Father, Hacker (Information Security Professional), Open Source Software Developer, Inventor, and 3D printing enthusiast

  • 4 Posts
  • 356 Comments
Joined 3 years ago
cake
Cake day: June 23rd, 2023

help-circle
  • I’ve been researching this a bit… I’ve come to the conclusion that there is no AI bubble. In fact, we’re only just getting started down this road. Unless there’s some massive 100x efficiency breakthrough in training AI and inference, the entire world is going to be building seemingly endless AI data centers (and the normal compute kind, e.g. for stuff like AWS, Google/YouTube, Meta, banks) for at least a decade. Probably a little longer (12-15 years before demand levels out).

    Everyone thinks that “AI data center” means ChatGPT, Claude, Gemini, etc but there’s 10,000x more demand for AI than those services. Think: Pharmaceutical companies trying to find proteins, scientists (and big agriculture!) trying to model the weather, and other businesses trying to automate stuff. Not just software; robots and things like conveyor belts.

    Another example: Ever use one of those self-checkouts that’s mostly just a camera pointing down, where you place the stuff you’re purchasing? That uses AI too.

    Having said that, there is a great big bubble in AI: OpenAI, specifically. That will definitely pop one day. And hopefully, the DRAM bullshit will go along with it.









  • Ah, the good old days when your “dumb” refrigerator would kill children playing hide and seek because the latch wouldn’t open from the inside. When it was lined with asbestos because that’s literally the best insulation that exists excepting aerogel. When the mercury thermostat would fail—leaking mercury on to your food (and aerosolizing some which would be breathed in as soon as you opened it)—and it would freeze everything inside, complete with an interior wall of snow that could take days to defrost. It used old school freon, destroying the ozone layer. Or before then, fun highly toxic gasses like methyl chloride!

    Those were the days! When a breeze through the house on a day with wonderful weather could blow out the pilot light in your oven, slowly leaking gas into your house, exploding and destroying the entire home late at night while everyone is asleep.

    Then the wonders of electricity came along to produce ovens that were hooked up to 220V lines without a grounding wire, and wiring that would slowly fail over time, eventually making contact with the metal frame, electrocuting anyone who touched the device—or anyone that touched the person touching it.

    Ovens were built different “back in the day”! They didn’t have anti-tip brackets, resulting in loads of children sitting on the oven door, spilling boiling liquids down upon them.

    The best were those old washing machines, though! You could lift up the lid and look inside to see your laundry spinning at high speeds! Just don’t reach your hand in, or you could find out what the term “degloving” means.

    Ah yes, the good old days of appliances.






  • She didn’t dial anywhere near enough numbers

    Not necessarily! This particular phone had a feature that let you set shortcut numbers. It was an advanced form of the “long press a single number to dial a particular contact” feature that came before it. So you could go into your contacts and—via a series of absurdly complicated menus for such a simple device—you could set “7752” as the shortcut number to dial say, your bank of fax machines that somehow deliver the equivalent of 100Base-T Ethernet speeds.

    “Tell me how old you are without telling me how old you are” 😢


  • I recently stayed at a rental property that had this (actual photo):

    Photo of a NuTone Intercom with a built-in CD player and FM tuner

    I tried to get it working but none of the remote panels worked. They were all disconnected somehow (owner probably cut the wires to prevent shenanigans by guests cranking the volume then leaving it like that). The CD player worked (central panel only) but oddly, it couldn’t pick up any FM stations. It would tune to them (“scan” feature worked) but they only ever produced static. I suspect the capacitors used in the amplification circuit dried out or something got corroded after being in a “regular ocean salt spray” area (it was on a beach) for such a long time 🤷


  • Wow! This brings back memories… It was a Soul Crusher: A primitive technology used to commune with the dead over long distances. I’ll explain…

    These devices used the “Afterlife Toll” (AT) command set, invented by someone named “Hayes” which I believe was just a nickname or mistranslation of Hades. With the correct invocation, you could whisper into the great beyond. Here’s an example:

    ATDT 6665551234

    Translated: “Afterlife Toll, Death Touch <helliphone number>”. After this invocation, the user would hear the pleasant sound of souls being crushed in order to make the afterlife connection.

    Of course—due to the popularity of such devices—crushing souls over long distances could get expensive so a number of Incorporeal Service Providers (ISP) sprang up to make it cheaper and easier than ever to crush souls from anywhere.

    Cool fact: This is where the term, “soul crushing machines” comes from! These days, soul crushing is fully automated and far beyond the measure of Beings Per Seance (BPS). Nearly every computer is shipped with an ethernet connection and practically everyone is walking around with devices that can commune over WIFI (Wailing Incorporeal Fidelity).

    In fact, our Incorporeal Technology (IT) is so advanced, you can have a soul crushing experience from anywhere in the world at all hours of the day, every day!



  • I literally said I’m using qwen3.5:122b for coding. I also use GLM-5 but it’s slightly slower so I generally stick with qwen.

    It’s right there, in ollama’s library: https://ollama.com/library/qwen3.5:122b

    The weights and everything else for it are on Huggingface: https://huggingface.co/Qwen/Qwen3.5-122B-A10B

    This is not speculation. That’s what I’m actually using nearly every day. It’s not as good as Claude Code with Opus 4.6 but it’s about 90% of the way there (if you use it right). When GLM-5 came out that’s when I cancelled my Claude subscription and just stuck with Ollama Cloud.

    I can use gpt-oss:20b on my GPU (4060 Ti 16GB)—and it works well—but for $20/month, the ability to use qwen3.5 and GLM-5 are better options.

    I still use my GPU for (serious) image generation though. Using ChatGPT (DALL-E) or Gemini (Nano Banana) are OK for one-offs but they’re slow AF compared to FLUX 2 and qwen’s image models running locally. I can give it a prompt and generate 32 images in no time, pick the best one, then iterate from there (using some sophisticated ComfyUI setups). The end result is a superior image than what you’d get from Big AI.


  • I just added up how much it would cost (in theory—assuming everything is in-stock and ready to ship) to build out a data center capable of training something like qwen3.5:122b from scratch in a few months: $66M. That’s how much it would cost for 128 Nvidia B200 nodes (they have 8 GPUs each), infiniband networking, all-flash storage (SSDs), and 20 racks (the hardware).

    If OpenAI went bankrupt, that would result in a glut of such hardware which would flood the market, so the cost would probably drop by 40-60%.

    Right now, hardware like that is all being bought up and monopolized by Big AI. This has resulted in prices going up for all these things. In a normal market, it would not cost this much! Furthermore, the reason why Big AI is spending sooooo much fucking money on data centers is because they’re imagining demand. It’s not for training. Not anymore. They’re assuming they’re going to reach AGI any day now and when they do, they’ll need all that hardware to be the world’s “virtual employee” provider.

    BTW: Anthropic has a different problem than the others with AGI dreams… Claude (for coding) is in such high demand that their biggest cost is inference. They can’t build out hardware fast enough to meet the demand (inference, specifically). For every dollar they make, they’re spending a dollar to build out infrastructure. Presumably—some day—they’ll actually be able to meet demand with what they’ve got and on that day they’ll basically be printing money. Assuming they can outrun their debts, of course.


  • I personally love glm-5 and qwen3.5, specifically: https://ollama.com/library/qwen3.5:122b

    I’ve used them both for coding and they work really well (way better than you’d think). They’re also perfectly capable of the usual LLM chat stuff (e.g. check my grammar) but all the models (even older, smaller ones) are capable of that stuff these days.

    For a treat: Have someone show you using some of these models to search the web! It’s amazing. You don’t see ads, you don’t have to comb through 12 pages of search results, and they read the pages that moment (not cached) to give you summaries of the content. So when you click the link to go to the content you know it’s the thing you were looking for. They’re not using a local index of the Internet, they’re searching on your behalf using whatever search engines you configured. It’s waaaaay better than ChatGPT (which uses Bing behind the scenes whether you like it or not) or Gemini (which uses Google, obviously). The (self-hosted) LLM will literally be running curl for you on Google, DuckDuckGo, Bing, or whatever TF else you want (simultaneously) then reading each of the search results and using your prompt to figure out what the most relevant results are. It’s sooooo nice!

    FYI: Ollama.com’s library page is actually a great resource for finding info on all the models that can be self-hosted: https://ollama.com/library