I don't believe that they believe it, I believe that they're all in on doing all the things you'd do if your goal was to demonstrate to investors that you truly believe it.
The safety-focused labs are the marketing department.
An AI that can actually think and reason, and not just pretend to by regurgitating/paraphrasing text that humans wrote, is not something we're on any path to building right now. They keep telling us these things are going to discover novel drugs and do all sorts of important science, but internally, they are well aware that these LLM architectures fundamentally can't do that.
A transformer-based LLM can't do any of the things you'd need to be able to do as an intelligent system. It has no truth model, and lacks any mechanism of understanding its own output. It can't learn and apply new information, especially not if it can't fit within one context window. It has no way to evaluate if a particular sequence of tokens is likely to be accurate, because it only selects them based on the probability of appearing in a similar sequence, based on the training data. It can't internally distinguish "false but plausible" from "true but rare." Many things that would be obviously wrong to a human, would appear to be "obviously" correct when viewed from the perspective of an LLM's math.
These flaws are massive, and IMO, insurmountable. It doesn't matter if it can do 50% of a person's work effectively, because you can't reliably predict which 50% it will do. Given this unpredictability, its output has to be very carefuly reviewed by an expert in order to be used for any work that matters. Even worse, the mistakes it makes are meant to be difficult to spot, because it will always generate the text that looks the most right. Spotting the fuckup in something that was optimized not to look like a fuckup is much more difficult than reviewing work done by a well-intentioned human.