[mdaniel]

> Requirements

> Ubuntu 18.04 or newer (required)

> Dedicated machines only - the machine shouldn't be doing other stuff while rented

well that's certainly not what I expected. ctrl-f "virtual" gives nothing, so it seems they really mean "take over your machine"

> Note: you may need to install python2.7 to run the install script.

what kind of nonsense is this? Did they write the script in 2001 and just abandon it?

[mschuster91]

> what kind of nonsense is this? Did they write the script in 2001 and just abandon it?

Anything AI/ML is a hot mess of cobbled-together bits and pieces of Python barely holding together. I recently read somewhere that there should be a new specialization of "ML DevOps Engineer"... and hell I'm supporting that.

[p1esk]

there should be a new specialization of "ML DevOps Engineer"

Do you mean MLOps? Nothing new about it. We have two full-time MLOps engineers at our startup.

[ethbr0]

Python is awesome because they built what people wanted.

Python is terrible because they built what people wanted.

[williamstein]

I just skimmed their FAQ at https://vast.ai/faq, and it seems like it could use an update. E.g., it says "Initially we are supporting Ubuntu Linux, more specifically Ubuntu 16.04 LTS.". That version of Ubuntu has been end-of-life'd for several years, and when I just tried vast.ai out, it seemed to be using Ubuntu 20.04. There were also a couple of words with letters missing (probably trivial typos) that could be found with a spell checker. The questions in their FAQ are really interesting though, in terms of highlighting what users care about (e.g., there's a lot devoted to "how do I use vast.ai + google colab together"?). I also wonder when vast.ai started? Sometimes you can get insight from a company blog page, but the vast.ai blog seems to start in Feb 2023: https://vast.ai/blog . There's a bunch of "personal experiences" with vast.ai from 3 years ago in this discussion though: https://www.reddit.com/r/MachineLearning/comments/hv49pd/d_c...

A comment in that discussion mentions yet another competitor in this space that I've never heard of: https://www.qblocks.cloud/ -- I just tried Q blocks out and the new user experience wasn't as good for me as with vast.ai: you have to put in $10 money to try it, instead of getting to try it initially for free; there is a manual approval process before you can try data center class GPUs; you only see that your instance is in Norway (say) after you try to start it, not before; it seems like there's no ssh access, and they only provide Jupyter to connect; neither pytorch nor tensorflow seemed to be installed. They could probably update their pages too, e.g., https://www.qblocks.cloud/vision is all about crypto mining and smartphones, which feels a bit dated... :-)

[mikeravkine]

TensorDock Marketplace is another option: https://marketplace.tensordock.com/order_list

It's unique in that you can set your own prices, it's a true spot marketplace.. I've grabbed 2x3090 for $0.02/hr before.

Probably no good for training (can be interrupted any time with zero warning ssh just drops and that's it) but for my inference usecases it lets me spot heavy compute for pennies.

[orf]

Seems like it: https://s3.amazonaws.com/vast.ai/install