Twofold: One, they lost a case in arbitration that basically said arbitration isn’t usable.
Two: Lot of companies do arbitration to avoid court, which works fine and is cheaper if you’re not getting taken to court much. If 75,000 people that could do a class action suit all go to arbitration though, the benefit is lost. Lawyers threatened that. 3 grand a arbitration case x 75,000 people == 225 million dollars on fees alone.
its not exactly for the positive reason you think. theyre trying to prevent the class action lawsuit going around the (UK?) right now and realized when a certain amount of people take the arbitration, it gets fairly costly, so they reverted on that clause.
regardless fuck arbitration, its like paying off judges but even more transparent about it.
its basically doing the right thing for the wrong reason (reverting arbitration cause not for thr consumer, but for their wallets)
Valve's contributions have singlehandedly revolutionized the Linux gaming scene. They're the only reason I can play most of the games I own. I don't worship them, exactly, but I do think very highly of them.
This for sure. Making games easily accessible on linux have lead to a lot of people not having to deal with windows anymore.
It is the same effect as a kidnapping victim beeing grateful when someone comes to release them fom the torture rack. It is not strange that valve gets a lot of goodwill from their actions.
Would i sish more people did as steam does? Ofcourse! But none do, so we are grateful for steam. I think they saved pc gaming. And not only for linux.
Before proton we used wine. And wine will continue development with or without steam.
If anything the open source community did more and gave steam a firm platform to build on.
Edit: And to add an observation steams push for Linux is a reaction to Microsoft becoming a contender in the PC games market place. Its not for our benefit anymore than for valves.
I’m pretty wary of corporate propaganda, but from the article this sounds like a pretty clear case of some greedy people taking advantage of Valve offering to cover all arbitration costs. Yes, they’re doing this to cover their ass, but it’s not a malicious move and I don’t see how it could be interpreted as anti-consumer.
I mostly like Valve, and agree that going too far with Stan-ing over a company is dumb. However I think the majority of people that tend to greatly support Valve comes down to both pushing tech and games forward into better consumer directions, and that they are currently not joining in on the mass enshittification as other companies (but of course all big companies can and will do some level of that given enough time).
With regards to pushing tech, they have done more (in at least the last 10 years) to force Linux to be seen as worth supporting. Their efforts to actually add to projects that were already around has been game changing. And that they kept actually putting time, money, and resources into it even after their initial efforts with Steam Machines and the original SteamOS didn’t gain traction on a mainstream level. The Steam Deck keeps outshining the other options even while being technically less powerful specs and they are putting work in to make sure things like drivers are released to help people that choose to install Windows.
But all the positive stuff will only keep happening so long as people don’t start feeling locked out or cheated. I forget a lot of the time how bad many users hated them back when the original versions of Steam were released. Many of the issues people had and were concerned about were valid and could have tanked Valve if they didn’t do everything they could to address them. If they start pulling shit like EA or really any of the console companies have done. Then it will be their time to see massive losses and get all the hate that is deserved.
I would if it had any lasting power. I mean, can’t they just push out another eula update 6 months from now when this change is no longer useful to them?
Fuck arbitration, of course, I’m just not expecting this to really mean anything.
Big win for consumers, at least in the US. People tend to do better in courts here than they do in arbitration (where one side pays the judge(arbitrator)).
"Specifically, the named Plaintiffs won binding decisions from arbitrators rendering Valve's arbitration provision unenforceable for both lack of notice and because it impermissibly seeks to bar public injunctive relief."
So none of these stupid clauses are valid? FOO FYEAH!
A friend of mine bought one at MSRP to add to his collection along with the likes of Anthem and Babylon’s Fall. He also picked up Suicide Squad for this reason, but he found that he unironically really enjoys that game while it’s still operational.
Right? For a game to be a collector’s item, it needs to still be able to function in its intended capacity. Additionally, they need to be considered good. Most games that become a collectable do so when they transition into the “classic” category, usually 20+ years after they released. In 2050, no one’s going to think, “Oh man, Concord was hailed as a masterpiece in its day, I need to own that piece of history!”
“The potential here is absurd,” wrote app developer Nick Dobos in reaction to the news. “Why write complex rules for software by hand when the AI can just think every pixel for you?”
“Can it run Doom?”
“Sure, do you have a spare datacenter or two full of GPUs, and perhaps a nuclear powerplant for a PSU?”
What the fuck are these people smoking. Apparently it can manage 20 fps on one “TPU” but to get there it was trained on shitload of footage of Doom. So just play Doom?!
The researchers speculate that with the technique, new video games might be created “via textual descriptions or examples images” rather than programming, and people may be able to convert a set of still images into a new playable level or character for an existing game based solely on examples rather than relying on coding skill.
It keeps coming back to this, the assumption that these models, if you just feed them enough stuff will somehow become able to “create” something completely new, as if they don’t fall apart the second you ask for something that wasn’t somewhere in the training data. Not to mention that this type of “gaming engine” will never be as efficient as an actual one.
I mean, you’ve never seen a purple elephant with a tennis racket. None of that exists in the data set since elephants are neither purple nor tennis players. Exposure to all the individual elements allows for generation of concepts outside the existing data, even though they don’t exit in reality or in the data set.
Try to get an image generator to create an image of a tennis racket, with all racket-like objects or relevant sport data removed from the training data.
Explain the concept to it with words alone, accurately enough to get something that looks exactly like the real thing. Maybe you can give it pictures, but one won’t really be enough, you’ll basically have to give it that chunk of training data you removed.
That’s the problem you’ll run into the second you want to realize a new game genre.
There are more forms of guidance than just raw words. Just off the top of my head, there’s inpainting, outpainting, controlnets, prompt editing, and embeddings. The researchers who pulled this off definitely didn’t do it with text prompts.
But at what point does that guidance just become the dataset you removed from the training data?
The whole point is that it didn’t know the concepts beforehand, and no it doesn’t become the dataset. Observations made of the training data are added to the model’s weights after training, the dataset is never relevant again as the model’s weights are locked in.
To get it to run Doom, they used Doom.
To realize a new genre, you’ll “just” have to make that game the old fashion way, first.
Or you could train a more general model. These things happen in steps, research is a process.
I know the input doesn’t alter the model, that’s not what I mean.
And “general” models are only “general” in the sense that they are massively bloated and still crap at dealing with shit that they weren’t trained on.
And no, “comprehending” new concepts by palette swapping something and smashing two existing things together isn’t the kind of creativity I’m saying these systems are incapable of.
Bloated, as in large and heavy. More expensive, more power hungry, less efficient.
I already brought it up. They can’t deal with something completely new.
When you discuss what you want with a human artist or programmer or whatever, there is a back and forth process where both parties explain and ask until comprehension is achieved, and this improves the result. The creativity on display is the kind that can unfold and realize a complex idea based on simple explanations even when it is completely novel.
It doesn’t matter if the programmer has played games with regenerating health before, one can comprehend and implement the concept based on just a couple sentences.
Now how would you do the same with a “general” model that didn’t have any games that work like that in the training data?
My point is that “general” models aren’t a thing. Not really. We can make models that are really, really big, but they remain very bad at filling in gaps in reality that weren’t in the training data. They don’t start magically putting two and two together and comprehending all the rest.
You keep moving the goal posts and putting words in my mouth. I never said you can do new things out of nothing. Nothing I mentioned is approaching, equaling, or exceeding the effort of training a model.
You haven’t answered a single one of my questions, and you are not arguing in good faith. We’re done here. I can’t say it’s been a pleasure.
My argument was and is that neural models don’t produce anything truly new. That they can’t handle things outside what is outlined by the data they were trained on.
Are you not claiming otherwise?
You say it’s possible to guide models into doing new things, and I can see how that’s the case, especially if the model is a very big one, meaning it is more likely that it has relevant structures to apply to the task.
But I’m also pretty damn sure they have insurmountable limits. You can’t “guide” and LLM into doing image generation, except by having it interact with an image generation model.
To be fair, half of the AAA gaming industry is all about trying to clone the latest successful game with a new coat of paint. Maybe using AI to make these clones will mean that the talented people behind the scenes are free to explore other ideas instead.
Of course in reality, it just means that the largest publishers will lay off a whole lot of people and keep churning out these uninspired games in the name of corporate profits, but it’s nice to dream sometimes.
This is perfect for capitalism with Matrix bio-fuel-cells-human/battery tech!
It would have been too easy to just chill peacefully and unbothered in my cozy pod - they would feed me a hallucination of a dead-end job the whole time, complete with all the stupid office buttons I have to press.
It’s basically like. Someone drawing a picture. Then watching the buttons you’re pressing on a controller. And then drawing a new picture. And based on the game that they think you’re playing in their head trying to guess what the next picture ought to look like. With no error correction and no conceptualization other than what the next picture should look like.
The… many limitations of this is the inability of image generators to rationalize 3 dimensional space. It can only approximate it based on what it thinks should appear on the screen. It lacks any ability to keep track of variable information. It really is more like a Doom-style hallucination than anything else. Some of the videos on that article are truly bizarre looking. I’d imagine after a few minutes every single one of them would devolve into an endless loop of being trapped in non-sensical geometry or killing the same enemy over and over again as the AI has no way of remembering the enemy existed to begin with, let alone that you killed it.
I’ll be honest I don’t think there is much use in this at all. It suffers from the same limits as any other model AI. Believability at a glance is not believability under scrutiny and if it’s only believable at a glance then there’s not much practical use in it. The advance in computational power and model sophistication required to stand up under scrutiny is massive.
arstechnica.com
Aktywne