• 4 Posts
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Joined 3 years ago
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Cake day: July 30th, 2023

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  • Do some research about how the city water treatment works. Find out what the issues are. There may already be published studies about the water treatment and tap water quality. Or maybe your city just doesn’t have a good water source to begin with and they’re doing the best they can. Maybe the issue is specific to one area or even just your neighbourhood. Whatever you do, if you’re going to get involved make sure you educate yourself first, to avoid embarrassing yourself.

    Write the mayor and city council about the issues, or go to town halls and present the issues to council.

    If there isn’t a reasonable response, go to local social media, traditional media, write op eds, try to garner support from other like-minded people.

    Go back to city council with more support behind you. March in the streets. With more people behind you, you might be able to get money for independent studies. Do petitions, and bring those to city Hall.

    Rinse, repeat. Get more and more support until you have a big enough voice that the city council has to listen. At each repetition, your support should be growing. If it isn’t, you’re not successfully finding like-minded people - either because you’re doing it wrong or not enough people genuinely agree with you (which may mean you’ll never get change).

    Ultimately you can run for council or mayor and do it yourself.

    Also, check social media and media archives to see if anyone else has brought up the issue or similar issues. There might already be a grassroots group already working on it. Better to join them than to start from scratch.

    One last thing: watch out for people with the more outlandish theories and behaviour (traditionally called “conspiracy nuts”, but I think that’s used too broadly, since sometimes there really is a conspiracy at play). They may try to glom onto you or may be the ones already actively doing stuff. They can take you down less-than-ideal paths. Keep yourself grounded in reality and facts.









  • Machine Learning (and even Large Language Models) do have genuine use cases they excel at and are probably more efficient at.

    One good example is protein folding. ML transformed biomedical research by basically solving the protein folding problem in minutes on a GPU instead of essentially trying to brute force a solution that was millions to tens of millions times more complex. I’m glossing over details, but it’s mind blowing how much better (especially when you consider resource usage) how much better ML is in this case. Think $1 and minutes vs $100000+ and years… for a single protein.

    The problem is using LLMs and Generative AI for things they seem good at but actually aren’t.