Ok, fair. Hard to understand why it would get that wrong.

Because LLMs aren't sentient, they don't draw on facts, and they don't have nuance. The answer given is similar to answers you might expect to see for similar questions.

It's really amazing we can make machines do that, and it's really depressing that we think a stochastic bullshit machine is going to give us something we can rely on.

They are this wrong about everything, but you don't usually notice it when using it to look for things you aren't an expert in. The default stance really does need to be "do not trust, verify" at all times.

They can still be useful, e.g. they're significantly better at finding "I want a thing that does x but not y and it must be blue, or maybe two things that can be glued together to do that" than classic search. But they'll routinely miss extremely obvious answers because the related search it ran didn't find it, or completely screw up what something can actually do. Checking more pages of results by hand or asking humans who know even a little about those fields is still wildly more useful... but they're absolutely slaughtering the sites where people do that, by stealing all the real traffic and sending DDoS-level automated requests.

I’d make assumptions about how the cheapest and fastest possible flash model optimized for being extra cheap and extra fast would get something wrong based on its limited context (which can be very incomplete summaries of search results)

It somehow seems to interpret whatever sources it's grepping as the exact opposite of what those sources say fairly often. I've lost track of how many times I've clicked on the sources it cites, and every single one is in agreement, but the AI claims the opposite.

Did you just agree to a stranger's counterpoint on the internet? This post should be in a museum somewhere

The simple answer is that these systems are very bad at telling the truth reliably.