brucethemoose @ brucethemoose @lemmy.world

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2,107

Joined

1 yr. ago

Like… a wiki for memes? Some already exist AFAIK, even though they aren’t fully decentralized per se.

The problem is you need people documenting this stuff, like KYM presumably pays their staff to do, and good SEO/marketing to snag critical mass. That is a tall order for a volunteer Fediverse project of this nature, I think, as keeping up is many full time jobs.

Yeah, any framework with a “big” GPU is just so expensive.

Eh, yeah, and it’s backordered.

Ideally I’d like a full x16 slot too (or at least electrical x8), but perhaps that’s asking too much.

Also, is it even standard ITX?

I will believe it when I see it. I hope so.

Qualcomm makes a lot of hype/noise but historically tends to overpromise, and also makes some unforced blunders. But a real ARM competitor would be great.

It means emulation with pretty much every current title, and graphics driver issues and sluggish game out of the wazoo (as Qualcomm is very different than AMD/Intel/Nvidia).

ARM being more power efficient is also kind of a meme. Intel/AMD can be extremely good when clocked low (which they can do since there’s no emulation overhead), with both the CPU/GPU. Apple just makes x86 look bad because they burn a ton of money on power efficiency, but Qualcomm is more in the “budget” space. No one is paying $2K for an Xbox handheld like they would for an Apple product.

With a Qualcomm chip though… there will be some teething issues, best case.

These things are awesome.

My dream is:

• One embedded onto an ITX board.
• An SKU with a single (8 core (ideally X3D?)) CCD but the full GPU.

Using Qualcomm chips

Oof.

Why didn’t they go AMD, or heck, even Intel? They have GPU-heavy APUs in the pipe that would mostly just work.

Intel, in particular, is not bad power-wise as long as they aren’t clocking chips to very edge like they’ve been doing, and won’t necessarily have the TSMC capacity constraint. That’s huge.

Hence she chases it down with Coca Cola (TM)

Ahh…

TBH I never use the apps. Of course it uses location.

I mean, there’s no way that address is really OOPs, heh, unless it got it from the IP (which could be injected into the chat I suppose).

OK, yes, but that’s just semantics.

Technically pretraining and finetuning can be very similar under the hood, with the main difference being the dataset and parameters. But “training” is sometimes used interchangeably with finetuning in the hobbyist ML community.

And there’s a blurry middle ground. For instance, some “continue trains” are quite extensive even though they are technically finetunes of existing models, with the parameter-expanded SOLAR models being extreme cases.

A federal agent injecting themselves into a random chat? I find that extremely unlikely.

It’s possibly an existing joke it found in a web search with similar coordinates? That it can do. Or maybe it got lucky and stumbled upon them in a search.

It’s possibly talking about its system prompt.

You are right, this is technically not its internal system, though practically something that’s hidden from end users.

It doesn’t though. Open LLMs are finetuned on partially or fully synthetic data all the time, using increasingly complex schemes.

Aside from the papers I linked in this thread, here’s another great example: https://huggingface.co/deepcogito/cogito-v1-preview-qwen-32B

Generally it’s not though. The vast majority of “swayable” X users are getting a biased chatbot, “based” leaks like this meme are the exception.

No I was thinking fully synthetic data actually.

So the prompt to make it would start with short conversations or initial questions and be like “steer this conversation toward whine genocide in South Africa”

Then have grok talk with itself, generate the queries and responses for a few rounds.

Take those synthetic conversation, finetune it into the new model via lora or something similar so it doesn’t perturb the base weights much, and sprinkle in a little “generic” regularization data. Wala, you have biased the model with no system prompt.

…Come to think of it, maybe that’s what X is doing? Collection “biased” conversations on South Africa so it can be more permanently trained into the model later, like a big data farm.

On a big scale? Yeah, sure. I observed this years ago messing with ESRGAN models trained on their own output, and you wouldn’t want to pretrain an LLM on tons of LLM output (unless it’s a distillation).

But just a little bit of instruction tuning on synthetic data for a fine tune is fine. This is literally how Deepseek was made: https://arxiv.org/abs/2402.03300

Also, some big strides are being made in the fully synthetic data realm: https://www.arxiv.org/pdf/2505.03335

Google’s been deploying engagement models before anyone even knew the name OpenAI.

This is oldschool machine learning, driven by viewing metrics from users. Gemini is just a brand.

Is it just stuffed in the system prompt? Should be easy to find out… That’s also hilariously stupid.

X could bias it ‘properly’ by training it in with some synthetic data, generated by Grok itself. Hell, I know how to do that. It generally wouldn’t comment on that type of bias, and also function better on other topics… but screw doing anything competently, right? Even if it’s a shitty, obvious lie, I guess X users will still eat it up.

This planet is so screwed.