LessWrong 2.0 Reader

Aside from the rare naturally edible-when-ripe cultivar, olives are (mostly) made edible by fermenting and curing them. With salt, yes. And lye, often. Even olives fermented in water are then cured in brine. What saltless olives are you interacting with?

Edit: Also, cooking is very much processing food. It has all the mechanisms to change things and generate relevant pollutants. It changes substances drastically, and different substances differently drastically. Cooking with fire will create smoke, etc. Cooking with overheated teflon cookware will kill your birds. Mechanisms are important.

Very cool! I used to think Hume was the most ahead of his time, but this seems like the same feat if not better.

I think this series might be easier for some to engage with if they imagine Carlsmith to be challenging priors around what AI minds will be like. I don't claim this is his intention.

For me, the series makes more sense read back to front - starting with some options of how to engage with the future, noting the tendency of LessWrongers to distrust god and nature, noting how that leads towards a slightly dictatorial tendency, suggesting alternative poises and finally noting that just as we can take a less controlling poise towards the future, so might AIs towards us. 

I flesh out this summary here: https://www.lesswrong.com/posts/qxakrNr3JEoRSZ8LE/1-page-outline-of-carlsmith-s-otherness-and-control-series [LW · GW]

More procatively I find it rasies questions in me like "am I distrustful towards AI because of the pain I felt in leaving christianity and an inability to trust that anyone might really tell me the truth or act in my best interests, despite many people doing so, much of the time". 

I would enjoy hearing lenses that others found useful to engage with this work through.

Testosterone influences brain function but not so much general IQ. It may influence to which areas your attention and thus most of your learning goes. For example, Lower testosterone increases attention to happy faces while higher to angry faces. 

Depending on what one means by 'learn' this is provably impossible. The reason has nothing to do with the transformer architecture (which one shouldn't think of as a canonical architecture in the grand scheme of things anyway).

There is a 2-state generative HMM such that the optimal predictor of the output of said generative model provably requires an infinite number of states. This is for any model of computation, any architecture.

Of course, that's maybe not what you intend by 'learn'. If you mean by 'learn' express the underlying function of an HMM then the answer is yes by the Universal Approximation Theorem (a very fancy name for a trivial application of the Stone-Weierstrass theorem).

Hope this helped. 😄

$\omega$ isn't a reference frame; rather, if $\psi$ is a world then ${\omega }^{-1}\left(\right\{\psi \left\}\right)$ aka $\{\iota \in I\mid \omega (\iota )=\psi \}$ are the reference frames for $\psi$.

Essentially when dealing with generalized reference frames that contain answers to questions such as "who are you?", the possible reference frames are going to depend on the world (because you can only be a real person, and which real people there are depends on what the world is). As such, "reference frames" don't make sense in isolation, rather one needs a (world, reference frame) pair, which is what I call an "interpretation".

Thanks, didn't know about the low basis theorem.

U axiomatizes a consistent guessing oracle producing a model of T. There is no consistent guessing oracle applied to U.

In the previous post I showed that a consistent guessing oracle can produce a model of T. What I show in this post is that the theory of this oracle can be embedded in propoaitional logic so as to enable provability preserving translations.

LS shows to be impossible one type of infinitarian reference, namely to uncountably infinite sets. I am interested in showing to be impossible a different kind of infinitarian reference. "Impossible" and "reference" are, of course, interpreted differently by different people.

Is there some theoretical result along the lines of "A sufficiently large transformer can learn any HMM"?