For the most part, narrow AI and machine learning don't overlap that much with AGI theory in the way that say, AIXI does.
Interesting characterization - my hunch would have been that AIXI is an interesting thought experiment but ultimately of little to no practical value, while machine learning research seems to be uncovering all kinds of domain-general ways of learning and reasoning.
My experience with applied machine learning is strictly undergraduate-level modulo a little tinkering and a little industry experience, so these impressions might be quite unlike those of an actual specialist, but my sense is that while it comes up with a lot of interesting stuff that might potentially be useful in making a hypothetical AGI, it ultimately isn't that interested in generalizing outside domain-specific approaches and that limits its bandwidth to a large extent.
Machine-learning algorithms are treated as -- not exactly a black box, but pretty...
I know people have talked about this in the past, but now seems like an important time for some practical brainstorming here. Hypothetical: the recent $15mm Series A funding of Vicarious by Good Ventures and Founders Fund sets off a wave of $450mm in funded AGI projects of approximately the same scope, over the next ten years. Let's estimate a third of that goes to paying for man-years of actual, low-level, basic AGI capabilities research. That's about 1500 man-years. Anything which can show something resembling progress can easily secure another few hundred man-years to continue making progress.
Now, if this scenario comes to pass, it seems like one of the worst-case scenarios -- if AGI is possible today, that's a lot of highly incentivized, funded research to make it happen, without strong safety incentives. It seems to depend on VCs realizing the high potential impact of an AGI project, and of the companies having access to good researchers.
The Hacker News thread suggests that some people (VCs included) probably already realize the high potential impact, without much consideration for safety:
Is there any way to reverse this trend in public perception? Is there any way to reduce the number of capable researchers? Are there any other angles of attack for this problem?
I'll admit to being very scared.