No one at the bouldering gym? What country/state do you live in? I’ve been to two different bouldering gyms and got the impression that it’s one place where people happily help each other or discuss techniques or challenge each other to go up walls. This, however, is my experience in northern Europe in a city where this is a somewhat common sport to play.
I posted it to promote one thing and one thing only: giggles from the shitposting meme community.
I’m F30 (if that matters at all), I have a boyfriend, we live together in a stable and happy relationship, we’re both social, have lots of friends and boardgames and beer, and occasionally take each other out on dates at nice restaurants. Neither of us is “unattractive” (whatever that means in this context, quite subjective I’d say), and we both laughed our ass off at this meme, it was funny, and gave my brain the giggles. Not everything like this is pushing incel ideology, and neither does anything else on my profile (feel free to check, I guess?).
PS: It’s nice to see people giving each other advice for dating here… One funny thing about the meme is that that person in the bottom row might simply “view” themselves that way, or exaggerate the contrast between him and the guy in the upper row. All in all, some people got the laughs, others got nice advice, there was no intention to promote any kind of ideology, so I’d say it’s been a good post.
The word embeddings and embedding layers are there to represent data in ways that allow the model to make use of them to generate text. It’s not the same as the model acting as a human. It may sound like a human in text or even speech, but its reasoning skills are questionable at best. You can try to make it stick to your company policy but it will never (at this level) be able to operate under logic unless you hardcode that logic into it. This is not really possible with these models in that sense of the word, after all they just predict the best next word to say. You’d have to wrap them around with a shit ton of code and safety nets.
GPT models require massive amounts of data, so they were only that good at languages for which we have massive texts or Wikipedias. If your language doesn’t have good content on the internet or freely available digitalized content on which to train, a machine can still not replace translators (yet, no idea how long this will take until transfer learning is so good we can use it to translate low-resource languages to match the quality of English - French, for example).
You still need your chatbot to stick to business rules and act like a real customer service rep, and that’s incredibly hard to accomplish with generative models where you cannot be there to evaluate the generated answers and where the chatbot can go on a tangent and suddenly start to give you free therapy when you originally went in to order pizza.
Don’t get me wrong, they’re great for many applications within the manual loop. They can help customer service reps (as one example) function better, provide more help to users, and dedicate more time to those who still need a human to solve their issues.
Companies are already replacing some workforce with LLMs.
My opinion right now is that companies want you to believe they are 100% capable of replacing humans, but that’s because people in upper management never listen to the damn developers down in the basement (aka me), so they have an unrealistic expectation of AI coupled with an unending desire for money and success.
They are replacing them because they are greedy cunts, not because they are replaceable.
man ls which would fetch you the manual for ls, which lists files and dirs for you. However, I think it’s more common for users to use ls --help instead, which would show the same manual information.
(sorry if you already knew this, but it looked almost like you were asking what this means and then a bunch of linux users just joked around without explaining anything XD)