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Joined 3 years ago
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Cake day: July 20th, 2023

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  • I literally just bought a satellite 1.1. I bought an atom echo to POC whether I could get reasonable wake word + stt + LLM running locally with good latency with the intention of building my own speaker afterwards.

    I went with the satellite 1.1 because:

    1. I haven’t done a good audio driver circuit since university
    2. Getting 2-3 PCBs printed and SMD soldered sounds like a PITA
    3. I didn’t want to design an acoustic cavity
    4. Satellite 1.1 w/ xmos is just really hard to compete with, and the on-board humidity and temperature and stuff removes the need for me to have a distinct sensor for those in that room

    It’s a bit more expensive but I’m really optimistic. It hasn’t arrived yet, I’ll lyk how I like it when it is delivered!

    I saw a project (echomuse) that converts an EchoDot gen 2 into an HA speaker that I thought about doing as well but I didn’t really wanna spend $100+time when I could spend $200 and no time for a better product and support a cool company.







  • I mean, yeah. Asking “do xyz make no mistakes” won’t get you what you want. Come up with a plan, decide on what constraints matter, pick libraries you want to use. Decide what doesn’t matter. Generally around now I feed it my plan and ask it “do you think I’ve missed anything?” and read what it suggests and see if I agree with any of it.

    From there, plan out what incremental progress looks like. Maybe start with the UART/I2C/SPI library and just reading firmware version off of each child component. Then ask it to go through the plan, increment by increment. Review everything as it does it, watch the console and redirect it if it’s making poor choices or just things you know will box yourself in in the future.

    On my best day in university my project this weekend would have been weeks of work. It took me a day, not including soldering and packaging after the electronics were functional. It’s just undeniably faster at this point. Even if the only thing I used it for was to open the serial port, watch the logs, and fix any bugs I introduced, it would be faster. But you can feed it whole datasheets and it’ll construct a client library for your device essentially perfectly on the first try.

    I have serious ethical qualms about how LLMs were created, how they’re going to be used, the inequality they create, the finances of the industry behind them, the environmental impact… but from a purely technical perspective they can be very powerful tools. But you need to already have domain knowledge to be able to massage it properly - “everyone is engineer” still isn’t reality. Someone with experience and good intuition though…












  • This is conjecture because I can’t access the full paper at this time, but based on:

    The learning losses are concentrated among roughly 80% of AI users whose behavior is consistent with homework outsourcing, as indicated by exceptionally short homework completion time coupled with high homework scores.

    I’m guessing this is an artifact of “students under higher pressure to perform are more likely to use AI more thereby lowering their scores”. Given Chinese patriarchical cultural biases, I’d imagine boys are under higher pressure on average, thereby leading to greater usage.

    So perhaps it’s actually the second one, as the abatract is unclear if they’re studying performance relating to usage or not. Without checking methodology, it’s unclear if they’re controlling for usage.