And then when you do ask humans to help AI in parsing true information people cry about censorship.

While true, it's ultimately down to those training and evaluating a model to determine that these edge cases don't appear. It's not as hard when you work with compositional models that are good at one thing, but all the big tech companies are in a ridiculous rush to get their LLM's out. Naturally, that rush means that they kinda forget that LLM's were often not the first choice for AI tooling because...well, they hallucinate a lot, and they do stuff you really don't expect at times.

I'm surprised that Google are having so many issues, though. The belief in tech has been that Google had been working on these problems for many years, and they seem to be having more problems than everyone else.

What's more worrisome are the sources it used to feed itself. Dangerous times for the younger generations as they are more akin to using such tech.

Even though our current models can be really complex, they are still very very far away from being the elusive General Purpose AI sci-fi authors have been writing about for decades (if not centuries) already. GPT and others like it are merely Large Language Models, so don’t expect them to handle anything other than language.

Humans think of the world through language, so it’s very easy to be deceived by an LLM to think that you’re actually talking to a GPAI. That misconception is an inherent flaw of the human mind. Language comes so naturally to us, and we’re often use it as a shortcut to assess the intelligence of other people. Generally speaking that works reasonably well, but an LLM is able to exploit that feature of human behavior in order to appear to be smarter than it really is.