Shouldn't this be in userspace?

Posted Feb 8, 2026 1:27 UTC (Sun) by quotemstr (subscriber, #45331)
In reply to: Shouldn't this be in userspace? by ATLief
Parent article: An in-kernel machine-learning library

There are tons and tons of great places to apply AI in Linux. Every magic number (my favorite being the "I determined this by opening LibreOffice a bunch of times" one) is a candidate for some kind of auto tuning.

BUT --- can't almost all of this tuning happen via a combination of eBPF and userspace supervision? AI inference isn't exactly known to be a lightweight or low-latency operation. In every scenario I can imagine, punting a kernel tuning decision to userspace would not impose meaningful cost overhead relative to any ML stuff userspace might want to do.

So, while I'm generally pretty gung-ho about applying AI to systems engineering problems, this particular patch seems like the wrong way to go about it.

Shouldn't this be in userspace?

Posted Feb 13, 2026 2:39 UTC (Fri) by cypherpunks2 (guest, #152408) [Link] (1 responses)

> AI inference isn't exactly known to be a lightweight or low-latency operation.

That really depends. The Opus encoder, for example, has a speech/music detection gated recurrent unit (GRU) with less than 5k weights and can detect, in real time with hysteresis and while using less than 0.02% of the CPU, whether or not any given 20 ms audio frame has transitioned from speech to music (and vice versa): https://jmvalin.ca/opus/opus-1.3/. Any time you call someone over WebRTC (and pretty much every common VoIP protocol), you'll be doing inference with this model 50 times per second without even realizing it.

And a GRU isn't just a trivial feedforward neural network; It has memory that allows it to keep some information for a long time while discarding other information more quickly. When your problem space is very small, you can make a model that is exceptionally lightweight for both training and inference.

Not all "AI" models are massive, bloated large language models with billions of weights.

Shouldn't this be in userspace?

Posted Feb 13, 2026 2:56 UTC (Fri) by mathstuf (subscriber, #69389) [Link]

> Not all "AI" models are massive, bloated large language models with billions of weights.

Yeah, but if they are, then we can fuel an exorbitant amount of capital expenditure and generally just make lots of motion in the stock market. What else are these poor, bored VCs with billions burning holes in their pockets to do with it? Feed the hungry? End malaria?