LessWrong 2.0 Reader

I have heard people say this so many times, and it is consistently the opposite of my experience. The random spontaneous conversations at conferences are disproportionately shallow and tend toward the same things which have been discussed to death online already, or toward the things which seem simple enough that everyone thinks they have something to say on the topic. When doing an activity with friends, it's usually the activity which is novel and/or interesting, while the conversation tends to be shallow and playful and fun but not as substantive as the activity. At work, spontaneous conversations generally had little relevance to the actual things we were/are working on (there are some exceptions, but they're rarely as high-value as ordinary work).

ChatGPT picked 2024-12-31 18:00.

Gemini picked 2024-12-31 18:00.

Claude picked 2025-01-01 00:00.

I don't know how can I make it more obvious that your belief is questionable. I don't think you follow "If you disagree, try getting curious about what your partner is thinking". That's the problem not only with you, but with LessWrong community. I know that preserving such belief is very important for you. But I'd like to kindly invite you to be a bit more sceptical.

How can you say that these forecasts are equal?

There's The Bayesian Conspiracy's discord server. No need to listen to the podcast or to related podcasts to participate in discussion.

a lot of skill ceilings are much higher than you might think, and worth investing in

The former doesn't necessarily imply the latter in general, because even if we are systematically underestimating the realistic upper bound for our skill level in these areas, we would still have to deal with diminishing marginal returns to investing in any particular one. As a result, I am much more confident of the former claim being correct for the average LW reader than of the latter. In practice, my experience tells me that you often have "phase changes" of sorts, where there's a rather binary instead of continuous response to a skill level increase: either you've hit the activation energy level, and thus unlock the self-reinforcing loop of benefits that flow from the skill (once you can apply it properly and iterate on it or use it recursively), or you haven't, in which case any measurable improvement is minimal. It's thus often more important to get past the critical point than to make marginal improvements either before or after hitting it.

On the other hand, many of the skills you mentioned afterwards in your comment seem relatively general-purpose, so I could totally be off-base in these specific cases.

Yes! I've always been a huge believer in this idea that the ease of eating a food is important and underrated. Very underrated.

I'm reminded of this clip of Anthony Bourdain talking about burgers and how people often put slices of bacon on a burger, but that in doing so it makes the burger difficult to eat. Presumably because when you go to take a bite you the whole slice of bacon often ends up sliding off the burger.

Am I making this more enjoyable by adding bacon? Maybe. How should that bacon be introduced into the question? It's an engineer and structural problem as much as it is a flavor experience. You really have to consider all of those things. One of the greatest sins in "burgerdom" I think is making a burger that's just difficult to eat.

The document seems to try to argue that Uber cannot possibly become profitable. I would be happy to take a bet that Uber will become profitable within the next 5 years. 

And indeed it already has.

Baltimore, MD, USA 

January 4. Time is TBD. The location is in Rockville. You can message me for the details. 

Fundamentally, the story was about the failure cases of trying to make capable systems that don't share your values safe by preventing specific means by which its problem solving capabilities express themselves in scary ways. This is different to what you are getting at here, which is having those systems actually operationally share your values. A well aligned system, in the traditional ‘Friendly AI’ sense of alignment, simply won't make the choices that the one in the story did.

Seems like that guy has failed to grasp the fact that some things are naturally more predictable than others.  Estimating how much concrete you need to build a house is just way easier than estimating how much time you need to design and code a large novel piece of software (even if the requirements don't change mid-project).

It's nicely done, and I think it will be helpful for anyone in refining their thinking. Thanks for doing this! And for making it easy to edit. That makes it a more general tool for scenario evaluation.