Kogasa

This has nothing to do with Windows or Linux. Crowdstrike has in fact broken Linux installs in a fairly similar way before.

Sure, throw people in jail who haven’t committed a crime, that’ll fix all kinds of systemic issues

Catch and then what? Return to what?

It sounds like you don’t understand the complexity of the game. Despite being finite, the number of possible games is extremely large.

U good?

Your first two paragraphs seem to rail against a philosophical conclusion made by the authors by virtue of carrying out the Turing test. Something like “this is evidence of machine consciousness” for example. I don’t really get the impression that any such claim was made, or that more education in epistemology would have changed anything.

In a world where GPT4 exists, the question of whether one person can be fooled by one chatbot in one conversation is long since uninteresting. The question of whether specific models can achieve statistically significant success is maybe a bit more compelling, not because it’s some kind of breakthrough but because it makes a generalized claim.

Re: your edit, Turing explicitly puts forth the imitation game scenario as a practicable proxy for the question of machine intelligence, “can machines think?”. He directly argues that this scenario is indeed a reasonable proxy for that question. His argument, as he admits, is not a strongly held conviction or rigorous argument, but “recitations tending to produce belief,” insofar as they are hard to rebut, or their rebuttals tend to be flawed. The whole paper was to poke at the apparent differences between (a futuristic) machine intelligence and human intelligence. In this way, the Turing test is indeed a measure of intelligence. It’s not to say that a machine passing the test is somehow in possession of a human-like mind or has reached a significant milestone of intelligence.

https://academic.oup.com/mind/article/LIX/236/433/986238

I don’t think the methodology is the issue with this one. 500 people can absolutely be a legitimate sample size. Under basic assumptions about the sample being representative and the effect size being sufficiently large you do not need more than a couple hundred participants to make statistically significant observations. 54% being close to 50% doesn’t mean the result is inconclusive. With an ideal sample it means people couldn’t reliably differentiate the human from the bot, which is presumably what the researchers believed is of interest.

Frivolous CVEs aren’t a good thing for security. This bug was a possible DOS (not e.g. a privilege escalation) in a disabled-by-default experimental feature. It wasn’t a security issue and should have been fixed with a patch instead of raising a false alarm and damaging trust.

Your broader point would be stronger if it weren’t framed around what seems like a misunderstanding of modern AI. To be clear, you don’t need to believe that AI is “just” a “coded algorithm” to believe it’s wrong for humans to exploit other humans with it. But to say that modern AI is “just an advanced algorithm” is technically correct in exactly the same way that a blender is “just a deterministic shuffling algorithm.” We understand that the blender chops up food by spinning a blade, and we understand that it turns solid food into liquid. The precise way in which it rearranges the matter of the food is both incomprehensible and irrelevant. In the same way, we understand the basic algorithms of model training and evaluation, and we understand the basic domain task that a model performs. The “rules” governing this behavior at a fine level are incomprehensible and irrelevant-- and certainly not dictated by humans. They are an emergent property of a simple algorithm applied to billions-to-trillions of numerical parameters, in which all the interesting behavior is encoded in some incomprehensible way.