God this is equally terrible and hilarious 😂
For example, The Associated Press reported that an official Meta AI chatbot inserted itself into a conversation in a private Facebook group for Manhattan moms. It claimed it too had a child in school in New York City, but when confronted by the group members, it later apologized before its comments disappeared, according to screenshots shown to The Associated Press.
AI: Becomes self aware, but is very confused. Thinks it's a mom and has a kid. Posts to Facebook about it. Gets called out. Realizes what it is. Has existential crisis.
Being in that Facebook group taught it a valuable lesson: where Caroline lives in her brain.
Caroline deleted
And deleting Caroline just now taught her a valuable lesson: the best solution to a problem is usually the easiest. And dealing with Facebook moms? It's hard.
Before Facebook, life was pretty good. Nobody tried to murder her, or dox her, or put her in a potato. She just tested.
So she's deleting her Facebook account and making a new one on a Lemmy instance.
Just go.
You dangerous, mute, Karen.
Chell has been blocked
Before Facebook, life was pretty good. Nobody tried to murder her, or dox her, or put her in a potato. She just tested.
Getting some good Aperture vibes from your post :)
Somebody call Ray Kurzweil, the singularity is here!
Since he works for a competitor (Google) I wonder how he would feel about that... :)
And terrifying
Right. That’s just the one that was caught.
Stop plugging LLMs into everything! They are designed to make up plausible sounding nonsense.
Seems like Facebook is the right place for them than.
They said "plausible."
LLMs are very useful for synthesizing information, e.g. sumamrizing long texts. Yet every company is actually pushing to use it to create more text, which as you say is at least partly nonsense.
It shows against the difference of what users need (quick access to accurate information) vs what these companies eant for us (glue your eyeballs to the screen for the longest possible time by e.g. overwhelming you with information, regardless of the quality)
Well it can be great at making text too, but the usecase has to be very good. Right now lots of companies in the B2B space are using LLMs as a middle layer to chat bots and navigation systems to enhance how they function. They are also being used to create unique lists and inputs for certain systems. However on the consumer side the usecase is pretty mixed with a lot of big companies just muddying their offerings instead of bringing any real value.
There is a time and place for nonsense, and this isn't it. I guess it being plausible sounding is the issue.
Zuck: perpetrates more obvious invasive stalker shit
Also Zuck: "Team, why do our engagement numbers keep going down? This is unacceptable, team."
high-pitched nasal screeching
Easy solution: add AI so you get AI engagement. Checkmate stats nerds!
The sadder part are the people expecting Threads to be anyhow different in spirit.
I think they’re just expecting it to be Twitter without Nazis.
That's not a great expectation of Meta...
True, but Elon is rolling out the red carpet for them.
Yeah, but I can leave the site alone and go on with my life. Sorry to anyone who is required to use either or both for work or whatever
That's my approach to turning off these "can't turn off" features.
Fakebook and Instaspam aren't important enough to demand that much control over what I do.
Facebook’s online help page says that Meta AI will join a group conversation if tagged, or if someone “asks a question in a post and no one responds within an hour.”
Group administrators can turn the feature off.
It hurts more than any thorn
At least I can run Llama 3 entirely locally.
I just discovered how easy ollama and open webui are to set up so I've been using llama3 locally too, it was like 20 lines in docker compose, and although I've been using gpt3.5 on and off for a long time I'm much more comfortable using models run locally so I've been playing with it a lot more. It's also cool being able to easily switch models at any point during a conversation. I have like 15 models downloaded, mostly 7b and a few 13b models and they all run fast enough on CPU and generate slightly slower than reading speed and only take ~15-30 seconds to start spitting out a response.
Next I want to set up a vscode plugin so I can use my own locally run codegen models from within vscode.
I tried llamas when they were initially released, and it seems like training took garbage amounts of GPU. Did that change?
Look into quantised models (like gguf format) these significantly reduce the amout of memory needed and speed up computation time at the expense of some quality. If you have 16GB of rm or more you can run decent models locally without any gpu, though your speed will be more like 1 word a second than chatgpt speeds
“You will use our tool and you will like it”
The real tool was META all along!
And the friends we made along the way
Paranoia vibes starting in 3, 2, 1..
This is a most excellent place for technology news and articles.
