• 18 Posts
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Joined 6 years ago
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Cake day: August 24th, 2019

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  • AI (LLMs more accurately) is just technology. It’s like saying let’s send all steam machine proponents to gulag. The problem is who controls this means of production. China does very interesting things with AI, it’s only in the west that the assistant/therapist/friend model is growing and being pushed on people and that they want power that doesn’t even exist yet to sustain it - of course they do, they’re tech companies. They want to control electricity because their tech doesn’t work without it. Altman even said he was working on something beyond electricity - he’s delusional, but he still believes it.

    But China conversely is investing heavily in renewables and solar power, to the point that in China power is not even considered a problem anymore. Their grid always has 2-3x more power than they use and pretty much all they build nowadays is renewables.

    Whether we like it or not AI is clearly here to stay. Maybe it will all fizzle out in some years, who knows - floppy disks also rose and fell to give way to the CD. But we see even socialist countries getting into AI (Cuba is announcing their chatbot, and China is soon to be leading and has already caused two huge scares in the US tech scene), because the technology is very important to get into. The US plans to use it, and is using it, in war, for example. If China said “no we don’t like AI” they would just get picked off by this tech. They have no choice but to understand and embrace it in order to level the playing field.

    Frankly Europe is the one that needs to step its game up but we’re 20 years too late for that. We gutted our tech in favor of American software and now we have nothing except startups whose sole purpose is to get bought out by Google and then retire on the money.




  • I agree with your impression, but apparently it’s really the best. With grapheneOS though and anything from google wiped, you only want the pixel for the hardware. Medhurst is an investigative journalist who covers palestine among other things. He is/was sometimes on Iran Press TV. I don’t think he’s an op because he’s been harassed by the police several times, had his equipment seized etc.

    Your phone still connects to a cell tower, satelites and even other devices when you want to use it and chinese manufacturers don’t worry about security because it’s not a worry in China, so the hardware doesn’t have any of these features. according to him at least.




  • Keep in mind this is the case for most US tech companies regardless of AI. Ever since Google became a giant, in the late 2000s they started buying up competition. Since then it’s become a dream of silicon valley techs to make the dumbest saas possible just so that a bigger company will buy them out and they can retire. The only profitable tech companies are basically the giants, and everyone else is finding investors to keep afloat year to year.

    Amazon itself makes the biggest share of its profits on AWS, not on the online store.

    Their promise to investors is “we’ll find a way to make it profitable eventually” and that day likely never comes. Spotify was notoriously in the red for most of its existence. Nowadays they report net profits, but I find that hard to believe considering nothing has changed in their model and their other ventures (like the “car thing”) failed miserably.

    In regards to AI this may open up more open source efforts because these are not driven by profits and there is a flourishing ecosystem there already.




  • I assume these are local models? What GPU do you run them with? I don’t even have my new gpu yet (soon inshallah) so there’s no point in me downloading a bunch of models yet lol.

    Also, I’d be interested to read that guide once you are done with it.

    We’ll put it up on prolewiki but I’m not sure how quickly it will get written. So far only one other person has participated, though two PW editors with experience in LLMs told me they’ll contribute soon. If you know the technical aspects deeply, I can add you to the project, it’s an etherpad collab document. My knowledge is very limited so I was able to write some parts, but others completely escape me. As a beginner’s guide I want it to basically teach everything from scratch, no matter how long the guide gets. People will jump to the sections they need to read anyway.



  • I am actually writing a guide on AI (with help from some PW editors and other interested comrades) and this is actually something I tackle in it. Of course the snake oil salesman will tell you his snake oil cures everything. But there may also be some actual medicine in it.

    Tbh I see OpenAI as a dinosaur, going the way of Facebook. Their model is bloated and huge, but outclassed by other models, including the open source deepseek. In fact, asking deepseek it only made 1 mistake on it, including South Dakota (“There is an R in South”), but it got every other one right (there’s supposed to be 21 states if you wanted to know, not counting Puerto Rico). It did need to think for 150 seconds which is a long time for such a question, but it’s also time during which I’m free to do something else while it computes. This is just my opinion, but I think that openAI is already on its way out. Their oss-200b model, which is open-source (something they never did before) is them trying to compete against much better Chinese models that compute at a fraction of the cost.

    Gizmodo makes a few good points and reminders at the end, even if it comes after a full article of nothing - but that’s just my own value judgment on the writing haha.

    Yes, a calculator has no margin of error - provided the user asks the right question. If you ask a calculator 2+1 because you’re terrible at math, when you wanted to ask 2+2, then it will confidently give a wrong answer too.

    They are also correct that you shouldn’t blindly trust the tools, but that goes for everything. Perhaps it needs to be reminded more often with AI, but I also don’t necessarily trust that my computer correctly installed a software package. How do I know it did? When I can successfully use it. Sometimes you installed something with the wrong parameters and it crashes when you try to use it, no AI involved there.

    I think these “haha I tricked AI look at how dumb it is” articles would have a much better angle approaching it from “here is what you shouldn’t ask LLM and what you should ask instead”. Which is going to be part of the guide we’re writing. I asked deepseek the same question (“How many US states have the letter R in them?”) in a new chat but added “make a python script” this time. It took only 7 seconds to think and gave me a quick script that outputs the correct list when ran. Unfortunately deepseek doesn’t run code, but chatGPT or local models (through an interface such as Open WebUI) can.

    Meanwhile Google doesn’t have an answer for the question in its search results. It might have had it in 2017 when search was good, but it doesn’t currently have it.

    But since it’s literally just five lines of python (the big part is building the array) I think this is a great introduction to scripting for people. You don’t have to shut your brain off when using AI, just like mathematicians don’t shut their brain off when using a calculator, they ask for the proof (e.g. 20/4 to confirm that 5*4 = 20… but with much more complicated math).

    Ultimately AI is clearly here to stay and is getting better year over year, not worse, provided it’s handled correctly. It’s software, and software works the way we want it to at the societal level. So it’s not so much a problem with the tech but with the mode of production. The bourgeoisie competes with each other in the anarchy of production, thereby creating new tech that improves productivity, but also sharpening the contradictions as the rate of profit keeps falling. AI, like all machines, does not produce profit but only outputs what you put into it.

    To leave this tech solely in the hands of the bourgeoisie would be detrimental for several reasons. In the same way that we have to know how tanks work because they are part of the battlefield, we have to know how AI works too.

    It’s debatable whether AI is on the same level as the steam machine in terms of respective productive forces but it doesn’t have to be. China is using AI (not just LLMs) to do dizzying stuff. As far back as 2023, when LLMs were still in their infancy, China used a neural model to map out the electrical cabling on a new ship design. It took the AI 24 hours to achieve 100% accuracy while it would take a team of engineers a full year.

    Tech capitalists want to focus their AI on the ‘companionship’ and ‘assistant’ uses because it looks better in marketing, and it distracts us from our objective material conditions while they continue to siphon money into their pockets. I mean, Musk announced that he wanted to put humanoid robots on Mars next year (heard that one before lol), while his Optimus models are still being controlled remotely by people and are clearly not capable of independent tasks. Meanwhile you can buy a Unitree humanoid model and program it yourself at home to do whatever you want autonomously.

    Yes AI is displacing jobs, but this is true of all capitalism, not automation. Automation should liberate us from labor, not from livelihood. These humanoid models, which can serve in a transition period between fully-automated workplaces and current human interfaces, use image recognition models to recognize literally anything they look at, which they use to interact with the world. Previously without AI you could have software recognize maybe 30 different objects in total, and without full accuracy.

    But of course they sell bullshit, it’s what capitalists do. I’m sure in the age of the steam engine there were tons of “revolutionary” designs the inventor knew didn’t work, but they still tried to sell it.


  • SMRs are meant for data storage aren’t they? Which is not to say they can’t write at all, they just don’t have as high speeds.

    For AI models specifically the file just lives on the HDD, it gets loaded into Vram (and then CPU and RAM if you don’t have enough Vram for it) when you use it. For everything else then probably yeah, I don’t even know what kind of HDDs I have lol. Seems difficult to find 7200 rpm ones over 5400 but tbh with the prices of SSDs nowadays, I’m probably going to replace my last HDDS with SSDs. If you’re looking for 10tb or huge archival size then it’s probably still worth getting an HDD, but for a 1-2tb drive it makes more sense to go SSD I think.




  • I estimated that to translate ProleWiki from English to 5 languages (the API charges per input tokens and output tokens, i.e. what you feed it -> english content and what it outputs -> translated content) it would cost us maximum 50$ with deepseek API. ChatGPT is so expensive I didn’t even try, it was going to be in the hundreds of dollars lol. The output per 1M with deepseek is 50 cents in the off-hours (easy, just run your code during the off-hours automatically) and gpt’s is 1.6$ for their “mini” model, which is still 3x as expensive.

    There are other chinese models coming along, I think xiaomi is making one. They’re also innovating in image and video generation models but for text models. One of them that came out shortly after deepseek is the one that someone said was too cheap to meter (because it literally uses so little resources to run that it makes no sense to even keep track of usage!), but I haven’t heard more about it since.



  • It seems you can run a deepseek model very well with a ~400$ GPU. It’s not cheap, but it’s very accessible compared to having 6 gtx 4080s (1500 each) to reach 92gb Vram. Most motherboards will also handle two gpus, so you can get a second of the same later to double your Vram.

    It’s not gonna be the full model like in this video but it’s still advanced enough for some tasks apparently. Instead of the 792b model you’ll get like 32 billion parameters (quantized), or 8b parameters in the unquantized.

    Actually I tried with my 2019 GPU and I could run a model, it was a bit slow but nothing major. But it was not a huge model either, and you’re also limited in context size for bigger tasks. I think deepseek especially because it’s so efficient is much easier to run. Even the full deepseek model only takes up less than a terabyte of space - of course it’s a lot in absolute numbers, but it’s pretty much what any SSD comes with nowadays (and an HDD that size costs almost nothing now).

    The API access is like 50 cents per 1m tokens (so about 1m words) you put into it in the off-hours too. It’s so, so cheap soon api access will probably be too cheap to even keep track of and we’ll see entirely free cloud models.



  • At least some of them appear to be AI, it’s tough to tell from the timelapse speed but pausing the video and manually scrubbing shows telltale signs. In the second video for example, cars park in front of this wall out of nowhere:

    Then leave in some amorphous blob formation:

    Just as a random nondescript vehicle transforms into reality out of nowhere and intersects with the wall:

    In the video with the green roof, the camera actually rises vertically. Playing at full speed it seems like the buildings are sinking, but scrubbing through the video slower shows that the camera is actually moving up, not the buildings moving down.

    Unfortunately this is the world we live in now…