit the hyperscalers against eachother to get better pricing. If you're reserving thousands of GPUs from the same hypersc
77.
by claytonjy 2y ago
What are folk's experiences with alternative cloud GPUs for inference ? If you're doing a lot of model training, buying GPUs or long-term reservations of GPUs is a no-brainer. But when it comes to inference, latency matters and i
78.
by claytonjy 2y ago
I'm somewhat new to helm, after a year I feel like I'm pretty good at it, but struggle to teach other ML folks what I've learned the hard way over the last year. Some of that is helm, plenty of it is Kubernetes. Most of our c
79.
by claytonjy 2y ago
Has anyone successfully implemented Backstage at their company? How'd it go? We're looking at it for an internal platform serving ~50 engineers today, spanning mobile, backend, enterprise integrations, and ML teams. The hope is it
80.
by claytonjy 2y ago
to reduce the chances of GitHub taking it down, perhaps? not sure it'll help though
81.
by claytonjy 3y ago
And ruff has a bunch of the pyupgrade rules included, which has made it easy for me to start catching things like using List instead of list in py3.10+.
82.
by claytonjy 3y ago
Yes, this is a big part of what makes this approach tolerable. In VSCode, the on-hover tooltip includes a link the ruff rule page with this information, so there's no searching needed. I've come to rely on that so much, it's
83.
by claytonjy 3y ago
This is the first I've heard of Tuta. How does it compare to the more popular nerd-focused Gmail alternatives like fastmail, proton, or hey?
84.
by claytonjy 3y ago
the person you're responding to is not the OP
85.
by claytonjy 3y ago
CoreWeave owns and runs their own infra, they aren't a middleman. There are middlemen that can actually get you better prices and availability than you can get yourself, because they buy or rent in volume, and can pit the hyper scalers
86.
by claytonjy 3y ago
have them read blog posts, docs, and client code from Temporal
87.
by claytonjy 3y ago
Yup, looks like a hopeful competitor to Temporal but too scared to name them directly.
88.
by claytonjy 3y ago
if you're using poetry, how does pyenv-virtualenv fit in?
89.
by claytonjy 3y ago
pyenv manages python versions, not virtual environments. venv won't help you grab python versions you don't have, and will happily install your requirements into a venv with the wrong python version.
90.
by claytonjy 3y ago
was this before torch 2.0? With the very notable exceptions of a few mispackaged versions, torch now includes all the relevant Nvidia libs, and I haven't seen it grab the CPU version on a GPU box yet, though I'm not sure what it l

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