It explains why the image is so grainy. At first I was confused what that stripe to the left and the bottom was. But it’s just the window edge, and the noise isn’t stars.

Don’t you see the reflection of the studio lighting in the middle?

of course they are sore losers

Regarding Russell’s paradox, its dual is also interesting: Consider the set D := { s | s ∈ s }, the set of sets that do contain themselves. Does D contain itself? It might or it might not, neither causes a contradiction. Tnis shows that you don’t need an antinomy for a set comprehension to be ill-defined.

> Something is only a crime if someone is willing to prosecute people for it.

The International Criminal Court is more than willing: https://www.icc-cpi.int/about/otp

AFAIK the ICC has not gone after the US, EU, UK. Basically just African warlords and some old fallout from WWII. And of course a leader can sanction the ICC [1] and the US military would take them into custody.

[1] - https://www.whitehouse.gov/presidential-actions/2025/02/impo...

People keep being amazed that Turing-complete mechanisms can run any program. ;)

Courtesy of Google: https://glennklockwood.com/garden/Azure-SmartNIC

Restricting such access it is still a work in progress: https://wicg.github.io/local-network-access/

Regarding chips, the dependency is more distributed (TSMC isn’t in the US), and also somewhat mutual (ASML). Software and services is more one-sided.

What Gödel showed is that (in any sufficiently powerful formal axiomatic system) the set of provable statements isn’t the same as the set of true statements. This means that either there are true statements that aren’t provable (incompleteness), or that there are provable statements that aren’t true (inconsistency), or both.

One way to see this is via the halting problem. For any program (with a fixed input), there is a truth of the matter of whether it will eventually halt or not. In the formal system, for every (Turing-machine) program P we can define a function s_P(n) that gives us the state of the program after n steps (by recursive definition). Then we can write for any program P the statement H(P) = “there exists a natural number n such that s_P(n) is a halting state”. Furthermore, we can write a program R that, given any program P as input, enumerates all proofs of the formal system (this is possible because proofs are strings, and we can write a program that enumerates all strings) and that for each proof checks if it is a proof of H(P) or of not H(P), and if it finds such a proof, stops and outputs the result (P halts or doesn’t halt). If such a proof exists, then R will eventually find it. And if R would find a proof for any P, then this would solve the halting problem.

But we know that the halting problem is undecidable, which means that there must be programs P for which there is neither a proof of H(P) nor of not H(P). This shows that there are truths (the program will halt or won’t halt) for which there is no proof in the formal system; or alternatively, that the formal system is inconsistent and proves falsities.

It’s also blue, not green.