They’d have taken gold by just standing there and explaining their logic to the judges.

This is a very, very bad idea.

SSDs are permanent flash storage, yes, but that doesn’t mean you can leave them unpowered for extended periods of time.

Without a refresh, electrons can and do leak out of the charge traps that store the ones and zeroes. Depending on the exact NAND used, the data could start going corrupt within a year or so.

HDDs suffer the same problem, though less so. They can go several years, possibly a decade, but you’d still be risking the data on the drive but letting it sit unpowered for an extended time.

For the “cold storage” approach you should really be using something that’s designed to retain data in such conditions, like optical media, or tape drives.

Don’t be obtuse.

There are other concerns with developing space tech besides ones concerning competence and expertise.

Even that is worth questioning, as Russia is suffering historical levels of brain-drain for obvious reasons.

As an infrastructure project its conceptually pretty sick. A nuclear power plant would be fairly ideal for the first long-term human presence on the moon.

The problem is that it’s Russia and China doing it.

It’s to serve as a power source for a potential moon base, apparently.

No. EAC and Battleye developed ways to explicitly support proton, which has to be explicitly enabled by the developer for the game to run.

Proton didn’t change, the popular AC options did. They’ve had proton support pretty much since the steamdeck launched, and it works great as long as the developer of a game bothers checking the checkbox for it.

EAC works on linux just fine, and the fact that Apex runs, means Respawn deliberately allows it.

Satisfactory 1.0 just dropped.

Coffe Stain literally does straight up ASMR trailers sometimes.

Please please please rob Nestle.

The universe doesn’t care, so we have to. If you want humanity to be something that’s worthy of existing, then it’s not optional.

Fine, you don’t have the stamina to care about this because you can’t personally do something about it. That’s ok.

But care about something. Care about not running the water while brushing your teeth for no reason, or about repairing some things you’d normally throw away. Care about being good company for the people you know. Care about doing things better when you spot an opportunity for improvement. Care about not making the lives of your colleagues harder if you can help it. Care about answering the questions of a child with mindfulness and consideration.

You don’t have to care about everything. Everything matters, everything needs improving, but no-one can fix everything so that it’s perfect.

But improve something. Take pleasure in doing it. Not everyone will do the same, but you’ll be one more among millions making the world a little better, instead of worse.

Not to mention that if you’re running a country, someone is going insult you.

Making everyone happy is an impossible ask, so if you can’t settle for the majority being content, and probably not even being that vocal about it, then you should not be governing.

That you insist on finding another window to climb in through when shown the door isn’t as good a look as you seem to think.

…

Why?

Seriously! Why!?

I don’t remotely understand this policy, and it seems that pretty much noone would vote for it if they could avoid doing so.

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.

Agreed.

But it could become one. Aside from private chats where e2ee is manually enabled, it’s all on a server somewhere.

In a couple sentences? In a way that doesn’t approach, equal or exceed the effort of training the model with that data to begin with?

You insist these models can do new things out of nothing, and you keep saying “all you have to do, is give them something”.

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 are completely missing what I’m saying.

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.

Obviously.

But at what point does that guidance just become the dataset you removed from the training data?

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.

Ok.

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.

“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.