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Joined 1 year ago
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Cake day: June 30th, 2025

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  • You wouldn’t gain anything speed or durability wise from disabling swap. Normal ram is always the priority if it is available, so any time the phone retrieves data from the swap it avoids having to relaunch an app killed due to memory pressure, which would take longer. As Android is already pretty aggressive about killing apps to save battery, in the majority of cases the swap would be used to ease the blow of a sudden, memory intensive task like high resolution video editing.

    Let’s assume the phone storage can take 256 read write cycles (which is a low estimate). Considering that phones have at least 256 gigs of storage nowadays that gives an allowance of 18 gigs written per day for a phone with 10 year lifespan. Considering that I very rarely change the contents of the storage and the memory will likely not spill over by that amount, or at all most days, it’s safe to say flash health isn’t a concern.














  • AMD Ryzen CPUs have reportedly seen over a 50% price increase in Japan, likely due to AI.

    … CPU prices could reportedly increase as software developers shift toward running cloud-based AI-related applications locally.

    Who tf is running ai models on cpus? The source seems to be a Chinese report by intel:

    … The goal was to achieve a cumulative price increase of 30% based on 2025 prices, thereby recovering the investment in capacity expansion and meeting the return expectations of the capital market and investors…

    … some users, especially software developers, are choosing to deploy AI-related applications locally, thus creating strong demand for AI PCs … The core growth is concentrated in the high-end thin and light laptop and thin and light gaming laptop user groups…

    So the reason AMD’s desktop cpus suddenly got more expensive in Japan is because Intel is expecting an increase in ultrabook sales? I’m unsatisfied



  • To me agentic ai seems to be a futile attempt at making llms useful in a work context. The idea of having virtual workers who will accomplish tasks and lift their own weight seems appealing until you realize not even hiring actual human workers increases throughput until they can get their bearings. Tools that consistently and accurately do repetitive things is more valuable for an individual than an open ended tool with the potential to solve it all in one go imo.

    I find it hard to believe that llms trying to cover up for their weaknesses with increasingly token intensive methods like thinking or planning will stay economically viable after the “capture the market” phase of the ai industry. It is remarkable that such methods work at all. I can’t imagine there’s nearly enough training data about non-final work or thought processes or planning that went behind producing something, not to mention people might not accurately describe how they reached their solution even if they try to. And even if they manage to print those thoughts into their context, llms don’t produce words through a thought process so it’s dubious how much benefit they can ultimately obtain.

    I think once the ai craze is over people might make tools that use machine learning to automate tasks but I don’t think the repackaged chatbots are it.

    I’ve tried agentic coding using a bunch of llms from ollama couple weeks ago, most couldn’t manage to consistently find the correct file, glm4.7 got pretty far but lost context and produced some irrelevant code.