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Cake day: June 21st, 2023

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  • If something is possible, and this simply indeed is, someone is going to develop it regardless of how we feel about it, so it’s important for non-malicious actors to make people aware of the potential negative impacts so we can start to develop ways to handle them before actively malicious actors start deploying it.

    Critical businesses and governments need to know that identity verification via video and voice is much less trustworthy than it used to be, and so if you’re currently doing that, you need to mitigate these risks. There are tools, namely public-private key cryptography, that can be used to verify identity in a much tighter way, and we’re probably going to need to start implementing them in more places.









  • It’s not that genuine passion and altruism isn’t acknowledged; the entire open source software world is a testament to that.

    You asked for an explanation as to why Free modern hardware hasn’t been developed yet. The simple answer is that passion and altruism has not yet been a strong enough incentive to motivate anyone to do it. He’s not accusing you of being lazy or hypocritical. The reason why you haven’t done it yet is the exact same reason why anyone else who could do it also hasn’t done it yet. It’s very very hard, and passion doesn’t pay the bills or feed you. Limited to a hobby, it’s simply more work than most people could ever hope to achieve in their spare time.


  • It’s more complicated than sheer greed.

    The fact of the matter is that actually producing any modern technology takes a massive amount of work, and up til this point, no one has gathered enough motivation and free time to do it all for any modern hardware just out of pure altruism. There’s a reason why companies have to pay hundreds of engineers a huge amount of money to get anything developed; those people are not going to do this incredibly difficult work just for fun and moral satisfaction. It’s easy to point the finger at corporate greed for some things being locked down, and to be clear, there’s plenty of valid criticism to go around, but it has to be at least considered that most of this stuff would never have been developed in the first place if it wasn’t for those same companies. Your average person is not going to assemble a motherboard from parts and schematics.

    Wouldn’t anyone just be curious to figure out how stuff works?

    To this point, quite frankly, no. Average people simply do not care about this very much. They want to just turn on their magic internet box, get their work done, play their games, consume their media, and move on without any further fuss. The fact of the matter is that most people have no clue what a BIOS is, could not care less if it was proprietary or not, and have zero interest in learning about flashing them or why they would ever want to do that.


  • The key element here is that an LLM does not actually have access to its training data, and at least as of now, I’m skeptical that it’s technologically feasible to search through the entire training corpus, which is an absolutely enormous amount of data, for every query, in order to determine potential copyright violations, especially when you don’t know exactly which portions of the response you need to use in your search. Even then, that only catches verbatim (or near verbatim) violations, and plenty of copyright questions are a lot fuzzier.

    For instance, say you tell GPT to generate a fan fiction story involving a romance between Draco Malfoy and Harry Potter. This would unquestionably violate JK Rowling’s copyright on the characters if you published the output for commercial gain, but you might be okay if you just plop it on a fan fic site for free. You’re unquestionably okay if you never publish it at all and just keep it to yourself (well, a lawyer might still argue that this harms JK Rowling by damaging her profit if she were to publish a Malfoy-Harry romance, since people can just generate their own instead of buying hers, but that’s a messier question). But, it’s also possible that, in the process of generating this story, GPT might unwittingly directly copy chunks of renowned fan fiction masterpiece My Immortal. Should GPT allow this, or would the copyright-management AI strike it? Legally, it’s something of a murky question.

    For yet another angle, there is of course a whole host of public domain text out there. GPT probably knows the text of the Lord’s Prayer, for instance, and so even though that output would perfectly match some training material, it’s legally perfectly okay. So, a copyright police AI would need to know the copyright status of all its training material, which is not something you can super easily determine by just ingesting the broad internet.


  • AI haters are not applying the same standards to humans that they do to generative AI

    I don’t think it should go unquestioned that the same standards should apply. No human is able to look at billions of creative works and then create a million new works in an hour. There’s a meaningfully different level of scale here, and so it’s not necessarily obvious that the same standards should apply.

    If it’s spitting out sentences that are direct quotes from an article someone wrote before and doesn’t disclose the source then yeah that is an issue.

    A fundamental issue is that LLMs simply cannot do this. They can query a webpage, find a relevant chunk, and spit that back at you with a citation, but it is simply impossible for them to actually generate a response to a query, realize that they’ve generated a meaningful amount of copyrighted material, and disclose its source, because it literally does not know its source. This is not a fixable issue unless the fundamental approach to these models changes.


  • There is literally no resemblance between the training works and the model.

    This is way too strong a statement when some LLMs can spit out copyrighted works verbatim.

    https://www.404media.co/google-researchers-attack-convinces-chatgpt-to-reveal-its-training-data/

    A team of researchers primarily from Google’s DeepMind systematically convinced ChatGPT to reveal snippets of the data it was trained on using a new type of attack prompt which asked a production model of the chatbot to repeat specific words forever.

    Often, that “random content” is long passages of text scraped directly from the internet. I was able to find verbatim passages the researchers published from ChatGPT on the open internet: Notably, even the number of times it repeats the word “book” shows up in a Google Books search for a children’s book of math problems. Some of the specific content published by these researchers is scraped directly from CNN, Goodreads, WordPress blogs, on fandom wikis, and which contain verbatim passages from Terms of Service agreements, Stack Overflow source code, copyrighted legal disclaimers, Wikipedia pages, a casino wholesaling website, news blogs, and random internet comments.

    Beyond that, copyright law was designed under the circumstances where creative works are only ever produced by humans, with all the inherent limitations of time, scale, and ability that come with that. Those circumstances have now fundamentally changed, and while I won’t be so bold as to pretend to know what the ideal legal framework is going forward, I think it’s also a much bolder statement than people think to say that fair use as currently applied to humans should apply equally to AI and that this should be accepted without question.