From a model-checking point of view. This is about taking a proof-theoretic approach...

Your last paragraph is also quite wrong: a machine learning could very well easily learn and solve an NP-complete problem, because this property does not say anything about average case complexity (and we should consider Probabilistic complexity classes, so the picture is even more "complex").

>The problem with those methods is that they're inference time

I agree, I just thought it was missing some prior art (not affiliated with these papers :-P)

What is not clear to me at all is, is this the draft of a research idea? Or is there already some implementation coming in a later post?

It seems to me that such an idea would be workable on a given language with a given type system, but it seems to me there would be a black magic step to train a model that would work in a language-agnostic manner. Could you clarify?

Then it switches to using an encoding that would be more semantic, but I think the argument is a bit flimsy: it compares chess to the plethora of languages that LLM can spout somewhat correct code for (which is behind the success of this generally incorrect approach). What I found more dubious is that it brushed off syntactical differences to say "yeah but they're all semantically equivalent". Which, it seems to me, is kind of the main problem about this; basically any proof is an equivalence of two things, but it can be arbitrarily complicated to see it. If we consider this problem solved, then we can get better things, sure...

I think without some e.g. Haskell PoC showing great results these methods will have a hard time getting traction.

Please correct any inaccuracies or incomprehension in this comment!

Honestly I hope that the AI filter would be much better in terms of false positive than the aforementioned one, if only because it should be easier via statistical methods.

There are variations of this, such as composition theory in art getting good results based on completely false assumptions, but these tend to fall under epistemic underdetermination.

I didn't think "There Is No Antimemetics Division" did very well with its premise, but the premise is quite fascinating, and it's the closest I've seen to this concept. Are there other explorations of similar ideas?

I discussed with a painter in the artistic lineage of Shi Guoliang, and he told me he remembered how much that could be seen as "Western art painted with a Chinese brush". I think the criticism was more directed towards such painters than say the Lingnan school that explicitly sought to revitalize Chinese painting through foreign influences, because it's really in the foundations of the painting -- how perspective and light are tackled through the 'scientific' system rather than the elaborate symbolic system of classical painting.

While this is a noble goal, it seems obvious that this isn't how it usually goes. For instance, "free market" is often used as a dogma against companies that are actively harmful to society, as "globalization" might be. An unstoppable force, so any form of opposition is "luddite behavior". Another one is easier transport and remote communication, that generally broke down the social fabric. Or social media wreaking havoc among teen's minds. From there, it's easy to see why the technological system might be seen as an inherent evil. In 1872's Erewhon, Butler already described the technological system as a force that human society could contain as soon as it tolerated it. There are already many companies persecuting their employees for not using AI enough, even when the employee's response is that the quality of its output is not good enough for the work at hand, rather than any ideological reason.

I'm neither optimistic nor pessimistic about the changes that AI might bring, but hoping it to become "human-centered" seems almost as optimistic as hoping for "humane wars".

Given the nature of the medium, you can tackle a theme (space invaders), and even a story on top of it. This is good for critics; they know stories, they know that books are the highest form of art for intellectuals. The currency of critics in the system (media/advertisement/entertainment industry loop) is credentialism -- except for purely independent critics you have their own platform and exist through a complex bidirectional relationship with their audience.

However, the story is almost always at odds with gameplay. A story limits the freedom the gameplay system can respond to the player by railroading certain outcomes. Often, adapting a story implies different scenes that cannot fit into a game genre, so it's more appropriate to a collection of mini-games rather than what people generally consider to be a game. Video-game stories tend towards tropes that don't cause such problems for itself, such as the 'big tournament' arc. Of course, certain genres have much more freedom (RPGs), but still a definite story means certain characters can't or have to die, etc, which remove the meaning of player choices.

The mastery approach hasn't gone away. But critics hate it; the general philosophy of the industry is inclusivity, which is at direct odds with a competitive direct ranking of players according to skills. It requires effort, and rewards innate ability -- reflex, memory, ability to make mental computations, ... are all advantages that generally directly translate into in-game advantages. So the critics industry had been relentless at disparaging the games that directly emphasized mastery (arcade designs, the infamous 'God Hand' review) and elevate what are generally called 'movie-games' that have worked at eliminating these aspects ('Last of Us', later 'God of war') to let all players experience the story fully without interacting with the gameplay in any meaningful manner. They had to compromise because of the success of Dark Souls that brought mastery back to the forefront, but this is where the total incompetence of mainstream critics is truly glaring (see the infamous 'Cuphead' journalist moment). As a result, their critiques are rarely anything more than press releases with a final score based on production value and not based on any insight into the depth of game mechanics and systems.

I'm surprised not to see Chris Crawford mentioned, as The Art of Computer Game Design (1984) makes the central point of this article at the very beginning, and is a primary source of video-game critique.

It's a nice trick to play around, but that limits its usefulness.

Whats bad about: RMS Not making a decent argument make your position look unserious

The objection that is generally made to RMS is that he is 'radically' pro-freedom rather than be willing to compromise to get 'better results'. This is something that makes sense, and that he is a beacon for. It seems such argument weaken even this perspective.

I feel that's the lesson anyone who toyed with libertarians ideals ultimately come to. It just takes a bit longer for some than others. It's also harder to realize if you're making mad bank on it, rather than be part of the idiots who blew their hard-earned money on some technical misunderstanding, scam, or retro-active regulation.

https://woolion.art/assets/img/ai/ai_editing.webp

It's original, ChatGPT, Flux.

Still, you can see that ChatGPT just throw everything out and does not do a minimal attempt at respecting style. Flux is quite bad, but it follows the design much more (although it gets completely confused by it) that it seems that with a whole lot of work you could get something out of it.

If you look for example at "Mermaid Disciplinary Committee", every single image is in a very different style, each that you can consider a default of what the model assume would be for the specific prompt. It's quite obvious that these styles were 'baked in' the models, and it's not clear how much you can steer in a specific style. If you look at "The Yarrctic Circle", a lot more models default to a kind of "generic concept art" style (the "by greg rutkowski" meme) but even then I would classify the results as at least 5 distinct styles. So for me this benchmark is not checking style at all, unless you consider style to be just around 4 categories (cartoon, anime, realistic, painterly).

So regarding image editing, I did my own tests at the first release of Flux tools, and found that it was almost impossible to get any decent results on some specific styles, specifically cartoon and concept art styles. I think the tools focus on what imaginary marketing people would want (like "put this can of sugary beverage into an idyllic scene") rather than such use cases. So editing like "color this" or other changes would just be terrible, and certainly unusable.