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#llama

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Hirad

One of the biggest advantages of Ollama over llama.cpp is its ability to automatically unload models. It removes the model from vram after 5 mins of being idle and that's very useful.

#Ollama#llamacpp#llama
Hirad

I'm considering to test llama.cpp and see if I prefer it over Ollama.
The good thing about Ollama is the ease of use, but it's terrible when it comes to model format. Meanwhile llama.cpp even though more complex, it simply works with gguf files, which makes things much easier.
Also in terms of performance, llama.cpp is supposed to be better than Ollama. But I have to try it to know for sure.

#Ollama#llamacpp#llama
KING CONSULT | Kommunikation

> The #Meta AI app is a #privacy disaster

> Your browser history has been public all along, and you had no idea. That’s basically what it feels like right now on the new stand-alone Meta AI app

#TechCrunch 06/'25: techcrunch.com/2025/06/12/the-

Spiegel 04/'25:
> Die App wird zunächst in den USA eingeführt und später weltweit ausgerollt. Ob und wann die … Features nach Deutschland kommen, ist noch unklar

spiegel.de/netzwelt/apps/meta-

TechCrunch · The Meta AI app is a privacy disaster | TechCrunchMeta does not indicate to users what their privacy settings are as they post, or where they are even posting to. So, if you log into Meta AI with Instagram, and your Instagram account is public, then so too are your searches.
#MetaAiApp#MetaAI#Llama
Strange Quark

According to researchers at University of #Glasgow, #LLMs are not #hallucinating. The technical term is #bullshitting.

"Calling their mistakes ‘hallucinations’ lends itself to the confusion that the machines are in some way misperceiving but are nonetheless trying to convey something that they believe or have perceived. This is the wrong metaphor.... they are not trying to convey information at all. They are bullshitting."

link.springer.com/article/10.1

SpringerLinkChatGPT is bullshit - Ethics and Information TechnologyRecently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
#LLM#ChatGPT#OpenAI
BGDon

Good read: Beware of AI model collapse!

In an AI model collapse, AI systems, which are trained on their own outputs, gradually lose accuracy, diversity, and reliability. This occurs because errors compound across successive model generations, leading to distorted data distributions and "irreversible defects" in performance. The final result? A Nature 2024 paper stated, "The model becomes poisoned with its own projection of reality." nature.com/articles/s41586-024

"In simpler terms, when AI is trained on its own outputs, the results can drift further away from reality." as stated by Aquant.

Full article here: theregister.com/2025/05/27/opi #AI #AIErrors #AI_Model_Collapse #LLMs #ChatGPT #Llama #Claude #TheRegister

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