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Why wouldn't this construction work over a continuous space?
faul_sname on Planning in a Lattice GraphDo you want me to spoil it for you, do you want me to drop a hint, or do you want to puzzle it out yourself? It's a beautiful little puzzle and very satisfying to solve.
avturchin on Magic by forgettingPresumably in deep meditation people become disconnected from reality.
avturchin on Magic by forgettingYes it is easy to forget something if it does become a part of your personality. So a new bad thing is easier to forget.
jessica-liu-taylor on Bayesian inference without priorsI 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.
avturchin on Magic by forgettingThe number of poor people is much larger than billionairs. So in most cases you will fail to wake up as a billionaire. But sometimes it will work and it is similar to law of attraction. But formulation via forgetting is more beautiful. You forget that you are poor.
bhauth on social lemon marketsYou're mistaken about lemon markets: the initial fraction of lemons does matter. The number of lemon cars is fixed, and it imposes a sort of tax on transactions, but if that tax is low enough, it's still worth selling good cars. There's a threshold effect, a point at which most of the good items are suddenly driven out.
avturchin on Magic by forgettingI can forget one particular thing, but preserve most of my selfidentification information
alexander-gietelink-oldenziel on Examples of Highly Counterfactual Discoveries?Did I just say SLT is the Newtonian gravity of deep learning? Hubris of the highest order!
But also yes... I think I am saying that
This doesn't get into the groundbreaking upcoming new work by Simon-Pepin Lehalleur recovering the RLCT as the asymptotic dimension of jet schemes around which suggest a much more mathematically precise conception of basins and their breadth.
zac-hatfield-dodds on Towards Monosemanticity: Decomposing Language Models With Dictionary LearningIt's a sparse autoencoder because part of the loss function is an L1 penalty encouraging sparsity in the hidden layer. Otherwise, it would indeed learn a simple identity map!