• @gerikson
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    2219 days ago

    SoftBank, one of the big backers behind Stargate, is notorious for WeWork-level funding disasters — but five days from floating the idea to the crash might be a new record.

    I LOLd

  • @FredFig
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    1519 days ago

    I must’ve read the words “Jevon’s Paradox” a hundred times today, I didn’t realize that many people had their livelihood predicated on NVidia going to the moon forevermore.

  • @swlabr
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    1319 days ago

    Working on this take:

    Aside from stitching together a bigger and bigger trenchcoat, has open AI done anything else? Just goes to show how vacuous LLMs are if this is what it takes to catch up/outpace them.

  • @istewart
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    1119 days ago

    We regret to inform you that Stonks have been replaced by Storks*. Go long long legs, big beaks, and affinity for coastal shorelines and wetlands

    *this offer may not be immediately available in all markets due to presence of H5N1 bird flu

  • @selfA
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    17 days ago

    Is the R1 model better than all existing models? Well, it benchmarks well. But everyone trains their models to the benchmarks hard. The benchmarks exist to create headlines about model improvements while everyone using the model still sees lying slop machines. No, no, sir, this is much finer slop, with a bouquet from the rotting carcass side of the garbage heap.

    […]

    This crash doesn’t mean AI sucks now or that it’s good now. It just means OpenAI, and everyone else whose stock dipped, was just throwing money into a fire. But we knew that.

    Slop generators are cheap now, and that’s a sea change — but the output is still terrible slop, just more of it.

    this bares repeating. I’ve seen quite a few people declare that DeepSeek fixes all of the issues with LLMs as a technology, but that just isn’t true. a DeepSeek LLM is still an unreliable plagiarism machine with no known use case trained on massive amounts of stolen data, even if OpenAI and other American ghouls were the ones who did the theft in the first place.

    there’s a small victory in that Altman and friends were exposed very publicly as lying grifters, and that’s worth celebrating. but it’s very important to not get swept up in a hype wave, especially one crafted by people who are much more competent at managing public opinion than Altman & co. from what I understand: no, this thing isn’t meaningfully open source. no, you can’t run the good version at home. sure, it performs great at the benchmarks we know were designed to be cheated. yeah, DeepSeek LLMs are probably still an environmental disaster for the same reason most supposedly more efficient blockchains are — perverse financial incentives across the entire industry.

    but hey, good news for the boy genius Prompt Engineer at your company: he gets to requisition another top end gaming PC, absolutely drowning in RGB, to run the shit version of DeepSeek on. maybe in a couple months he can spin switching from OpenAI’s rentseeking to a DeepSeek LLM startup’s slightly cheaper rentseeking into a mild pay bump.

    e: see david’s reply, I’m wrong about not being able to run the full version at home — but you need $6000 of fairly specific hardware and it’s molasses slow

    • David GerardOPMA
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      17 days ago

      so you can run the good version at home! this thread tells how to build a workstation for it.

      tl;dr 768GB RAM.

      with that, you can run the largest deepseek model, or even open a tab in chrome

      apparently it’s not very fast, but it does in fact do the stuff

      • @selfA
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        417 days ago

        ah, I stand corrected! the figures I was looking at previously were for doing it at acceptable speeds in a data center.

        can you imagine the intensity of the RGB in the boy genius Prompt Engineer’s new $6000 custom top end gaming PC with server components? maybe they’ll have the LLM slowly plagiarize them a Python script that turns on more RGB when the GPU’s under load.

    • @blakestaceyA
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      617 days ago

      yeah, DeepSeek LLMs are probably still an environmental disaster for the same reason most supposedly more efficient blockchains are — perverse financial incentives across the entire industry.

      1. the waste generation will expand to fill the available data centers

      2. oops all data centers are full, we need to build more data centers

    • @wndy
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      318 days ago

      Like, it’s not even THAT much better. I mean, not so much so that everyone should flood it lmao. The main plus was no restriction on tokens used, but that’s useless when it’s getting overloaded all the time.

      I would say it’s just barely noticeably better than the free tier of GPT. Which makes it a little annoying to go back but w/e.

      • @Evinceo
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        218 days ago

        Can’t people run it locally supposedly?

        • @wndy
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          17 days ago

          Not people who can’t afford 100k to spin up their own servers. It’s going to be a game changer for AI startups and such though who won’t have to spend as much as previously thought.

          edit: Basically, numbers out of my ass, but it’s like they reduced the amount you have to spend to get chatgpt-level output from $500k to $100k. Amazing and all, definitely newsworthy, but uh… not directly relevant for us little folk, more about the ripple effects

        • @Architeuthis
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          317 days ago

          The 671B model although ‘open sourced’ is a 400+GB download and is definitely not runnable on household hardware.

            • @swlabr
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              717 days ago

              What? You don’t have a spare $6,000 to run nonsense generators at home?

              Really sorry about this but this sounds like the premise to a shitty boomer joke:

              “If I wanted to spend another 6000 for a home nonsense generator, I’d get married again!”

              etc.