I basically have the opposite reaction from my first gen immigrant social circle ¯\_(ツ)_/¯. Also, unless they're ignoring/ignorant of the checks & balances falling apart, I'm not sure this bolsters OPs implied point.
The onus is on you to prove or at least convincingly argue that the results are unlikely to generalize across incremental model releases. In my personal experience, the overly affirming nature seems to have held since GPT-3. What makes you think a newer, larger model would not exhibit this behavior? Beyond "they're more capable"? I'd argue that being more capable doesn't mean less sycophantic.
It's certainly possible some of the new advances (chain-of-thought, some kind of agentic architecture) could lessen or remove this effect. But that's not what the paper was studying! And if you feel strongly about it, you could try to further the discussion with results instead of handwavingly dismissing others' work.
Any paper like this would easily take a year or more to write and go through the submission/review/rebuttal/revision/acceptance process. I don't understand why the models being a year or two old now is worth noting as though it's a clear weakness? What should they do, publish sub-standard results more quickly?
Common Lisp in particular is multi-paradigm. You can write a ton of code and never use recursion once. I doubt bridging this "gap" was in any way difficult.
> It comes on the heels of a Delaware court decision clearing Meta’s insurers of responsibility for damages incurred from “several thousand lawsuits regarding the harm its platforms allegedly cause children” — a ruling that could leave it and other tech titans on the hook for untold future millions.