This is a perfect example of the revealed-preference fallacy. The use of providers like Meta does not reflect a well-informed, freely chosen preference. Meta spends a ton of money to squash competition, remove viable alternatives, and to make their products addictive.

I do say this as a fan of both, though.

Say hypothetically that 20% of attack slip through, which is still worrying, you can mitigate 80% of attacks by just waiting a week. It's a low risk, high reward strategy.

Did you use AI to write this...? Because it does not follow from the post you're replying to.

[0] https://arxiv.org/abs/2501.12948

I'm getting a good amount of interviews for developer and data engineering positions, but the competition is tough. Many positions have seen a 5x increase in candidates since the same time last year, according to my interviewers.

However, I'm hopefully getting an offer as a data platform engineer soon. The department leader has ranked me as their first choice, so unless the higher-ups complain... Knock on wood.

The biggest one is that, well... The test doesn't aim to see what GPT-4 can do and how well it does it, only whether the participant can guess the (possibly cherry-picked) answer the author decided on. In short, we don't know if he sampled answers and decided on the most probable answer (akin to consensus voting/self-consistency[1]), or if he asked a question and chose the first one.

Maybe GPT-4 guesses the correct answer for a question 80% of the time, but he got unlucky? You don't know, the author doesn't tell you. The answers are generated ahead of time and are the same every time you go through the test.

[1] https://doi.org/10.48550/arXiv.2203.11171