In fact, perhaps most progress toward justice required "disruption," and that's a bargain price to pay.
12,479 karma · joined April 18, 2014
In fact, perhaps most progress toward justice required "disruption," and that's a bargain price to pay.
https://www.ucsf.edu/news/2023/05/425451/makers-pfas-forever...
So 270 would be 11 standard deviations above normal so 1 in 17,000,000,000,000,000,000,000,000,000,000 people.
Also being a broad or nebulous category doesn’t make it not science… much of what science studies starts broad and nebulous or even theoretical.
And I really don’t understand your point at all. All science starts with observing a correlation and deducing a cause years to centuries later.
But you don’t wait for newton to start believing in gravity
You’re welcome to do your own years of research to learn more (everything, cooking, freezing, drying, blending, adding acids affects amino acids and certainly bacteria in the food) but until then stick with what the studies prove
Like yes you can take any continuous variable and draw as many lines in the sand as you'd like (5 levels of tallness, or even 27 levels of tallness, or whatever) and actually say nothing while apparently sound like you're saying something??
Seems like nothing new, just a better or more immersive form of fantasy for those who can't have the life they fantasize about.
Perhaps it would look like this -- if you replace a worker with AI then you must still pay minimum wage straight into a public benefit tax.
You introduce somebody to your attractive single friend there's a real chance they hit it off and form a relationship. You introduce them to 100 attractive friends, one makes more money, one has a more stable job, one is flirtier, etc then it's both exhausting and none of them seem like a great opportunity.
I think there are certain basic psychological facts that are anti-standard-economics that nerds (and therefore tech companies) almost always tend to be completely blind to. This is one of them.
We mostly don't like them, we mostly do feel disenfranchised, and people are trying to mobilize more political awareness of which politicians are cozying up to data-centers.
One of the biggest complaints isn't the data-centers themselves, but that they use so much electricity that these heinously ugly power-lines have to get put up in what is one of the most beautiful nature areas of the country (i.e. "blue ridge mountains / Shennandoah river / country roads").
> Also, those same people have the most ability to live wherever they want, and can leave.
That's a ludicrous suggestion. The tax alone on selling your house is at a minimum 10%, aside from every other cost, that's basically a 6 figure loss plus all your close family and friends.
> This is wealthy DC lobbyists being a little annoyed about a hum.
No. It's mostly the residents who predate the datacenters who are the most opposed. Western Loudoun was actually mostly farmland one generation ago, and actually had a bit of hippie / homeschooler energy.
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Instead datacenters should be required by law to build underground with noise limits, and required by law to not increase electricity prices and not drain the grid around them. If they can't be profitable without negative externalities then they aren't worth having.
Also the county west of loudoun (Clarke), which has no data centers, has even lower taxes than loudoun. If you compare tax rate in loudoun in 2006 versus 2025 it's 1 percentage point lower now.
Suppose 1/20 people are sadistic, and 1/20 people love eating bitter food.
Let's suppose each question is multiple choice with a T/F.
Let's suppose also 1/10 respondents are bots that answer randomly.
Of the people who answer they like sadism on a given question, 66% will be bots. And of the people who say they like bitterness 66% will be bots.
For simplicity sake consider a simple two-question survey (one question about sadism, one about bitter food).
In this case you will get the following numbers, even if there's no genuine correlation:
[One bot in each category] - 1/40 like both
- 3/40 like bitterness but NOT sadism
- 3/40 like sadism but NOT bitterness
- 33/40 like neither
So you would conclude if you like bitterness (4 people) you have a (1/4) 25% chance of liking sadism, whereas if you don't like bitterness (36 people) you have a (3/36) 8% chance of liking sadism. Therefore liking bitterness would appear to predict to liking sadism (when really both are just predictors of being a bot).
Supposed x% of participants are bots or answer randomly — if we’re measuring a trait that isn’t significantly more common than x% then s big portion of answers for any atypical response (eg I hate other people, I prefer taste of straight coffee beans) will both be random bots and correlate
But afaik this site doesn't even track that many metrics (e.g. does it even count clicks on articles?) so I think what I'm proposing is a bit antithetical to the minimalist nature.
Personally I agree that it's both possible to detect this better and would actually drastically improve the quality of this site if that wasn't the meta and think it's something that should be openly discussed (in terms of practical suggestions).
Many companies run in such a way that there is no bucket for "engineers get to do stuff they know is important x% of the time." So what happens is that things that executives don't understand the significance of all get 0 time allocation. Other teams may be told they aren't allowed to work on something owned by the CI team (again often for legibility reasons).
This is how I work at a "startup" that has just a single test environment that everyone has to share after 10 years of existence.
I think the reality is that a CEO (sort of like a president) only has about 7% control over a company. The rest of it is everybody they've hired -- they are just the brain not whole the body. However they like to believe that they are the most important thing, and quickly disregard everything they don't have the time or specialty to understand (i.e. seeing engineers as interchangeable when one may be a genius who got into MIT and could be advancing whatever field he works in -- while the other is just some random bro who took a bootcamp).
When people talk about something like google succeeding it's easier to give credit to 2 founders or a CEO than it is to track the dozens of brilliant employees who built the best search/mail/maps/ads/etc platforms
That said, it's often easier said than done. We've all worked at places where projects were canceled 3 months in due to all sorts of reasons (e.g. security breach changes all priorities, nobody cares about your database change now).
So I do think there comes a point where an engineer asks themselves -- "How many projects do I have to prepare, how many stakeholders do I have to convince, how many wins do I need before I see tangible benefits commensurate with my investment?" What if I just let the executives set the course and provide my insight if asked, and still get 90% of the pay.
Ultimately this is a guide to work successfully within a dysfunctional system, but nonetheless great advice for that.