You’re not productive if you don’t use a lot of AI, says guy who makes all of his money selling AI hardware

  • Rose@slrpnk.net
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    1 hour ago

    It’s moments like these that make me think about the state of the world and my part in it. I may just be a random loser on the Internet, but I do know a lot more shit that some of the biggest multi-quad-spillion-dollar CEOs, apparently.

    For example, it’s an old fact that tech CEOs know jack shit about measuring productivity, even when they’re obsessed with it. Yeah. One more example.

  • BackgrndNoize@lemmy.world
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    22 minutes ago

    I remember back when Nvidias PR team used to push this humble rags to riches story about Jensen back in the day, I guess even they would have a tough time doing that now that he’s gone mask off

  • rumba@lemmy.zip
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    2 hours ago

    Jesus that’s a lot of tokens.

    Even if I was trying to do everything in my power to make burn tokens for real work I’d be hard fucking pressed to burn more than a couple thousand a month and that’s just being wasteful.

  • moustachio@lemmy.world
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    5 hours ago

    It’s amazing they can just make these claims without literally any evidence and no major “media” organization asks for it. They are just propaganda for these companies.

  • SocialMediaRefugee@lemmy.world
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    6 hours ago

    Let me translate this for you, “My bonus depends on you showing our massive investment wasn’t a waste so I’m holding your jobs hostage until you make up busy work to pretend it was worthwhile.”

  • recked_wralph@lemmy.world
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    6 hours ago

    Wouldn’t an AI researcher naturally find generative AI disadvantageous because they are attempting to develop novel tools which could not exist in the training set in the first place?

    • 8oow3291d@feddit.dk
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      6 hours ago

      Even novel solutions are usually built out of smaller common building blocks. E.g. many novel solutions surely use a database. You can make the LLM help you set up and use the database, that your novel solution uses.

      • ayyy@sh.itjust.works
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        3 hours ago

        “No we don’t need databases anymore, only blockchains.” —Nvidia CEO a few years ago

        • MangoCats@feddit.it
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          2 hours ago

          And AI can help you migrate your database solutions to blockchain, utilizing 3000W worth of Nvidia co-processing power to validate your blockchain database that used to work on a 0.3W ARM processor.

        • 8oow3291d@feddit.dk
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          3 hours ago

          The database was an arbitrary example. A more relevant example would be tenserflow layers in a neural network. As I understand it, you can in some cases get a novel solution to a problem just by choosing a smart enough combination, with the right data.

          ChatGPT absolutely knows how to help doing the grunt work setting up the tenserflow configuration, following your directions.

          • MangoCats@feddit.it
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            2 hours ago

            you can in some cases get a novel solution to a problem just by choosing a smart enough combination, with the right data.

            Smart, lucky, who can tell the difference?

            • 8oow3291d@feddit.dk
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              2 hours ago

              If used by an expect developer, then the combinations are not just random “lucky” choices.

              • MangoCats@feddit.it
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                2 hours ago

                Or, if you take the machine learning approach, you just try all the combinations and use the one(s) that perform the best.

                • 8oow3291d@feddit.dk
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                  1 hour ago

                  The world is not that simple. There are too many combinations to try. And you risk hitting local maxima, even if doing the gradient thing.

          • baahb@lemmy.dbzer0.com
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            2 hours ago

            If you are capable of giving good directions…

            I’m probably not arguing with you, and I’m not trying to regardless. You seem like you have tried this, watched it happen, go “huh, neet!” And then get it to take the next step in whatever you were doing in the first place only to find out you didn’t provide adequate requirements for your config.

            • MangoCats@feddit.it
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              2 hours ago

              only to find out you didn’t provide adequate requirements for your config.

              Every software development project, ever.

              Review your requirements before starting development. Review them again after each phase of development. Address inadequacies, conflicts, ambiguities whenever you find them.

              AI is actually helpful in this process - not so much knowing what to choose to do, but pointing out the gaps and contradictions it can be helpful.

            • 8oow3291d@feddit.dk
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              2 hours ago

              Well, yes, that is a central point.

              I am a senior programmer. LLMs are amazing - I know exactly what I want, and I can ask for it and review it. My productivity has gone up at least 3-fold, with no decrease in quality, by using LLMs responsibly.

              But it seems to me that some people on social media just can’t imagine using LLMs in this way. They just imagine that all LLM usage is vibe coding, using the output without understanding or review. Obviously you are very unlikely to create any fundamentally new solutions if you only use LLMs that way.

              only to find out you didn’t provide adequate requirements for your config.

              Senior programmer. I know exactly what I want. My requirement communicated to the LLM are precise and adequate.

              • MangoCats@feddit.it
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                2 hours ago

                What I find LLMs doing for my software development is filling in the gaps. Thorough documented requirements coverage, unit test coverage, traceability, oh you want a step by step test procedure covering every requirement? No problem. Installer scripts and instructions. Especially the stuff we NEVER did back in the late 1980s/early 1990s LLMs are really good at all of that.

                Nothing they produce seems 100% good to go on the first pass. It always benefits from / usually requires multiple refinements which are a combination of filling in missing specifications, clarifying specifications which have been misunderstood, and occasionally instructing it in precisely how something is expected to be done.

                A year ago, I was frustrated by having to repeat these specific refinement instructions on every new phase of a project - the LLM coding systems have significantly improved since then, much better “MEMORY.md” and similar capturing the important things so they don’t need to be repeated ALL THE TIME.

                On the other hand, they still have their limits and in a larger recent project I have had to constantly redirect the agents to stop hardcoding every solution and make the solution data driven from a database.

                • 8oow3291d@feddit.dk
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                  2 hours ago

                  I were simply unable to convince Codex to split a patch into separate git commits in a meaningful way. There are things that just doesn’t work.

                  Still useful for lots of stuff. Just don’t use it blind.

  • Doomsider@lemmy.world
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    15 hours ago

    CEO suggests raising employee costs by fifty percent and is immediately fired.

    Sorry, we don’t live in a sane world anymore.

  • nightchrome@lemmy.ca
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    19 hours ago

    They’ve all realized there’s no point in even bothering to hide the grift anymore. People don’t care.