Submitted by BronzeArcher t3_1150kh0 in MachineLearning
prehensile_dick t1_j8z0dgl wrote
Corporations scraping all kinds of copyrighted materials and then profiting off the models while the people doing all the labor are getting either nothing (for content generation) or poverty wages (for content labellers).
Their current push to promote LLMs as some sort of pinnacle of technology, when they barely have any legitimate use-cases and struggle with the most basic of logic, will probably lead to a recession in the tech industry.
BronzeArcher OP t1_j8z83z8 wrote
These are what I feel like are the most standard topics. Valuable, nonetheless.
prehensile_dick t1_j8zan8s wrote
I feel like the ethical issues pertaining to bias and toxic content can be (and are being) worked on. The collection of the training data and attribution problem seem more intractable and companies are already being sued for that.
Diligent_Ad_9060 t1_j8zc02u wrote
I'd be very interested in hearing someone having more insight into Free Software Foundation and their process against copilot
prehensile_dick t1_j8zdhy9 wrote
Not specifically about that suit, but the Legal Eagle episode about copyright and AI was really interesting. The relevant part starts at 5:03
Diligent_Ad_9060 t1_j8zdoh6 wrote
Thank you for sharing. I'll have a look
currentscurrents t1_j8zh4aa wrote
>scraping all kinds of copyrighted materials and then profiting off the models while the people doing all the labor are getting either nothing (for content generation)
Yeah, but these people won't be doing that labor anymore. Now that text-to-image models have learned how to draw, they don't need a constant stream of artists feeding them new art.
Now artists can now work at a higher level, creating ideas that they can render into images using the AI as a tool. They'll be able to create much larger and more complex projects, like a solo indie artist creating an entire anime.
>LLMs... barely have any legitimate use-cases
Well, one big use case: they make image generators possible. Those rely on embeddings from language models, which are a sort of neural representation of the ideas behind the text. It grants the other network the ability to work with plain english.
Right now embeddings are mostly used to guide generation (across many fields, not just images) and semantic search. But they are useful for communicating with a neural network performing any task, and my guess is that the long-term impact of LLMs will be that computers will understand plain english now.
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