Thanks for putting in all this work! Anything related to futamura projections is supercool. 😁

Exercise and a weighted blanket helped me a lot. I also try to limit blue light towards the evening.

Hope you figure it out, insomnia is brutal. 🥲

Sorry, I misread that then.

But isn't it really hard to get >50% then? What was it like with biden last time?

(And don't get me wrong, I'm definitely not looking forward to the coming 4 years.)

Forcing people to vote can also have a bad effect on results.

Here in Belgium we have that and there's a far-right party that get lots of votes because people view it as a "fuck you" vote to the current system (which admittedly does have a lot of flaws).

Power usage / cost per answer for latest models like o3 is very high.

Can't find the picture but power usage of LLMs seems to go up exponentially the bigger the model gets. 😅

I have been catching up on AI developments recently and it's wild how far we have come already.

But I'm also wondering how far LLMs etc can be pushed to the limit. At some point, they need to rethink how these models work..

I followed a copy writing course once and it was eye opening to me. It really put emphasis on writing short, simple sentences.

Maybe these journalists should also start doing that 😅

Typst?

github.com/typst/typst

Oh and if you want all the results that are k steps away from all nodes, you just remove the start node clause in the last rule.

So yes, it does take an iterative approach and we use steps <k to find all intermediate results.

(Technically, you do that too in your approach after every multiply. You just don't look at the intermediate results.)

Datalog inductively reasons about the rules until it finds no other results. So you write down a recursive rule and it automatically expands it recursively. 😄

First rule is the base case, 2nd rule computes all derived results starting from the results of the first.

Ok that is a clever use of math to find the result, need to keep that in mind in the future 😄

Also nice use of rot13 to hide spoilers, i need to start doing that!

It automatically handles transitive edges. And how would you handle it then if you don't increment by 1?

Something to note: Datalogs like Souffle nowadays do a lot of optimizations at compile time. e.g. it will generate a specialized BTree datastructures optimized specifically for relations used in this program. (Even the indices are calculated automatically!)

And that results in very fast programs.

Something like this.. didn't run it or anything so probably contains bugs 😇, but it would give you a rough idea how to tackle it. And there's variations on this depending on the exact problem.

I think this is would be a fairly trivial problem in datalog (e.g. souffle), idk if that's an option for you?

Impressive!

.. or maybe I should just use Lisp 😅