Jessica Taylor. CS undergrad and Master's at Stanford; former research fellow at MIRI.
I work on decision theory, social epistemology, strategy, naturalized agency, mathematical foundations, decentralized networking systems and applications, theory of mind, and functional programming languages.
Blog: unstableontology.com
Twitter: https://twitter.com/jessi_cata
I think you are assuming something like a sublinear utility function in the difference (quality of own closed model - quality of best open model). Which would create an incentive to do just a bit better than the open model.
I think if there is a penalty term for advancing the frontier (say, for the quality of one's released model minus the quality of the open model) that can be modeled as dividing the revenue by a constant factor (since, revenue was also proportional to that). Which shouldn't change the general conclusion.
It seems this is more about open models making it easier to train closed models than about nations vs corporations? Since this reasoning could also apply to a corporation that is behind.
Thanks, fixed.
I don't see how this helps. You can have a 1:1 prior over the question you're interested in (like U1), however, to compute the likelihood ratios, it seems you would need a joint prior over everything of interest (including LL and E). There are specific cases where you can get a likelihood ratio without a joint prior (such as, likelihood of seeing some coin flips conditional on coin biases) but this doesn't seem like a case where this is feasible.
The axioms of U are recursively enumerable. You run all M(i,j) in parallel and output a new axiom whenever one halts. That's enough to computably check a proof if the proof specifies the indices of all axioms used in the recursive enumeration.
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 propositional 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.
Regarding quantum, I'd missed the bottom text. It seems if I only read the main text, the obvious interpretation is that points are events and the circles restrict which other events they can interact with. He says "At the same time, conspansion gives the quantum wave function of objects a new home: inside the conspanding objects themselves" which implies the wave function is somehow located in the objects.
From the diagram text, it seems he is instead saying that each circle represents entangled wavefunctions of some subset of objects that generated the circle. I still don't see how to get quantum non-locality from this. The wave function can be represented as a complex valued function on configuration space; how could it be factored into a number of entanglements that only involve a small number of objects? In probability theory you can represent a probability measure as a factor graph, where each factor only involves a limited subset of variables, but (a) not all distributions can be efficiently factored this way, (b) generalizing this to quantum wave functions is additionally complicated due to how wave functions differ from probability distributions.
For corporations I assume their revenue is proportional to f(y) - f(x) where y is cost of their model and x is cost of open source model. Do you think governments would have a substantially different utility function from that?