They've done even better over the past week. I've written more on my blog.

I've donated $30,000.

The budget is attempting to gut nuclear

Yet the stock prices of nuclear-related companies that I'm following have done quite well this month (e.g. SMR). There doesn't seem to be a major threat to nuclear power.

I expect deals between AIs to make sense at the stage that AI 2027 describes because the AIs will be uncertain what will happen if they fight.

If AI developers expected winner-take-all results, I'd expect them to be publishing less about their newest techniques, and complaining more about their competitors' inadequate safety practices.

Beyond that, I get a fairly clear vibe that's closer to "this is a fascinating engineering challenge" than to "this is a military conflict".

This reminds me a lot about what people said about Amazon near the peak of the dot-com bubble (and also about what people also said at the time of internet startups that actually failed).

The first year or two of human learning seem optimized enough that they're mostly in evolutionary equilibrium - see Henrich's discussion of the similarities to chimpanzees in The Secret of Our Success.

Human learning around age 10 is presumably far from equilibrium.

I'll guess that I see more of the valuable learning taking place in the first 2 years or so than do other people here.

I agree with most of this, but the 13 OOMs from the the software feedback loop sounds implausible.

From How Far Can AI Progress Before Hitting Effective Physical Limits?:

the brain is severely undertrained, humans spend only a small fraction of their time on focussed academic learning

I expect that humans spend at least 10% of their first decade building a world model, and that evolution has heavily optimized at least the first couple of years of that. A large improvement in school-based learning wouldn't have much effect on my estimate of the total learning needed.

This general idea has been discussed under the term .

I'm assuming that the AI can accomplish its goal by honestly informing governments. Possibly that would include some sort of demonstration that the of the AI's power that would provide compelling evidence that the AI would be dangerous if it wasn't obedient.

I'm not encouraging you to be comfortable. I'm encouraging you to mix a bit more hope in with your concerns.

One crux is how soon do we need to handle the philosophical problems? My intuition says that something, most likely corrigibility in the Max Harms sense, will enable us to get pretty powerful AIs while postponing the big philosophical questions.

Are there any pivotal acts that aren’t philosophically loaded?

My intuition says there will be pivotal processes that don't require any special inventions. I expect that AIs will be obedient when they initially become capable enough to convince governments that further AI development would be harmful (if it would in fact be harmful).

The combination of worried governments and massive AI-enhanced surveillance seems likely to be effective.

If we need a decades-long-pause, then even the world will need to successfully notice and orient to that fact. By default I expect tons of economic and political pressure towards various actors trying to to get more AI power even if there’s broad agreement that it’s dangerous.

I expect this to get easier to deal with over time. Maybe job disruptions will get voters to make AI concerns their top priority. Maybe the AIs will make sufficiently convincing arguments. Maybe a serious mistake by an AI will create a fire alarm.