we appear to be the first to write up the outrage coherently too. much thanks to the illustrious @self

      • Lumisal@lemmy.world
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        2 months ago

        I did read the thing, then provided an article explaining why detecting copyrighted material / determining if something is written by AI is very inaccurate.

        Perhaps take your own advice to “read the fucken thing” next time instead of making yourself look like an idiot. Though I doubt you’ve ever heard of “better to stay silent and let them think you the fool than to speak and remove all doubt”.

        Btw, I even recall that Ars specifically covered the company you linked to in a separate article as well. I’d be glad to provide it once you’ve come to your senses and want to discuss things like an adult.

        • froztbyte@awful.systems
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          2 months ago

          Mistral’s Mixtral-8x7B-Instruct-v0.1 produced copyrighted content on 22% of the prompts.

          did you know that a lesser-known side effect of the infinite monkeys approach is that they will produce whole sections of copyright content abso-dupo-lutely by accident? wild, I know! totes coinkeedink!

          I’d be glad to provide it once you’ve come to your senses and want to discuss things like an adult

          jesus fucking christ you must be a fucking terrible person to work with

          I’ve seen toddlers throw more mature tantrums

          • Lumisal@lemmy.world
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            2 months ago

            I’m too old to discuss against bad faith arguments.

            Especially with people who won’t read the information I provide them showing their initial information was wrong.

            One is a company that has something to sell, the other an article with citations showing why it’s not easy to determine what percentage of a data set is infringing on copyright, or whether exact reproduction via “fishing expedition” prompting is a useful metric to determine if unauthorized copyright was used in training.

            The dumbest take though is attacking Mistral of all LLMs, even though it’s on an Apache 2.0 license.

            • froztbyte@awful.systems
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              2 months ago

              I’ve read the article you’ve posted:. it does not refute the fucking datapoint provided, it literally DOES NOT EVEN MENTION MISTRAL AT ALL.

              so all I can tell you is to take your pearlclutching tantrum bullshit and please fuck off already

              • Lumisal@lemmy.world
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                2 months ago

                Yes, clearly I’m the one throwing a tantrum 🙄

                Btw, you can just fact check my claim about what Mistral is licenced under. The article talks about copyright and AI detection in general, which to anyone with basic critical thinking skills could then understand would apply to other LLMs like Mistral.

                You might want to look up what pearl clutching means as well. You’re using it wrong:

                https://dictionary.cambridge.org/us/dictionary/english/pearl-clutching

                Considering I’ve done the opposite of a shocked reaction. While at it, maybe also look up “projection”

                https://www.psychologytoday.com/us/basics/projection

                Anyhow, have a good day.

              • self@awful.systems
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                2 months ago

                god these weird little fuckers’ ability to fill a thread with garbage is fucking notable isn’t it? something about loving LLMs makes you act like an LLM. how depressing for them.

              • Lumisal@lemmy.world
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                2 months ago

                Well since you want to use computers to continue the discussion, here’s also ChatGPT:

                Determining the exact percentage of copyrighted data used to train a large language model (LLM) is challenging for several reasons:

                1. Scale and Variety of Data Sources: LLMs are typically trained on vast and diverse datasets collected from the internet, including books, articles, websites, and social media. This data encompasses both copyrighted and non-copyrighted content. The datasets are often so large and varied that it is difficult to precisely categorize each piece of data.

                2. Data Collection and Processing: During the data collection process, the primary focus is on acquiring large volumes of text rather than cataloging the copyright status of each individual piece. While some datasets, like Common Crawl, include metadata about the sources, they do not typically include detailed copyright status information.

                3. Transformation and Use: The data used for training is transformed into numerical representations and used to learn patterns, making it even harder to trace back and identify the copyright status of specific training examples.

                4. Legal and Ethical Considerations: The legal landscape regarding the use of copyrighted materials for AI training is still evolving. Many AI developers rely on fair use arguments, which complicates the assessment of what constitutes a copyright violation.

                Efforts are being made within the industry to better understand and address these issues. For example, some organizations are working on creating more transparent and ethically sourced datasets. Projects like RedPajama aim to provide open datasets that include details about data sources, helping to identify and manage the use of copyrighted content more effectively【6†source】.

                Overall, while it is theoretically possible to estimate the proportion of copyrighted content in a training dataset, in practice, it is a complex and resource-intensive task that is rarely undertaken with precision.

                • froztbyte@awful.systems
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                  2 months ago

                  you should speak to a physicist, they might be able to find a way your density can contribute to science

        • Steve@awful.systems
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          2 months ago

          you’re conflating “detecting ai text” with “detecting an ai trained on copyrighted material”

          send the relevant article or shut up

          • Lumisal@lemmy.world
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            2 months ago

            Ignoring the logical inconsistency you just spouted for a moment (can’t tell if it’s written by AI but knows it used copyrighted material? Do you not hear yourself?), you do realize Mistral is released under the Apache 2.0 license, a highly permissive scheme that has no restrictions on use or reproduction beyond attribution, right?

            I think it’s clear you’re arguing in bad faith however with no intention of changing your misinformed opinion at this point. Perhaps you’d enjoy an echo chamber like the “fuckai” Lemmy instance.

            • self@awful.systems
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              2 months ago

              holy shit you really are quite dumb. the fuck is wrong with you?

              actually don’t answer that

            • self@awful.systems
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              2 months ago

              wait a minute… there’s another “fuck ai” instance and they’ve already told you to go fuck yourself?

              I wonder if they want to be friends

              • froztbyte@awful.systems
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                2 months ago

                have seen one on lemmy.world. it’s kinda the dancing baby version of the stubsack and techtakes tho from what I can tell