Here comes the push.

  • Cyborganism@lemmy.ca
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    1 year ago

    LOL! To “make it safer”.

    No.

    It’s to increase share value by creating a rush to buy their graphics cards.

  • devbo@lemmy.world
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    1 year ago

    why do CEOs never say “lets take our time to avoid making mistakes and insure quality”?

    • nicetriangle@kbin.social
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      1 year ago

      Capitalism big number must go up every quarter bullshit. Forces myopic short term decision making and will probably be the death of civilization.

    • magnetosphere@kbin.social
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      1 year ago

      Because that’s boring and doesn’t make good headlines. Not making exciting headlines means share prices stagnate. Taking your time also means that someone else might beat you to the punch. Neither of those things are good for the company’s bottom line or the CEOs business reputation.

    • Centillionaire@kbin.social
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      1 year ago

      Because they are not Miyamoto, helping churn out Zelda and Mario games that feel familiar, yet innovative. 🤌🏻

  • aelwero@lemmy.world
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    1 year ago

    That’s like saying we should all drive faster to help identify shortcomings in traffic signals or vehicle safety features…

    Sounds like a flimsy ass false pretense to chase profits. Just my opinion, mind, but that doesn’t sound like something someone would posit at face value.

    • Katlah@lemmy.dbzer0.com
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      1 year ago

      we should all drive faster to help identify shortcomings in traffic signals or vehicle safety features

      american traffic engineers in question

  • the_q@lemmy.world
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    1 year ago

    Oh is that why? It’s not because Nvidia is making bank in the AI sector and he’s just another greedy CEO?

  • Dr. Dabbles@lemmy.world
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    1 year ago

    “Please buy more of my hardware so nobody finds out how deep in trouble my company is. PLEASE.”

      • Dr. Dabbles@lemmy.world
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        1 year ago

        Their “investments” in their largest customers are showing up as sales volume when they’re essentially giving products away. This coming year has four major companies coming to market with deadly serious competition, and the magic money investment in AI scams is drying up very quickly. So, if I was nvidia, doing what Jensen has been up to with the CEO-to-CEO customer meetings to arrange delivery timelines, and royally screwing over his most reliable channel partners, I’d hope with everything I have that the customers I have keep buying needlessly so the bubble never bursts.

    • Dr. Dabbles@lemmy.world
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      1 year ago

      Dedicated ASIC is where all the hotness lies. Flexibility of FPGA doesn’t seem to overcome its overhead for most users. Not sure if it will change when custom ASIC becomes too expensive again, and all the magic money furnaces run out of bills to burn.

      • just_another_person@lemmy.world
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        1 year ago

        ASIC are single purpose at the benefit of potential power efficiency improvements. Not at all useful something like running neutral networks, especially not when they are being retrained and updated.

        FPGAs are fully (re)programmable. There’s a reason why datacenters don’t lease ASIC instances.

        • Dr. Dabbles@lemmy.world
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          1 year ago

          Not at all useful something like running neutral networks

          Um. lol What? You may want to do your research here, because you’re so far off base I don’t think you’re even playing the right game.

          There’s a reason why datacenters don’t lease ASIC instances.

          Ok, so you should just go ahead and tell all the ASIC companies then.

          https://www.allaboutcircuits.com/news/intel-and-google-collaborate-on-computing-asic-data-centers/

          https://www.datacenterfrontier.com/servers/article/33005340/closer-look-metas-custom-asic-for-ai-computing

          https://ieeexplore.ieee.org/document/7551392

          Seriously. You realize that the most successful TPUs in the industry are ASICs, right? And that all the “AI” components in your phone are too? What are you even talking about here?

          • just_another_person@lemmy.world
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            1 year ago

            TPU units are specific to individual model frameworks, and engineers avoid using them for that reason. The most successful adoptions for them so far are vendor locked-in NN Models a la Amazon (Trainium), and Google (Coral), and neither of them has wide adoption since they have limited scopes. The GPU game being flexible in this arena is exactly why companies like OpenAI are struggling to justify the costs in using them over TPUs: it’s easy to run up front, but the cost is insane, and TPU is even more expensive in most cases. It’s also inflexible should you need to do something like multi-model inference (detection+evaluation+result…etc).

            As I said, ASICs are single purpose, so you’re stuck running a limited model engine (Tensorflow) and instruction set. They also take a lot of engineering effort to design, so unless you’re going all-in on a specific engine and thinking you’re going to be good for years, it’s short sighted to do so. If you read up, you’ll see the most commonly deployed edge boards in the world are…Jetsons.

            Enter FPGAs.

            FPGAs have speedup improvements for certain things like transcoding and inference in the 2x-5x range for specific workloads, and much higher for ML purposes and in-memory datasets (think Apache Ignite+Arrow workloads), and at a massive reduction in power and cooling, so obviously very attractive for datacenters to put into production. The newer slew of chips out are even reprogrammable “on the fly”, meaning a simple context switch and flash can take milliseconds, and multi-purpose workloads can exist in a single application, where this was problematic before.

            So unless you’ve got some articles about the most prescient AI companies currently using GPUs and moving to ASIC, the field is wide open for FPGA, and the datacenter adoption of such says it’s the path forward unless Nvidia starts kicking out more efficient devices.

            • Dr. Dabbles@lemmy.world
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              1 year ago

              Now ask open AI to type for you what the draw backs of FPGA is. Also the newest slew of chips is using partially charged NAND gates instead of FPGA.

              Almost all ASIC being used right now is implementing the basic math functions, activations, etc. and the higher level work is happening in more generalized silicon. You can not get the transistor densities necessary for modern accelerator work in FPGA.

  • li10@feddit.uk
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    1 year ago

    I guess we’re just waiting until something awful happens before it’s properly regulated.

    Not surprising.

  • spudwart@spudwart.com
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    1 year ago

    Nvidia has pissed off the pc gaming industry, which is why their focus has shifted to the server markets.

    Now in the server markets they’re not top dog, so they want to straddle the fence.

    This divided focus will be their undoing.

    • miskOP
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      1 year ago

      Nvidia is top dog in machine learning accelerator / server market which is why they have neglected GPU market. They just want more.

      • spudwart@spudwart.com
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        1 year ago

        If their winning position was truly “top dog” they wouldn’t be shivering, shaking and pissing themselves begging for people to purchase their crap using insane lines like “The more you buy the more you save.”

        This is total and complete panic.

        • miskOP
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          1 year ago

          They do not appear to be in any trouble:

          • spudwart@spudwart.com
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            1 year ago

            This is precisely why they’re panicked. They’ve just had record stock numbers, record income, record everything. This system depends on constant growth. They need to keep that growth going or the shareholders will pull out, and it will cause their stock to crash.

            This all built up just like the Crypto-Rush of 2020-2021. Which you can see in the chart. It went up, peaked, and then dropped when crypto crashed. They’re betting big on AI, when it turns out AI isn’t as profitable as they thought it would be, it will crash also.

            • miskOP
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              1 year ago

              You seem to change narrative / move goalposts with every response.

              Nvidia is okay, nobody expects another 1000% stock price increase. Crypto mania is a faint memory when looking at the profits from ML. They can’t keep up with demand to the point of partially dropping some market segments. Their customers will keep gobbling up hardware for foreseeable future because there are legitimate uses for it and data scientists / engineers will keep processing larger and larger datasets.

              If anything, they’re likely scared of competition from big tech players doing custom chips. Amazon, Google, Microsoft all sell cloud computing resources and already do own sillicon design. They’re definitely looking to have piece of that “AI” pie too.

              Nvidia puts out sleazy statements like the one I’ve linked to nudge regulators to make that pie even bigger.

              • spudwart@spudwart.com
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                1 year ago

                A top dog position is a slow & steady growth or consistent government backing. Sharp growths like they have been having consistently lead to crashes. They don’t need to even have a loss, they just need to under-perform for their next quarterly projections.

                My pointing out cryptomania was not for the fact that Crypto is why they failed. It’s that Crypto gave them market boost, followed by a crash when crypto began to crash. This crash wasn’t explicitly because crypto crashed, it was because their projects weren’t met as a result of crypto’s crash. Crypto doesn’t need to be involved for their projections to falter. They can be ahead, and be winning the game today. But that doesn’t make them Top dog. Top dog is stable, top dog doesn’t sit at the precipice of another crash.

                Their entire system is built upon pump & dump style investments as a result of the crypto era. They chase quick and easy money. But every time it results in a steep crash afterward. This will be their undoing because this will hurt their reputation, as it already has. The quest for more money, comes at the expense of everything else.

                Top dog doesn’t need to worry about reputation in the long run, because they’ll maintain their place in the long run. An aware front runner will make note of their position and act accordingly. Nvidia is a front runner, planning like a top dog, acting like a top dog.

                They are panicked, because they’re not Microsoft, Google, Amazon, IBM or Oracle. They don’t have a decades long presence in the economy that if they go under, everyone goes down with them.

                These top dogs don’t even need to worry about their stocks because they will get bailed out. Nvidia is banking on the idea that they’re just as needed. But if they really were just as needed, they wouldn’t have to peacock or nudge. They’d just have to threaten that they’re going to go under, and governments would panic in fear of an economic collapse.

                This is a gamble, and one they will lose. Their decision to divide their position and go after lottery tickets, both in the stock market and in regulations will be their undoing.

                If they were needed, they wouldn’t have any need to look needed.