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.
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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.
It's pretty obvious that OpenAI is terrible at it -- it is known for its unmissable touch. However, for Flux it really depends on the style. They already posted at some point that they changed their training to avoid averaging different styles together, which is the ultimate AI look. But this is at odds with the goal to directly generate images that are visually appealing, so the style matching is going to be a problem for a while, at least.
There are Gitops solution that give you all the benefits that are promised by it, without any of the downsides or compromises. You just have to bite the bullet and learn kubernetes. It may be a bit more of a learning curve, but in my experience I would say not by much. And you have much more flexibility in the precise tech stack that you choose, so you can reduce it by using stuff you're already know well.
Do you have something like that to manage the group dynamics?
Also in terms of personalities, I'm guessing the most appropriate way to get the list of prompts would be to run an analysis on the hn dataset to classify user behaviour patterns and create the prompts according to this. Since you can match these to posts in thread, you can also get a rough approximation of the dynamics distribution. Did you do such an analysis?
The advantage is that it's limited, so it greatly reduces the wall of difficulty to manage to get some 'nice-sounding' music (mostly the restriction to the pentatonic scale). However, kids still manage to find the most horrible-sounding settings, and insist on keeping them as is...
To guess it, I looked at 'crab' because it's a quite uncommon that has some deep relationship with a few words only. Then checked the most obvious one (which was the solution) against the other words, and determined that it didn't bear any significant relationship to the third word. So I checked the other (less obvious) potential solutions, and after a frustrating lack of match, I gave up. And then got annoyed that the first candidate was the right one. To be fair, I guess it's partly because I'm an ESL, as I think that solution/sauce can be used as a nominative locution enough to form a "special relationship".
To be a designer, you have to play with people's (as in general crowd, not individuals) general understanding of the subject. In particular, that means avoiding the curse of knowledge, and yes for normal people PC meant "not Apple consumer product". So ultimately, the search algorithm includes:
- categorize all relationships between words, ranked by strength
- compare with what is expected to be known in popular culture (adjust ranks)
- match against the designer's expectations of similar problems (look for clues to pick a best match)
It's a lot of words to say it's the opposite of a aha moment, the result of a pure computational problem, that is often quite frustrating. Thank you for coming to my TED talk.
It's disheartening because now I will look much more into reputable publishers, and so filter off independent writers who have nothing to do with this.
Lowering the investment to understand a specific paper could really help focus on the most relevant results, on which you can dedicate your full resources.
Although, as of now I tend to favor approaches that only summarize rather than produce "active systems" -- with the approximate nature of LLMs, every step should be properly human reviewed. So, it's not clear what signal you can take out of such an AI approach to a paper.
Related, a few days ago: "Show HN: Asxiv.org – Ask ArXiv papers questions through chat"
https://news.ycombinator.com/item?id=45212535
Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning
I believe that detecting whether an ad is clickbait is a similar problem -- not exactly the same, but it suffers from the same issues:
- it's not well defined at all.
- any heuristic is constantly gamed by bad actors
- it requires a deeper, contextual analysis of the content that is served
- content analysis requires a notion of what is reputable or reasonable
If I take an LLM's definition of "clickbait", I get "sensationalized, misleading, or exaggerated headlines"; so scams would be a subset of it (it is misleading content that you need to click through). They do not provide their definition though.
So you have Google products (both the Products search and the general search) that recommend scams with an incredible rate, where the stakes are much higher. Is it reasonable that they're able to solve the general problem? How can anyone verify such a claim, or trust it?
For fuel, Google results were 90% scams, for coffee machines closer to 75% The scams are fairly elaborate: they clone some legitimate looking sites, then offer prices that are very competitive -- between 50% and 75% of market prices -- that put them on top of SEO. It's only by looking in details at contact information that there are some things that look off (one common thing is that they may encourage bank transfers since there's no buyer protection there, but it's not always the case).
A 75% market rate is not crazy "too good to be true" thing, it's in the realm of what a legitimate business can do, and with the prices of the items being in the 1000s, that means any hooked victim is a good catch. A particular example was a website copying the one for a massive discount appliance store chain in the Netherlands. They had a close domain name, even though the website looked different, so any Google search linked it towards the legitimate business.
You really have to apply a high level of scrutiny, or understand that Google is basically a scam registry.
Looking at the original claim, we can take from birds a number of optimization regarding air flows that are far beyond what any plane can do. But, the impact that could be transfer to planes would be minimal compared to a boost in engine technology. Which is not surprising since the way both systems achieve "flight" are completely different.
I don't believe such discourse would happen at all if it was just considered to be a number of techniques, of different categories with their own strength and weaknesses, used to tackle problems.
Like all fake "laws", it is based on a general idea that is devoid of any time-frame prediction that would make it falsifiable. In "the short term" is beaten by "in the long run". How far is "the long run"? This is like the "mean reversion law", saying that prices will "eventually" go back to their equilibrium price; will you survive bankruptcy by the time of "eventually"?
However, you'll probably get an angry answer that it's management fault, or something of the sort, that is to blame (because there isn't enough time). Responsibility would have to be taken up before in pushing back if some objectives truly are not reasonable.