• brucethemoose@lemmy.world
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    2 months ago

    As a fervent AI enthusiast, I disagree.

    …I’d say it’s 97% hype and marketing.

    It’s crazy how much fud is flying around, and legitimately buries good open research. It’s also crazy what these giant corporations are explicitly saying what they’re going to do, and that anyone buys it. TSMC’s allegedly calling Sam Altman a ‘podcast bro’ is spot on, and I’d add “manipulative vampire” to that.

    Talk to any long-time resident of localllama and similar “local” AI communities who actually dig into this stuff, and you’ll find immense skepticism, not the crypto-like AI bros like you find on linkedin, twitter and such and blot everything out.

    • falkerie71@sh.itjust.works
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      2 months ago

      For real. Being a software engineer with basic knowledge in ML, I’m just sick of companies from every industry being so desperate to cling onto the hype train they’re willing to label anything with AI, even if it has little or nothing to do with it, just to boost their stock value. I would be so uncomfortable being an employee having to do this.

      • Mikelius@lemmy.world
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        2 months ago

        For sure, it seems like 90% of ai startups are nothing more than front end wrappers for a gpt instance.

        • dan@upvote.au
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          2 months ago

          They’re all built on top of OpenAI which is very unprofitable at the moment. Feels like the whole industry is built on a shaky foundation.

          Putting the entire fate of your company in a different company (OpenAI) is not a great business move. I guess the successful AI startups will eventually transition to self-hosted models like Llama, if they survive that long.

          • Zos_Kia@lemmynsfw.com
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            2 months ago

            Most projects I’ve been in contact with are very aware of that fact. That’s why telemetry is so big right now. Everybody is building datasets in the hopes of fine tuning smaller, cheaper models once they have enough good quality data.

            • xavier666@lemm.ee
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              2 months ago

              My company is realizing that hosting a model which will be private, cost-effective, and performing better than traditional algorithms is like finding a unicorn. Few months back, the top execs were jumping around GenAI like a bunch of kids. Fortunately, the Sr. research head beat some sense into them.

              • falkerie71@sh.itjust.works
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                2 months ago

                You’re lucky there’s a higher up that could talk down the even higher ups. Though, sometimes it’s not even about the r&d teams.

                I saw company wide HR educational emails or courses telling you how to improve you work quality/efficiency, and one of them tells us to “research AI” and learn how to utilize it, talking about how great it is and improved the work efficiency by 30%. Sure, it has its uses, but I won’t go touting how great it is. And with how ChatGPT works, you have to be the biggest idiot in the world to upload all your sensitive stuff to ChatGPT just for it to make a spreadsheet faster. But without these disclaimers in the email, I doubt regular clerical staff knows about this, and it’s extremely dangerous.

              • Zos_Kia@lemmynsfw.com
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                2 months ago

                What kind of use-cases was it, where you didn’t find suitable local models to work with ? I’ve found that general “chatbot” things are hit and miss but more domain-constrained tasks (such as extracting structured entities from unstructured text) are pretty reliable even on smaller models. I’m not counting my chickens yet as my dataset is still somewhat small but preliminary testing has been very promising in that regard.