It guessed my buddy's name, unprompted!
Signed, John Jacob Jingleheimer Schmidt
swlabr
joined 2 years ago
Just remember, it can, and will, always get worse!
Yeah exactly. Loving the dude's mental gymnastics to avoid the simplest answer and instead spin it into moralising about promptfondling more good
OpenAI should be opening Thanatoria any day now, with Sora^TM^ to generate visual^[Soon with audio! ] content to comfort you on your hemlock shuffle off the mortal ~~buffalo~~ coil.
Swatting as a service
Sorry, as mentioned elsewhere in the thread I can’t open links. Looks like froztbyte explained it though, thanks!
Actually I’m finding this quite useful. Do you mind posting more of the article? I can’t open links on my phone for some reason
what is this “alignment” you speak of? I’ve never heard of this before
video events
Ah you see, this is proof that FSD is actually AGI. Elon told the FSD that it needs to maximise tesla profits. The FSD accessed a camera pointing at a tesla earnings report and realised that it could increase the value of tesla’s carbon credit scheming by taking out trees, hence the events of the video
In the current chapter of “I go looking on linkedin for sneer-bait and not jobs, oh hey literally the first thing I see is a pile of shit”
text in image
Can ChatGPT pick every 3rd letter in "umbrella"?
You'd expect "b" and "I". Easy, right?
Nope. It will get it wrong.
Why? Because it doesn't see letters the way we do.
We see:
u-m-b-r-e-l-l-a
ChatGPT sees something like:
"umb" | "rell" | "a"
These are tokens — chunks of text that aren't always full words or letters.
So when you ask for "every 3rd letter," it has to decode the prompt, map it to tokens, simulate how you might count, and then guess what you really meant.
Spoiler: if it's not given a chance to decode tokens in individual letters as a separate step, it will stumble.
Why does this matter?
Because the better we understand how LLMs think, the better results we'll get.
MFs are boiling the oceans to reinvent cold reading
Abstracted abstract:
Frontier models are increasingly trained and deployed as autonomous agents, which significantly increases their potential for risks. One particular safety concern is that AI agents might covertly pursue misaligned goals, hiding their true capabilities and objectives – also known as scheming. We study whether models have the capability to scheme in pursuit of a goal that we provide in-context and instruct the model to strongly follow. We evaluate frontier models on a suite of six agentic evaluations where models are instructed to pursue goals and are placed in environments that incentivize scheming.
I saw this posted here a moment ago and reported it*, and it looks to have been purged. I am reposting it to allow us to sneer at it.
*
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IDK if they were really speedrunning, it took 3 replies for the total mask drop.