There's a pattern where people create AI-specific infrastructure for coding agents which is essentially instantly obsolete because it's pointless. Stuff like most MCPs (instead of just using a CLI), agent-specific files (CLAUDE.md, AGENTS.MD, github-instructions.NET etc.) etc.

> You should have a good, concise introduction to the codebase that allows anyone to write and test a simple patch in under 15 minutes.

Yeah, that's the CONTRIBUTING file.

MAE is kind of obvious, because healthy ears are incredibly sensitive. 0 dbSPL translates to attowatts on the eardrum displacing it just a few pm, with hair cells firing on sub-nm movements (after mechanical amplification). It is completely unsurprising that just the thermal effect of RF being pulsed in the general direction of the head can become audible in the right circumstances.

The gzip compression of layers is actually optional in OCI images, but iirc not in legacy docker images. The two formats are not the same. On SSDs, the overhead for building an index for a tar is not that high, if we're primarily talking about large files (so the data/weights/cuda layers instead of system layers). The approach from the article is of course still faster, especially for running many minor variations of containers, though I am wondering how common it is for only some parts of weights changing? I would've assumed that most things you'll do with weights would change about 100% of them when viewed through 1M chunks. The lazy pulling probably has some rather dubious/interesting service latency implications.

The main annoyance imho with gzip here is that it was already slow when the format was new (unless you have Intel QAT and bothered to patch and recompile that into all the go binaries which handle these, which you do not).

When I grow up, I'm going to Bovine University!