lily33

An intelligence service monitors social media. They may as well have said, "The sky is blue."

More interesting is,

Sharing as a force multiplier

-- OpenAI

Do you know of a provider is actually private? The few privacy policies I checked all had something like "We might keep some of your data for some time for anti-abuse or other reasons"...

Too bad that's based on macros. A full preprocessor could require that all keywords and names in each scope form a prefix code, and then allow us to freely concatenate them.

Aren't USAid grants public?

No, that's because social media is mostly used for informal communication, not scientific discourse.

I guarantee you that I would not use lemmy any differently if posts were authenticated with private keys than I do now when posts are authenticated by the user instance. And I'm sure most people are the same.

Edit: Also, people can already authenticate the source, by posting a direct link there. Signing wouldn't really add that much to that.

Sure, but that has little to do with disinformation. Misleading/wrong posts don't usually spoof the origin - they post the wrong information in their own name. They might lie about the origin of their "information", sure - but that's not spoofing.

I don't understand how this will help deep fake and fake news.

Like, if this post was signed, you would know for sure it was indeed posted by @lily33@lemm.ee, and not by a malicious lemm.ee admin or hacker*. But the signature can't really guarantee the truthfulness of the content. I could make a signed post that claiming that the Earth is flat - or a deep fake video of NASA'a administrator admitting so.

Maybe I'm missing your point?

(*) unless the hacker hacked me directly

It works fine for me on Hyprland.

That is why I use just int main(){...} without arguments instead.

https://openrouter.ai/deepseek/deepseek-r1 - offers multiple providers, so at least someone will be up (though note that most are more expensive than Deepseek themselves).

I don't think any kind of "poisoning" actually works. It's well known by now that data quality is more important than data quantity, so nobody just feeds training data in indiscriminately. At best it would hamper some FOSS AI researchers that don't have the resources to curate a dataset.

What makes these consumer-oriented models different is that that rather than being trained on raw data, they are trained on synthetic data from pre-existing models. That’s what the “Qwen” or “Llama” parts mean in the name. The 7B model is trained on synthetic data produced by Qwen, so it is effectively a compressed version of Qen. However, neither Qwen nor Llama can “reason,” they do not have an internal monologue.

You got that backwards. They're other models - qwen or llama - fine-tuned on synthetic data generated by Deepseek-R1. Specifically, reasoning data, so that they can learn some of its reasoning ability.

But the base model - and so the base capability there - is that of the corresponding qwen or llama model. Calling them "Deepseek-R1-something" doesn't change what they fundamentally are, it's just marketing.