Perhaps you are confusing a lack of preparation with a lack of good ideas.
The AI space will ultimately be dominated by people who know how to train models, process data, write senior-level code, consistently produce research papers, and understand the underlying technical details behind current models at the software level, because those are the people who can communicate ideas with clarity and pragmatism and command respect from their peers and the average joe. Ask yourself whether you truly believe Yudkowsky is capable of any of these things. To my knowledge he hasn’t demonstrated any of this, he has produced at most a few research papers in his lifetime and has no public-facing code. So maybe the problem is not a lack of preparation.
A question for all: If you are wrong and in 4/13/40 years most of this fails to come true, will you blame it on your own models being wrong or shift goalposts towards the success of the AI safety movement / government crack downs on AI development? If the latter, how will you be able to prove that AGI definitely would have come had the government and industry not slowed down development?
To add more substance to this comment: I felt Ege came out looking the most salient here. In general, making predictions about the future should be backed by heavy uncertainty. He didn’t even disagree very strongly with most of the central premises of the other participants, he just placed his estimates much more humbly and cautiously. He also brought up the mundanity of progress and boring engineering problems, something I see as the main bottleneck in the way of a singularity. I wouldn’t be surprised if the singularity turns out to be a physically impossible phenomenon because of hard limits in parallelisation of compute or queueing theory or supply chains or materials processing or something.