I think that "exactly like" it's absurd. Bubbles are never "exactly" like the previous ones.
I think in this case there is a clear economical value in what they produce (from the POV of capitalism, not humanity's best interests), but the cost is absurdly huge to be economically viable, hence, it is a bubble. But in the dot com bubble, many companies had a very dubious value in the first place.
Yeah, you are not gonna be able to do that with an LLM. They will be able to quote only some passages, and only of popular books that have been quoted often enough.
You entirely ignored this part.
You basically proved my point in doing so, BTW. You cannot do what you claimed with an LLM. And I'm not saying, and I never said before "ChatGPT" or "OpenAI". I don't understand why you think that I might be "defending these hypocritical companies", when I literally said the opposite at the end.
You are entirely fooled by the output of ChatGPT and you are not arguing in good faith (or you are entirely unable to understand what I said).
Edit/addendum: And to stress out my point, given that the person to whom I've replied to showed the output of ChatGPT as if it were any kind of proof, this is what other LLMs say. This is 4o mini:
Large Language Models (LLMs) like me do not have the ability to quote whole sections of copyrighted texts verbatim. While I can generate text based on patterns and information learned during training, I do not store or recall specific texts or books. Instead, I can provide summaries, analyses, or discuss themes and concepts related to a book without directly quoting it. If you have a specific topic or question in mind, feel free to ask!
And this is Llama 3.1 70B:
Large Language Models (LLMs) can generate text based on the patterns and structures they've learned from their training data, which may include books. However, whether they can quote whole sections of a book depends on several factors.
LLMs are typically trained on vast amounts of text data, including books, articles, and other sources. During training, they learn to recognize patterns, relationships, and context within the text. This allows them to generate text that is similar in style and structure to the training data.
However, LLMs do not have the ability to memorize or store entire books or sections of text. Instead, they use the patterns and relationships they've learned to generate text on the fly.
That being said, it's possible for an LLM to generate text that is very similar to a section of a book, especially if the book is well-known or widely available. This can happen in a few ways:
- Overlapping patterns: If the book's writing style, structure, or content is similar to other texts in the training data, the LLM may be able to generate text that resembles a section of the book.
- Memorization of key phrases: LLMs may memorize key phrases, quotes, or passages from the training data, which can be recalled and used in generated text.
- Contextual generation: If the LLM is given a prompt or context that is similar to a section of the book, it may be able to generate text that is similar in content and style.
However, it's unlikely that an LLM can quote a whole section of a book verbatim, especially if the section is long or contains complex or unique content. The generated text may be similar, but it will likely contain errors, omissions, or variations that distinguish it from the original text.
Feel free to give them a shot in: https://duck.ai
Wow, thanks, I have not seen this comment, yet I hinted about this in some of my other replies that I've done before.
Yes, I think ML is fair use, but there it would also be fair to force something into the public domain/open source if, in order to be accrued, it has to make use of fair use at unseen amounts of scale.
This would be a difficult to make law, though. Current ML is very inefficient in the amount of data it requires, but it could (and should) be made better.
Now I sail the high seas myself, but I don’t think Paramount Studios would buy anyone’s defence they were only pirating their movies so they can learn the general content so they can produce their own knockoff.
We don't know exactly how they source their data (and that is definitely shady), but if I can gain access to a movie in a legal way, I don't see why I would not be able to gather statistics from said movie, including running a speech to text model to caption it, then make statistics of how many times a few words were used, and followed by which ones. This is an oversimplified explanation of what a LLM does, but it's the fairest I can come up, and it would be legal to do so. The models are always orders of magnitude smaller than the data they are trained on.
That said, I don't imply that I'm happy with the state of high tech companies, the AI hype, the energy consumption, or the impact on the humble people. But I've put a lot of thought into this (and learning about machine learning for real), and I think this is not a ML problem, but a problem in the economic, legal and political system. AI hype is just a symptom.
It’s not AI
It's not AGI, it's not general intelligence, and it's not comparable to a human (well, you can compare anything, but human and ML are just very different things in tons of ways).
But it is AI. The ghosts that chase Pacman are AI. A search algorithm is also AI, dammit. Of course an LLM is AI. Any agent that maximizes a function is AI. You are just embarrassing yourself.
FWIW, cppfront would be the same, IMHO. It allows C++ syntax, and it just passes it through verbatim. Only transforms "syntax 2" into today's C++. And Herb Sutter very much says that what it does is based on the papers that he's presented for standardization, and that he'd like this approach (new syntax) land into today's C++ compilers and the standard.
cppfront is the only one that I thought had a chance till recently. The presentations from Sean Baxter seem to finally make the community see it on a positive light (I've seen posts on Reddit being removed on the premise of not being C++, which I think it's a bit unfair), so that's good.
Also preemptively deciding that me disagreeing with you automatically makes you right because you predicted your explanation wouldn’t satisfy me is just A-tier bullshit.
I predicted that I would waste my time by replying to you, and I predicted right.
I wanted to give it a chance, though, because Lemmy is a place that is friendly enough and that I want to thrive, despite how little I contribute. I tried to be constructive and explain things the best I could, and assume the best possible faith, etc. When you just say that I sound like an asshole, and completely act in bad faith in how russian roulette is supposed to be in the context of someone who says "you can beat me at any game", now I feel the urge to try the block feature in Lemmy, sorry.
I'd have to dig it, but I think it said that it added the PID and the uninitialized memory to add a bit more data to the entropy pool in a cheap way. I honestly don't get how that additional data can be helpful. To me it's the very opposite. The PID and the undefined memory are not as good quality as good randomness. So, even without Debian's intervention, it was a bad idea. The undefined memory triggered valgrind, and after Debian's patch, if it weren't because of the PID, all keys would have been reduced to 0 randomness, which would have probably raised the alarm much sooner.
Thanks!
Definitely worth it. Kudos for the tool and all your plugins.
My father in law has worked in construction all his life, and had a small company with his brothers. They had vans and light trucks. It is kinda common for other people to just rent it in some cases. And normally furniture, moving, appliances, etc, it is delivered to you by professionals, unless you want to save some money. At IKEA's door often there are people with vans offering to you to carry the goods, and sometimes even assemble it (at a cost, I mean).
OpenAI doesn't produce LLMs only. People are gonna be paying for stuff like Sora or DallE. And people are also paying for LLMs (e.g. Copilot, or whatever advanced stuff OpenAI offers in their paid plan).
How many, and how much? I don't know, and I am not sure it can ever be profitable, but just reducing it to "chains of bullshit" to justify that it has no value to the masses seems insincere to me. ChatGPT gained a lot of users in record time, and we know is used a lot (often more than it should, of course). Someone is clearly seeing value in it, and it doesn't matter if you and I disagree with them on that value.
I still facepalm when I see so many people paying for fucking Twitter blue, but the fact is that they are paying.