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Joined 1 year ago
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Cake day: August 28th, 2023

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  • Hmm, if you’re interested in expanding further I’d love you to share more detail. What specifically in the scenario I proposed would require foresight?

    I suppose you could say the government passing some form of increased welfare could require foresight but even that is primarily reactionary (a reaction to the public unrest from record rates of unemployment and poverty). If you look at the civilian unemployment rate, it’s quite low right now, around 5%. In the worst of times, it’s been 10-15% during which there were huge pushes for the government to step in (ie. covid relief / 2008 financial reforms). That makes me think that if we experienced sustained high (15%+) unemployment it’s quite reasonable to predict that there’d be enough pressure for the government to provide some significant form of relief.

    If anything, my pessimism would stem from social unrest due to the polarization of media, the hyper optimization of content, and similar negative byproducts of capitalism plus advanced optimization. But I view these all as distinct problems separate from the problems discussed here (the economic conditions induced by late-stage capitalism).


  • Everyone here has written echoes of the same viewpoint: the wealthy got too greedy and so now the whole world will die as they stand and watch.

    While I understand the allure of such narratives that paint a world falling into pieces at the hands of the ultra-wealthy, I think it’s worth exploring an alternate vision of late-stage capitalism. One where despite being grim, we avoid descending into a completely unrecognizable dystopia.

    In this scenario, nearly the entire workforce is displaced by robotic and AI-driven automation, leading to a massive societal shift. With most traditional jobs gone, the public faces mass unemployment and widespread poverty. Outcry erupts as the majority falls below the poverty line. With nearly all jobs displaced, for most people only two options remain: attempt entrepreneurship or face unemployment.

    Confronted with growing public unrest, governments reluctantly implement basic welfare measures such as small universal basic income or food stamps, providing just enough for people to get by. Meanwhile, the majority of global funding is redirected toward research and development, primarily powered by these new forms of automation. This fuels breakthroughs in production and technology, eventually driving down the cost of quality goods. Over time, even those relying on minimal welfare begin to see modest improvements in their quality of life.

    Meanwhile, the wealth gap grows wider than ever. Billionaires, enriched by the automation economy, turn their attention to ambitious but arbitrary ventures like constructing moon bases, developing underwater cities, or investing in life-extension technologies. Occasionally, these projects destabilize society—whether through anti-competitive practices or efforts to sidestep government oversight—but as long as governments hold their ground (a non-trivial task), their effects on the majority remain limited.

    What results is a fragile balance: a world with basic welfare programs supplying the masses, incremental technological progress, and a stark divide between the majority and the ultra-wealthy. It’s far from utopian, but it avoids outright collapse. As innovation continues, life gradually improves for everyone—even though the wealthiest always dictate the terms and reap the greatest rewards.



  • When you consider the price of a used android (ie. Oneplus 6T for $80 on ebay) and compare it spec for spec with a raspberry pi, it’s actually a really good deal. Like you get:

    • Built in backup power supply (battery)
    • 8-core power-efficient CPU (SDM845)
    • Embedded sensors (microphone, magnetometer, gyro)

    The way I set mine up is to run the server directly on Android using Termux, having an app autostart Termux on boot, and making sure to disable battery optimizations on the app. And then I just had the phone always plugged into the outlet to maintain the battery (and of course android would just trickle charge / disable once full charged).

    Of course this isn’t perfect because you still have much more variability in play (at the OS level) than an RPi (along with not having a standard environment like debian unless you use proot), but it overall is a very powerful setup that works quite well.



  • I respectfully disagree. Any high quality creator is tangibly penalized by YouTube’s recommendation algorithm for not optimizing their titles and thumbnails. A rare few choose to take this penalty but I don’t blame the many quality creators who choose to take part in the game that YouTube has made for everyone.

    Yes, the alternate titles may not be perfect, but I’d take any random person’s attempt at a title over the hyper optimized ones any day because I’d rather make an informed decision to watch something even if there is some degree of inaccuracy than to make a completely uninformed decision based on what an algorithm predicted would most likely get me to click and get hooked on a video irregardless of my own will and whether I am satisfied at the end of watching it.


  • Sorry but has anyone in this thread actually tried running local LLMs on CPU? You can easily run a 7B model at varying levels of quantization (ie. 5 bit quantization) and get a generalized prompt-able LLM. Yeah, of course it’s going to take ~4GB of RAM (which is mem-mapped and paged into memory), but you can easily fine tune smaller more specific models (like the translation one mentioned above) and have surprising intelligence at a fraction of the resources.

    Take, for example, phi-2 which performs as well as 13B param models but with 2.7B params. Yeah, that’s still going to take 1.5GB RAM which Firefox wouldn’t reasonably ship, but many lighter weight specialized tasks could easily use something like a fine tuned 0.3B model with quantization.