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Joined 2 years ago
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Cake day: March 15th, 2025

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  • Currently, using the Strata backend with Qwen-Flash-Next. It has successfully made 4 save game editors, 2 plugins, and did some work on La-Mulana 2006 to make the controls and graphics play nice with Windows 11, plus my gamepad. The DLC restoration mod is largely successful, I am doing QA for making the DLC accurate to what was offered in the ad copy.

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    Hermes Agent is my model of choice, and I have Strata using 256k context, on a IQ3. I find that Next-Flash is much faster than the smaller 27b, and has more personality. Sometimes it can get a bit loopy. I typically have the AI keep a bible of findings, and start a fresh Hermes session - then tell it to condense the information from the old workspace and session into a more relevant version. Save on context, and makes it more effective since it discards findings that have been superseded.

    Hardware wise, a TRX50 AI TOP motherboard, 7965WX CPU, RTX 4090 and x2 RTX 3060, with 128gb of 5600 RDIMM. Down the line, I might try some GPU unlockers when other folk have tested them for bugs. So about a month or two?

    https://github.com/JustAResearcher/gpu-unlock-ada

    https://github.com/Zagitta/gpu-unlock

    https://github.com/impacifist/Windows-GPU-UNLOCK

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    I bought my memory and the CPU from Ebay, for prices a bit lower than at Newegg. If I could redo my GPU purchases, I would have gone with a RTX Pro 4500 Blackwell. That has 32gb of VRAM, and occupies a single double-width PCIe slot, and sips energy. The RTX 4090 is only 24gb, and takes up 1 and 1/2 of my slots.

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    Qwen-Flash-Next is an experimental model, the official version might come out in a month or so. If it is the same size or smaller, I will switch to that as my main driver. My current AI model feels useful to me, but clearly has raw aspects to it. Vision is a big one, since this AI can fail to see or understand details.










  • AI helped me with my voting ballot. I asked Kagi’s AI to research the ambiguous candidates and propositions. I had it put them into a political alignment chart - left/centrist/rightwing. Addendums for candidates included things like whether they had criminal convictions or corruption, stance on vaccinations, how they feel about “tough on crime”, the homeless, ect.

    For propositions, the political alignments had a fourth entry added, where the yes/no included the wealth level of backers for a position.

    This is very useful, completing in a hour what would have taken a week of research. Very useful for digging into the mechanical details of a proposition, like whether it prevented the replacement or supplementing of a measure.





  • Not improvements to the AI themselves, but rather the software that runs them. Backends like Unsloth are typically generalists - they are compatible with all sorts of hardware, but in exchange, they don’t incorporate the latest improvements or ideas. Projects run by pure human implementation tend to require a lot of oversight to ensure that additions don’t break functionality.

    AI is really good at collecting and aggregating information. This makes them ideal for creating tailor-made products that have a narrow focus, since they raid many Githubs and papers, then attempt to make them into a product. Strata is one such backend, which is specially designed for Qwen Next-Flash.

    Strata runs much faster than Unsloth and other generalist backends, but lacks flexibility in what it is suited for.


    At least, that is my admittedly basic understanding of the situation…