 All of this is governed by these mathematical rules, which are very much like what you would experience if we were actually inside of a video game. First self-aware entities appeared, that's in a sense a universe waking up and becoming aware of itself, right, is actually an opportunity. If we can figure out what's going on with black holes and maybe even get some clues by looking at them, then that can actually maybe be the master key that can help us unlock some of the deepest mysteries of quantum gravity and get a unified theory of physics. The snap decision, you know, should we ask this person on a date or not, where it might come down to just whether one neuron fired or not in the beginning, triggering a whole cascade of events that could end up with you living in this city, you know, being married to this person with children or living somewhere completely different, doing something different. I'm quite optimistic that we can create a really inspiring future with technology, but that's going to require winning what I call the wisdom race, the race between the growing power of the technology, exponentially growing power of the technology, with the wisdom with which we manage this tech. But there's a catch here because technology is getting exponentially more and more powerful, right? And at some point it crosses the threshold of power where learning from mistakes actually goes from being a good strategy to being a really, really bad strategy. And I feel we've already crossed that threshold with nuclear weapons, and we've earned the verge of crossing the threshold with synthetic biology, which can be used fantastically to improve our health or to create engineered pandemics. And we're totally going to cross that threshold with artificial intelligence if we succeed in building artificial general intelligence that can outsmart us, you know, in all ways. It's not difficult at all to make the world much, much better. It's just that we have our monkey brains and most political leaders are very clueless about technology. And in short, of course, go into careers that machines suck at and are going to continue to be bad at for a long time.