LessWrong 2.0 Reader

Yes, perfect causal closure is technically impossible, so it comes in degrees. My argument is that the degree of causal closure of possible abstractions in the brain is less than one might naively expect.

Are there any measures of approximate simulation that you think are useful here?

I am yet to read this but I expect it will be very relevant! https://arxiv.org/abs/2402.09090

"Spy" is an ambiguous term, sometimes meaning "intelligence officer" and sometimes meaning "informant". Most 'spies' in the sense that law enforcement is concerned are essentially untrained civilians who have chosen pass information to officers of a foreign country, for varying reasons. So if you see someone acting suspicious, an argument like "well a real spy would have been trained to not act suspicious in spy school" is usually invalid.

Then wolfram alpha?

The "you need to hit a particular activation level" seems right to me. Generally when I'm trying to teach people skills, I try to get them to fluency-escape-velocity, where it is net-positive to apply the skill to their day-job.

There's additional important bits about hitting particular thresholds allow you to build engines out of multiple skills (I'll probably reply more to t14n's comment [LW · GW] about that)

IIRC OAers also said somewhere (doesn't seem to be in the blog post, so maybe this was on Twitter?) that o1 or o1-preview was initialized from a GPT-4 (a GPT-4o?), so that would also rule out a literal parameter-size interpretation (unless OA has really brewed up some small models).

(All of which I consider to be consistent with my summary, if anyone is wondering, and thus, given that Hsu did not choose to object to any of the main points of my summary in his clarifications, are confirmation.)

Yes, I'd assume a sensible implementation would transfer the metadata as well - the new post would have the same date, karma, and comments as the original comment. Just as if it had always been posted as a post.

This is what Hsu just said about it: "3. I could be described as a China hawk in that I've been pointing to a US-China competition as unavoidable for over a decade. But I think I have more realistic views about what is happening in PRC than most China hawks. I also try to focus on simple descriptive analysis rather than getting distracted by normative midwit stuff."

https://x.com/hsu_steve/status/1861970671527510378 

Steve Hsu clarified some things on my thread about this discussion: https://x.com/hsu_steve/status/1861970671527510378

"Clarifications:

1. The mafia tendencies (careerist groups working together out of self-interest and not to advance science itself) are present in the West as well these days. In fact the term was first used in this way by Italian academics.

2. They're not against big breakthroughs in PRC, esp. obvious ones. The bureaucracy bases promotions, raises, etc. on metrics like publications in top journals, cititations, ... However there are very obvious wins that they will go after in a coordinated way - including AI, semiconductors, new energy tech, etc.

3. I could be described as a China hawk in that I've been pointing to a US-China competition as unavoidable for over a decade. But I think I have more realistic views about what is happening in PRC than most China hawks. I also try to focus on simple descriptive analysis rather than getting distracted by normative midwit stuff.

4. There is coordinated planning btw govt and industry in PRC to stay at the frontier in AI/AGI/ASI. They are less susceptible to "visionaries" (ie grifters) so you'll find fewer doomers or singularitarians, etc. Certainly not in the top govt positions. The quiet confidence I mentioned extends to AI, not just semiconductors and other key technologies."

I mean "mass and energy are conserved" - there's no way to gain weight except if losses are smaller than gains.  This is a basic truth, and an unassailable motte about how physics works.  It's completely irrelevant to the bailey of weight loss and calculating calories.