Thanks for the yearly update! I have some thoughts on why we care about string diagrams and commutative diagrams so much. (It's not even just "category theory".) I'll poke you later to talk about them in greater depth but for quick commentary:

For string diagrams it's something like "string diagrams are a minimal way to represent both timelike propagation of information and spacelike separation of causal influence". If you want to sketch out some causal graph, string diagrams are the natural best way to do that. From there you start caring about monoidal structure and you're off to the races.

For commutative diagrams the story is different but related, though admittedly I understand what's going on with [commutative diagrams]+[sparse activations] way way less. I'd say it's something like "the existence of a satisfied commutative diagram puts strong constraints on other aspects of the neural net, like what form the latent space(s?) and maps to and from them have to look like and what they have to do and what information has to get preserved or discarded".

For one last observation, a friend's been poking me about the sense that constraints and equipartition/environment are dual to each other, and that there's a correspondence (for bounded systems at least) between phase volume size-change and the sign of something like an informational analogue to thermodynamic temperature. (And also that your approach is importantly incomplete in currently only dealing in theory and not engineering, but for my part I think that that's priced in to how you talk about your plan.)

Bother me on Discord?

+1 this. Wouldn't it work pretty much just as well if not better to just, like... eat a spoonful of honey under those circumstances?

An intriguing attempt to cash out semantics in a gearsy way, of a kind I haven't seen anywhere else but personal notes and a single much less gearsy research paper. This ended up seizing my attention during a summer research program and made me believe in the explainability of nearly all things and the tractability of all simply-explainable open questions once again. "What followup work would you like to see building on this post?" Yes. My answer to that is "yes".

A concise breakdown of what I'd call a type of development trap - a way in which you can end up pushed back down into a dire bootstrapping problem. I might want to see a larger taxonomy of those, but that's not what this was for.

True, useful, and inspiring. It led me to make my own variation on them, made me realize a way that my brief teaching career might have been more comfortable, and ultimately led me to write up a brief post. I still carry one around. I'd hoped other people might also start making these for themselves, and improving on the technology, but that largely hasn't happened.

I'm sorry to hear about the social drama and the depressive spiral both. I can't know how you feel but I've been nearby, at least. For my part, I very nearly did Inkhaven, and I'm very glad that it happened. From all accounts and everything I've observed, you did an incredible job organizing it, you were probably majorly responsible for most of the weird wonderful things I glimpsed that happened within it, and I moderately strongly regret not having taken part. Cheers!

Having participated in the Half-Haven discord for the past two months, I have written ~28 blog posts as of today, and am on track to complete the 30 posts in 2 months goal.

Wait, is that why it's called Halfhaven???

Thief With Access To The Real Diamond

That leaves a gap between cases in which the thief has access to the predictor/planner/reporter (which run into the diagonalization barrier), and cases in which the thief doesn’t even have detailed information about the diamond (in which case we can solve the problem). In between those, the thief has arbitrarily good information about the diamond, but does not have access to the predictor/planner/reporter.

For this case, I do not have a solution, but I do expect that it’s solvable-in-principle.

The main difficulty in these cases is that the $P\left[Obs|do\right(A^{\ast }\left)\right]$ may be exactly the same between action-plans $A^{\ast }$ which result in the diamond being stolen, and action plans which do not. The thief has enough information to make the predicted sensor readings completely identical between the two cases.

The reason the problem might still be solvable-in-principle is that the actions $A^{\ast }$ still give us information about whether the diamond was stolen. But we somehow have to extract that information in a way which does not require any difference whatsoever between the observation-distributions in the two cases.

I was chewing over the ELK problem this morning and had a silly idea here. What if you deliberately introduce a specific inaccuracy in the camera, or the reporter? Have some timestamp or watermark or scratch, something that has to do with the system's perception of the diamond and which would not be known from mere access to the diamond or at least be very expensive to fake.

Thanks for the post! It makes me wonder whether hyperfinite quantification and hyperreal truth values handle Yablo-esque paradoxes too, but I haven't thought about that much at all yet.

This is an important bit of clarification! You can do some entertaining countersignaling with a nice suit jacket and an unbuttoned button-down.