My perspective is that consciousness isn't a binary thing, or even a linear scale. It's an amalgamation of a bunch of different independent processes working together; and how much each matters is entirely dependent on culture and beliefs. We're artificially creating these independent processes piece by piece in a way that doesn't line up with traditional ideas of consciousness. Conversation and being able to talk about concepts one hasn't personally experienced are facets of consciousness and intelligence, ones that the latest and greatest LLMs do have. Of course there others too that they don't: logic, physical presence, being able to imagine things in their mind's eye, memory, etc.

It's reductive to dismiss GPT4 as nothing more than mimicry; saying it's just a mathematical text prediction model is like saying your brain is just a bunch of neurons. Both statements are true, but it doesn't change what they can do. If someone could accurately predict the moves a chess master would make, we wouldn't say they're just good at statistics, we'd say they're a chess master. Similarly, regardless of how rich someone's internal world is, if they're unable to express the intelligent ideas they have in any intelligible way we wouldn't consider them intelligent.

So what we have now with AI are a few key parts of intelligence. One important thing to consider is how language can be a path to other types of intelligence; here's a blog post I stumbled across that really changed my perspective on that: http://www.asanai.net/2023/05/14/just-a-statistical-text-predictor/. Using your example of mathematics, as we know it falls apart doing anything remotely complicated. But when you help it approach the problem step-by-step in the way a human might - breaking it into small pieces and dealing with them one at a time - it actually does really well. Granted, the usefulness of this is limited when calculators exist and it requires as much guidance as a child to get correct answers, but even matching the mathematical intelligence of a ten year old is nothing to sneeze at.

To be clear I don't think pursuing LLMs endlessly will be the key to a widely accepted 'general intelligence'; it'll require a multitude of different processes and approaches working together for that to ever happen, and we're a long way from that. But it's also not just getting carried away with the hype to say the past few years have yielded massive steps towards 'true' artificial intelligence, and that current LLMs have enough use cases to change a lot of people's lives in very real ways (good or bad).