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Joined 3 years ago
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Cake day: August 24th, 2023

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  • There’s usually more than 1 way to do something.

    Sometimes people get caught up on wanting to do it the best way, and then they just dont do it at all.

    If there’s an easier, less ideal, maybe slightly more wasteful way to do something, and its the difference between doing it or not, just do it that way and dont get hung up on perfection if the alternative is not getting it done.

    If its something that needs to be built into a habit, it might be enough to get you started, and then maybe you can move on to the better way in the future.

    Edit: just to clarify, often times the outcome is the same but people get caught up on the how vs just getting it done. Don’t get caught up on the best how if there’s another way that’ll also work that you will find easier to do.














  • If anything i think the better comparison is you use more power watching TV or gaming than you probably will using AI in the day if you do either of those 2 things.

    The issue is training takes a lot of power, and because we can’t run the hardware locally our usage is also placed in these data centers which put pressure on a specific area instead of distributing the same power usage.

    I saw a post a couple days ago about a company etching the model weights into silicon chip and they made a 8b model that could do 16k t/s and once made are relatively cheap to produce, and in power requirements, and would only get better. Just need to make sure they can be recycled well as they’d end up on a 1 to 2 year cycle like phones. Model to chip in 60 days they said.

    So maybe that’s the future solution to distrubuted usage, but we would still need to solve training, but we could just mandate these datacenters must build their own renewable power and it would be less is everyone could run their own local inference.