AI content for specialists
There is a lot of AI content recently, and it is sometimes of the kind that requires specialized technical knowledge, which I (an ordinary software developer) do not have. Similarly, articles on decision theories are often written in a way that assumes a lot of background knowledge that I don't have. As a result there are many articles I don't even click at, and if I accidentally do, I just sigh and close them.
This is not necessarily a bad thing. As something develops, inferential distances increase. So maybe, as a community we are developing a new science, and I simply cannot keep up with it. -- Or maybe it is all crackpottery; I wouldn't know. (Would you? Are some of us upvoting content they are not sure about, just because they assume that it must be important? This could go horribly wrong.) Which is a bit of a problem for me, because now I can no longer recommend Less Wrong in good faith as a source of rational thinking. Not because I see obviously wrong things, but because there are many things where I have no idea whether they are right or wrong.
We had some AI content and decision theory here since the beginning. But those articles written back then by Eliezer were quite easy to understand, at least for me. For example, "How An Algorithm Feels From Inside" doesn't require anything beyond high-school knowledge. Compare it to "Hypothesis: gradient descent prefers general circuits". Probably something important, but I simply do not understand it.
Just like historically MIRI and CFAR split into two organizations, maybe Less Wrong should too.
Feeling of losing momentum
I miss the feeling that something important is happening right now (and I can be a part of it). Perhaps it was just an illusion, but at the first years of Less Wrong it felt like we were doing something important -- building the rationalist community, inventing the art of everyday rationality, with the perspective to raise the general sanity waterline.
It seems to me that we gave up on the sanity waterline first. The AI is near, we need to focus on the people who will make a difference (whom we could recruit for an AI research), there is no time to care about the general population.
Although recently, this baton was taken over by the Rational Animations team!
Is the rationalist community still growing? Offline, I guess it depends on the country. In Bratislava, where I live, it seems that ~ no one cares about rationality. Or effective altruism. Or Astral Codex Ten. Having five people at a meetup is a big success. Nearby Vienna is doing better, but it is merely climbing back to pre-COVID levels, not growing. Perhaps it is better at some other parts of the world.
Online, new people are still coming. Good.
Also, big thanks to all people who keep this website running.
But still it no longer feels to me anymore like I am here to change the world. It is just another form of procrastination, albeit a very pleasant one. (Maybe because I do not understand the latest AI and decision theory articles; maybe all the exciting things are there.)
Etc.
Some dialogs were interesting, but most are meh.
My greatest personal pet peeve was solved: people no longer talk uncritically about Buddhism and meditation. (Instead of talking more critically they just stopped talking about it at all. Works for me, although I hoped for some rational conclusion.)
It is difficult for me to disentangle what happens in the rationalist community from what happens in my personal life. Since I have kids, I have less free time. If I had more free time, I would probably be recruiting for the local rationality (+adjacent) community, spend more time with other rationalists, maybe even write some articles... so it is possible that my overall impression would be quite different.
(Probably forgot something; I may add some points later.)
We've basically known how to create AGI for at least a decade. AIXI outlines the 3 main components: a predictive world model, a planning engine, and a critic. The brain also clearly has these 3 main components, and even somewhat cleanly separated into modules - that's been clear for a while.
Transformers LLMs are pretty much exactly the type of generic minimal ULM arch I was pointing at in that post (I obviously couldn't predict the name but). On a compute scaling basis GPT4 training at 1e25 flops uses perhaps a bit more than human brain training, and its clearly not quite AGI - but mainly because it's mostly just a world model with a bit of critic: planning is still missing. But its capabilities are reasonably impressive given that the architecture is more constrained than a hypothetical more directly brain equivalent fast-weight RNN of similar size.
Anyway I don't quite agree with the characterization that these models are just " interpolating valid completions of any arbitrary prompt sampled from the distribution". Human intelligence also varies widely on a spectrum with tradeoffs between memorization and creativity. Current LLMs mostly aren't as creative as the more creative humans and are more impressive in breadth of knowledge, but eh part of that could be simply that they currently completely lack the component essential for creativity? That they accomplish so much without planning/search is impressive.
Interestingly that is closer to my position and I thought that Byrnes thought the generator of value was somewhat more complex, although are views are admittedly fairly similar in general.