endoself — LessWrong

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Replying toWe are the Athenians, not the Spartans

Note that I ... wrote the only comment on the IAF post you linked

Yes, I replied to it :)

Unfortunately, I don't expect to have more Eliezer-level explanations of these specific lines of work any time soon. Eliezer has a fairly large amount of content on Arbital that hasn't seen LW levels of engagement either, though I know some people who are reading it and benefiting from it. I'm not sure how LW 2.0 is coming along, but it might be good to have a subreddit for content similar to your recent post on betting. There is an audience for it, as that post demonstrated.

Replying toWe are the Athenians, not the Spartans

endoself9y

We are the Athenians, not the Spartans

Maybe you've heard this before, but the usual story is that the goal is to clarify conceptual questions that exist in both the abstract and more practical settings. We are moving towards considering such things though - the point of the post I linked was to reexamine old philosophical questions using logical inductors, which are computable.

Further, my intuition from studying logical induction is that practical systems will be "close enough" to satisfying the logical induction critereon that many things will carry over (much of this is just intuitions one could also get from online learning theory). E.g. in the logical induction decision theory post, I expect the individual points made using logical inductors to mostly or all apply to practical systems, and you can use the fact that logical inductors are well-defined to test further ideas building on these.

Replying toWe are the Athenians, not the Spartans

endoself9y

We are the Athenians, not the Spartans

Scott Garrabrant and I would be happy to see more engagement with the content on Agent Foundations (IAF). I guess you're right that the math is a barrier. My own recent experiment of linking to Two Major Obstacles for Logical Inductor Decision Theory on IAF was much less successful than your post about betting, but I think that there's something inessential about the inaccessiblity.

In that post, for example, I think the math used is mostly within reach for a technical lay audience, except that an understanding of logical induction is assumed, though I may have missed some complexity in looking it over just now. Even for that, it should be possible to explain enough about logical inductors briefly and accessibly enough to let someone understand a version of that post, though I'm not sure if that has been done. People recommend this talk as the best existing introduction.

Replying toThe Growth of My Pessimism: Transhumanism, Immortalism, Effective Altruism.

endoself10y

The Growth of My Pessimism: Transhumanism, Immortalism, Effective Altruism.

I model probabilistic thinking as something you build on top of all this. First you learn to model the world at all (your steps 3-8), then you learn the mathematical description of part of what your brain is doing when it does all this. There are many aspects of normative cognition that Bayes doesn't have anything to say about, but there are also places where you come to understand what your thinking is aiming at. It's a gears model of cognition rather than the object-level phenomenon.

If you don't have gears models at all, then yes, it's just another way to spout nonsense. This isn't because it's useless, it's because people cargo-cult it.... (read more)

Replying toWelcome to Less Wrong! (8th thread, July 2015)

endoself11y

Welcome to Less Wrong! (8th thread, July 2015)

Hi Yaacov!

The most active MIRIx group is at UCLA. Scott Garrabrant would be happy to talk to you if you are considering research aimed at reducing x-risk. Alternatively, some generic advice for improving your future abilities is to talk to interesting people, try to do hard things, and learn about things that people with similar goals do not know about.

Replying toEven when contrarians win, they lose: Jeff Hawkins

endoself11y

Even when contrarians win, they lose: Jeff Hawkins

As far as I can tell, you've misunderstood what I was trying to do with this post. I'm not claiming that Hawkins' work is worth pursuing further; passive_fist's analysis seems pretty plausible to me. I was just trying to give people some information that they may not have on how some ideas developed, to help them build a better model of such things.

(I did not downvote you. If you thought that I was arguing for further work towards Hawkins' progam, then your comment would be justified, and in any case this is a worthwhile thing for me to explicitly disclaim.)

Replying toEven when contrarians win, they lose: Jeff Hawkins

endoself11y

Even when contrarians win, they lose: Jeff Hawkins

Yeah, I didn't mean to contradict any of this. I wonder how much a role previous arguments from MIRI and FHI played in changing the zeitgeist and contributing to the way Superintelligence was received. There was a slow increase in uninformed fear-of-AI sentiments over the preceding years, which may have put people in more of a position to consider the arguments in Superintelligence. I think that much of this ultimately traces back to MIRI and FHI; for example many anonymous internet commenters refer to them or use phrasing inspired by them, though many others don't. I'm more sceptical that this change in zeitgeist was helpful though.

Of course specific people who interacted with MIRI/FHI more strongly, such as Jaan Tallinn and Peter Thiel, were helpful in bring the discourse to where it is today.

Replying toEven when contrarians win, they lose: Jeff Hawkins

endoself11y

Even when contrarians win, they lose: Jeff Hawkins

The quote from Ng is

The big AI dreams of making machines that could someday evolve to do intelligent things like humans could, I was turned off by that. I didn’t really think that was feasible, when I first joined Stanford. It was seeing the evidence that a lot of human intelligence might be due to one learning algorithm that I thought maybe we could mimic the human brain and build intelligence that’s a bit more like the human brain and make rapid progress. That particular set of ideas has been around for a long time, but [AI expert and Numenta cofounder] Jeff Hawkins helped popularize it.

I think it's pretty clear that he would have worked on different things if not for Hawkins. He's done a lot of work in robotics, for example, so he could have continued working on robotics if he didn't get interested in general AI. Maybe he would have moved into deep learning later in his career, as it started to show big results.

Even when contrarians win, they lose: Jeff Hawkins

endoself

11y

I had long thought that Jeff Hawkins (and the Redwood Center, and Numentia) were pursuing an idea that didn't work, and were continuing to fail to give up for a prolonged period of time. I formed this belief because I had not heard of any impressive results or endorsements of their research. However, I recently read an interview with Andrew Ng, a leading machine learning researcher, in which he credits Jeff Hawkins with publicizing the "one learning algorithm" hypothesis - the idea that most of the cognitive work of the brain is done by one algorithm. Ng says that, as a young researcher, this pushed him... (read 267 more words →)

Replying toOpen thread, Feb. 16 - Feb. 22, 2015

endoself11y

Open thread, Feb. 16 - Feb. 22, 2015

GiveWell, GiveDirectly, Evidence Action/Deworm the World. You can vote for multiple charities.

Replying to2014 Less Wrong Census/Survey

endoself11y

2014 Less Wrong Census/Survey

I took the survey.

Are there any Lesswrongers in the Waterloo, Ontario area?

endoself

14y

I will soon be attending the University of Waterloo and I was wondering if there is interest in a meetup. Please reply if you are in the area.