l'empathie mécanique @dpwiz@qoto.org

@jwcph @Kjaerulv Well, technically it would be something along the lines of "iterative improvement under external scoring". But I don't quite see the difference when not looking at implementation details.

Visibility is surprisingly tricky. Lots of implementation options, semantic options and how to combine those

#Haskell #gamedev

@jwcph @Kjaerulv But selection for intelligence (as a property that allows solving diverse and open-ended problems) is literally how those models are popping up in a first place.

And yes, the AIs are different. First, they grow intelligent, then... We die... Unless humanity manages to coordinate away from rushing down this cursed trench we're in, and climb outside, towards caring.

@Kjaerulv I don't think the blood temperature is relevant at all. Either an agent, be it human or organization, natural or artificial, brings forth your values, or they don't. And then it is a question about the values.

@Kjaerulv rationalism doesn't have to be cold blooded. Not unless you don't value having warm blood.

@reidrac@social.sdf.org It's not like you're adding Taylor series and FFTs as a primitive. Although I'm now curious to look at a console where those guys ARE the primitives ops, forcing authors to performs backflips through fiery numeric rings (and fields)

@reidrac@social.sdf.org IMO having modular division (div/mod/fract) available opens up a good amount of interesting hacks and tricks without making it *too* easy.

Switched to map and contour generation from quad tree cells. Those are now correctly represent terrain transitions, not only passable regions.

The thing is more costly to construct, but the map filling is much faster than sampling each tile corner - less duplicate work and big chunks of uniform terrain are naturally aggregated and can be dispatched as one job.

Out of 1M tiles only ~75k are 1-tile transitions that are processed sequentially (presumably while some bigger jobs are chugging in background).

#Haskell #gamedev

I really should do that final tagless retargetable encoding for SDFs and run those on GPU instead.

I hope I won't burn my laptop with extreme parallel* load
Missing my old R7 5900 battlestation...

(* thanks `GHC.Conc` and `scheduler`!)

@RL_Dane @Deuchnord Rust is okay, but but I like Haskell because it is more high-level

@reidrac@social.sdf.org You can chose one of the bits to stand for transparency flag. And another for collision checking. Still, 2 more bits for user data. Alternative - 3-bit collision mask.

@isagalaev If that is indeed their ~~plan~~ blueprint for comprehensive regulation touted at that interview then there would be no voters to get mad. Alas, no profits either.

@timbray I wander what its failure mode would be when the "thinkers of the children" would come for its bacon.

Okay, the numbers level out (with a slight advantage for the Free) when its sampling function becomes complicated (a primitive SDF vs a stack of 100 primitives). I'm now more sure that I'm measuring some right thing, and not some laziness fluke.

Added bisimulation tests for the Free re-implementation (found 2 bugs ) and got to benchmarking the thing.

I was surprised that a round dance of 3 functors and a ping-pong of functions that pass control around is not only "a little slower" than a tight package, but instead twice as fast!

@haskman Why do you even want to consider laziness at a review time? Without a profiler/benchmark data you can't point a finger at the expression and say "there's laziness in there, make it strict to go faster" on a hunch. It may as well go slower.

@haskman #Haskell needs to become a better Haskell, not a better Python, or a better Rust, or a better PureScript.

@haskman But anyway, I think that questioning laziness is barking up the wrong tree. What we should strive for is not strictness, but a better tooling that will answer the challenges of performance and legibility "in the large".

Otherwise we're end up in competition with the other more established languages and their outgrown ecosystems instead of walking on our strong foot.