The guy is genuinely worried for his future. I see nothing shameful or narcissistic about that, and I don't think it makes sense for you to wish him any harm.
Can you imagine ChatGPT terminating a conversation because it thought your question was "low effort?" The behavior wouldn't be viewed as helpful or aligned, and nobody would use it.
StackOverflow was, all too often, not helpful or aligned. It died because the staff were unable to get the moderators to be helpful.
That's because the purpose of this article is not to have an objective debate over their abilities at all. Most interesting research in this field isn't. Instead, it's to present a new technique to improve LLM performance, which is much more interesting than (once again) rehashing the philosophy of LLM personhood.
The reason I think this is a bad idea is that it lulls you into a false sense of security. The article makes recommendations that seem thorough and sensible - keyword "seem" - but, as mentioned elsewhere here, there are other potential hidden sources of telemetry (in CarPlay and Android Auto), and who knows what else.
For this kind of thing to succeed as a general lifestyle, you would need to invest an enormous amount of time making potentially irreversible modifications to all kinds of electronic equipment - only to be virtually guaranteed to miss something.
Do this kind of thing if you want, but don't be fooled into thinking you're actually solving the problem for real.
That makes sense. If you could magically just get the top d PCs in quadratic kernel space without having to compute the whole kernel matrix, and then just do top-d quadratic PCs -> ridge, would that be better than doing the PCA -> top-d -> quadratic kernel ridge as you are now?
Absolutely. Who cares if the LLM automates some of the grunt work? Mathematicians are artists, and they paint with ideas. The goal is map out more of the beautiful structure of how things work. The enjoyment in it derives entirely from the payoff of seeing the larger view of how things fit together. If part of their process involves bouncing things off of other people, or even LLMs, I don't think it matters much, nor does it take away from the enjoyment in getting things figured out.