Jamie

u/Jamie@jamie.moe
5 posts · 448 comments

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on Ctrl+Alt+T · c/linuxmemes · 2 pts · 2y

At the time I decided on it, I used Sakura as a terminal emulator, plus it's on the home row. I use a different term emulator now, but the muscle memory remains.

Interesting to find a RyanF9 video here and not in a motorcycle community. But yeah, probably most people here don't have much interest in Gore-Tex unless they ride or do other outdoorsy things.

The only thing more eco-friendly than buying an eco-friendly printer, is to not buy a new printer at all.

Both of my local libraries offer printing at $0.25 a page. For photos, I just go to the photo lab at the store and print them there.

Both are cheaper than owning a printer unless you're doing a ton of it, and in the former case, I get to support a library just a little bit.

Speaking for LLMs, given that they operate on a next-token basis, there will be some statistical likelihood of spitting out original training data that can't be avoided. The normal counter-argument being that in theory, the odds of a particular piece of training data coming back out intact for more than a handful of words should be extremely low.

Of course, in this case, Google's researchers took advantage of the repeat discouragement mechanism to make that unlikelihood occur reliably, showing that there are indeed flaws to make it happen.

Accumulated knowledge in our society really is frail. Take a computer mouse, tons of people are involved in making them, they're considered extremely simple tools. Yet not one person on the planet could go out into nature, get the natural resources required, and without help turn those resources into a working computer mouse.

I'm not an expert, but I would say that it is going to be less likely for a diffusion model to spit out training data in a completely intact way. The way that LLMs versus diffusion models work are very different.

LLMs work by predicting the next statistically likely token, they take all of the previous text, then predict what the next token will be based on that. So, if you can trick it into a state where the next subsequent tokens are something verbatim from training data, then that's what you get.

Diffusion models work by taking a randomly generated latent, combining it with the CLIP interpretation of the user's prompt, then trying to turn the randomly generated information into a new latent which the VAE will then decode into something a human can see, because the latents the model is dealing with are meaningless numbers to humans.

In other words, there's a lot more randomness to deal with in a diffusion model. You could probably get a specific source image back if you specially crafted a latent and a prompt, which one guy did do by basically running img2img on a specific image that was in the training set and giving it a prompt to spit the same image out again. But that required having the original image in the first place, so it's not really a weakness in the same way this was for GPT.

Really says something that, according to steamcharts numbers, Payday 2 has over 10x the current playercount than Payday 3 right now. Even peak, Payday 3 has 3,475, whereas Payday 2 has 34,680.

And as far as D&D video games go... Baldur's Gate 3 already mastered that niche. I'll keep an eye out if it sounds impressive, but I don't see it living up to the same standard. Even then, going to a game shop and playing with real people around a table can't be beat, either.

I accidentally submitted early, but also, I wrote out the lyrics. It's the most bland version of those breakup-depression kind of songs imaginable. I guess people voted it as "feel-good" out of irony.

Sitting at my favorite cafe

Sipping my tea it's saturday

Thinking about all he's done, to everyone

This town is full of broken dreams

Shattered hopes, and silent screams

Somebody please help me

Betrayed by this town

Let's tear it all down

We're all just destined to fall

I've lost it all

Betrayed by this town

Let's tear it all down

We're all just destined to fall

We've lost it all

Alone in the streets, alone in my thoughts

Thinking of all our favorite spots

I thought someday things might turn around

But I was lost and never found

Betrayed by this town

Let's tear it all down

We're all just destined to fall

I've lost it all

Betrayed by this town

Let's tear it all down

We're all just destined to fall

We've lost it all

Faces painted with smiles

Lies are told

A facade of unity

A vitality sold

So I sit here in silence

Just wondering how

To rewrite the tales

This town won't allow

Betrayed by this town

Let's tear it all down

We're all just destined to fall

I've lost it all

Betrayed by this town

Let's tear it all down

We're all just destined to fall

We've lost it all

I've lost it all

We've lost it all