←back to thread

AI models need a virtual machine

(blog.sigplan.org)
224 points azhenley | 1 comments | 30 Aug 25 13:25 UTC | HN request time: 0s | source
Show context
nhod ◴[30 Aug 25 14:42 UTC] No.45075076[source]▶
A million years ago in AI time, AKA yesterday, there was a HN post from John Carmack talking about how Meta wasted a ton of time and money making XROS and how nowadays it doesn’t make any sense to write a new OS [1].

And then this post today which makes a very strong case for it. (Yes, a VM isn’t an entire OS, Yes, it would be lighter weight than a complete OS. Yes, it would be industry-wide. Yes, we’d likely use an existing OS or codebase to start. Yes, nuance.)

[1] https://news.ycombinator.com/item?id=45066395

replies(4): >>45075289 #>>45075402 #>>45075695 #>>45078397 #
1. ijk ◴[30 Aug 25 15:05 UTC] No.45075289[source]▶
I think the main difference is that sandboxing and simplifying the LLM's access to tools and data tends to be core functionality, whereas for XR it is more about performance and developer experience.

I'm going to put a lot of work in anyway to keep the LLM from accidentally overwriting the code running it or messing with customer data incorrectly or not being overwhelmed with implementation details; having a standard for this makes it much easier and lets me rely on other people's model training.

If it's merely that I have to train a dev on an XR SDK, I can pay them a salary or encourage schools to teach it. AI needs an team for an R&D project and compute time, which can get a lot more expensive at the high end.