> We have hope for these approaches but the reality of this stuff is way more nuanced than you think it is. Sure, everything has more nuance. The point is this

> We have hope for these approaches but the reality of this stuff is way more nuanced than you think it is. Sure, everything has more nuance. The point is this stuff is available now; this isn't some future sci-fi, it's only going to get better, it's not the only research on gene targeting, and AI is starting to help with this research. By the time AGI is actually here, consider the breadth of knowledge and capabilities that will be at its disposal. > Alphafold can't reliably predict thermal energy landscapes or make functional predictions - and how could it? It wasn't trained on anything that could capture structure - function relationships. If your point is that the only reason an AI like AlphaFold can't make functional predictions is that we haven't trained an AI to do that, then unless you're arguing we can't or won't ever do that, I'm not sure how that's supposed to be an objection to the argument that AI will be able to make use of this information without doing all of the experiments people seem to think would be necessary. Like I said, we're already going to be doing these experiments because it's useful to us, and we will train AIs to make these predictions, again, because it's useful to us. Stop imagining what an AGI has access to now, and start thinking what it will have access to with the inevitable march of progress that we're already on. Edit: and of course, this doesn't even take into account the fact that an AI could acquire resources to pay people to do this research. The internet provides ample opportunities like this now.