Beautiful! I'll definitely give this a go
minoscopede
joined 11 months ago
python -m http.server is still my media server of choice. It's never let me down.
On any site with unverified signups (all of them) you can't.
If you want to talk to real people, you'd have to use a platform that has in-person ID verification. Like a pub, or a park.
Good luck finding a bot free place on your phone. It'd have to involve zero-sum proofs and biometrics. And even then you can't really be sure that person isn't using a bot to write without full root access to their system and a live webcam feed.
I want clear evidence that the LLM will tell me if it doesnβt know something, and will never hallucinate or make something up.
Every step of any deductive process needs to be citable and traceable.
I mostly agree, but "never" is too high a bar IMO. It's way, way higher than the bar even for humans. Maybe like 0.1% or something would be reasonable?
Even Einstein misremembered things sometimes.
Eh, certain parts of LA are safe. But LA is actually pretty conservative in other areas, due to a large religious population, and a lot of first-gen immigrants.
I have to ask: would this story be so popular if they didn't mention that the four people that did this were Chinese?
Racism doesn't disappear just because the article doesn't say the quiet part out loud. We all know the thought process that led to this article's virality.
Let's do better, Lemmy. We all have an opportunity to make the world a more tolerant and empathetic place through what we post and upvote.
It only seems to make a difference when the rich ones complain.
"despite what you may have heard, pusillanimous does not serve as the basis for pussyfoot, pussycat, or a certain related vulgarism." - Merriam-Webster Dictionary
Social media is a misinformation engine
Obvious ragebait article
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I see a lot of misunderstandings in the comments π«€
This is a pretty important finding for researchers, and it's not obvious by any means. This finding is not showing a problem with LLMs' abilities in general. The issue they discovered is specifically for so-called "reasoning models" that iterate on their answer before replying. It might indicate that the training process is not sufficient for true reasoning.
Most reasoning models are not incentivized to think correctly, and are only rewarded based on their final answer. This research might indicate that's a flaw that needs to be corrected before models can actually reason.