Semantics; it’s obviously not equivalent to physical violence. 

I expect this to start not happening right away.

So at least we’ll see who’s right soon.

I like it relatively better when those values are relatively more aligned with mine, but I still put some weight on people doing their own thing even when I otherwise don’t like it. And third, I am not the sort of person who would try to convince you to pursue values which are not your own (including by self-modifying into someone whose values are not in line with your current values). I might fight you, if your values are sufficiently opposed to mine, but I’m not going to try to convince you that I’m doing you a favor by fighting you. I’m certainly an asshole sometimes, but I at least strive to be an honest asshole.

Well said. I can identify with this part (and it reminds me of mtg's Black). In fact, I would go even further and say that "human values" being maximized by a Singleton forever would importantly fall short of my ideal future.

I basically agree with the rest of the essay, though I certainly feel companionate love. It has a lot of direct and indirect practical benefits (as well as being valuable for its own sake), but also means I have to make tradeoffs to pursue my ambitions (however, my revealed preferences are to follow my ambitions anyway, e.g. moving to Canada to do a PhD). 

some quick thoughts:

It appears that under this pair encoding, each new input would be applied as a two-argument function to  the existing list, when we presumably want it to be fed to the last element of the list in order to continue the stream of output growing to the right. Otherwise there’s effectively still a restriction to finite input, before an infinite output can be produced. 

Assuming that problem were fixed:

Under Vanessa’s distribution on terms, only finite terms will be sampled with probability one, so you’d effectively feed in an infinite sequence of finite terms. 

There’s some flexibility on the input distribution preserving universality; see “Learning universal predictors” theorem 9.

If I had to guess, this is probably enough for universality, but I don’t know this. 

Li and Vitanyi has a section on concrete models or some such that includes a discrete lambda calculus prior (not for induction).

Similar to Wentworth’s advice to ask experts what they are mentally tracking.

I think probabilistic lambda calculus is exactly equivalent to monotone Turing machines, so in the continuous case relevant to Solomonoff induction there is no difference. It’s “unfair” to compare the standard lambda calculus to monotone Turing machines because the former does not admit infinite length “programs.”

Yea, though I walk through the valley of arguments, I will fear no argument, for I understand that adversarially selected reasoning-chains are memetic hazards. 

Still an awesome visual.

I mean, the color wheel is from magic: the gathering, not Duncan Sabien. He just wrote a particular (interesting) take on it. My impression that Mark Rosewater has had the most influence on shaping the philosophy (or at least communicating it).

I still have a couple of years left. I have been advocating human brain uploading / emulation and other forms of rationality enhancement with deep learning lately, and might actually work on a related project this spring, but so far I am still mainly focused on agent foundations.