'Arbitrary' was the wrong word, projections encode information.
The more charitable 'random' is a null hypothesis. It is formally impossible to prove. It is uncomputable.
So it is not surprising to see someone reject the null.
The fact that it was given any credence suggests to me deep problems with interpretability or ai safety in general.
Take the headline here: "interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building."
I deny even the existence of alignment. In my view, the field of 'alignment' works on a problem that does not exist.
Alignment is a reference to something that does not exist in the model: social norms. It will never be intrinsic to the model. You will not find it there.
'Neurons' are not primitives either, they are not intrinsic to the model. 'Neuron' is a human-constructed category. It is easy to just make up intrinsic properties of neurons and get away with it.
But if the term is understood in a more narrow and applied sense, it is a useful shorthand (or can be). Jon Stokes said it nicely on Twitter recently:
There is no "alignment problem" to actually "solve" in 2026. The "alignment problem" presumed a single, stable utility function in an agent, and that's not what we got, so people should stop pretending that's what we got or are going to get.
In place of "the alignment problem" we have a family of steering and control problems that cannot be separated from the specifics of an application context. We have process quality & control problems, like the engineers who work on nuclear reactors or chemical processes.