I don't consider 30 minutes away from town the "boonies", that's more like a normal commute. The boonies would be like a 3 hour drive in the Sonora desert.
Mining towns used to work in the days when one parent worked full-time and one parent raised kids full-time, and job security, unions, and pensions were a thing.
In modern times, both parents often have career ambitions, and the modern capitalist economy and housing pricing has greedily recalibrated to every family needing two incomes. So you're not going to have many families willing to move to the boonies unless you (at the bare minimum) hand out doubly-high salaries.
Very likely that's not enough though, as it's also a massive financial risk to them if you can just lay them off after the next earnings report with no pension to continue supporting them. Most modern families would rather stay where jobs are slightly more likely to exist.
They need to hire IT, maintainence, and security to run the datacenters, and there aren't many qualified people in the boonies. Small towns are better targets, and honestly also just objectively less damaging to the environment.
None of this NIMBYism is about the datacenter itself, it's all a protest against AI making the economy really shitty for them.
Part of the problem is the rest of us are broke as well and taxed to death so we don't have much left. If they paid you well, we wouldn't be able to afford your books.
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Notably, unlike Claude, there is not an opt-out option for the model training part. The TOS explicitly allows Kimi to train on your code.
Exactly. A lot of academics seem to not get the fundamental problem: You don't know the future.
You don't know what Trump is going to say 2 hours from now. You don't know what natural disaster is going to happen tomorrow. You don't know what war is going to break out next month.
NOTHING in your past data contains anything that can tell you these events are going to happen.
Now markets may have idiosyncratic residuals from momentum and reversion effects that you can quantitatively model and profit from, and that's a tradeable signal, but the way you do that is realizing that a certain coin is slightly biased and trade it a million times, averaging out the news shocks and recovering the residual idiosyncratic bias that you found.
Trying to forecast actual prices beyond ultra-short horizons is trying to predict those shocks, which is a fool's errand. You have a system with a signal to noise ratio of 1:100, and you're effectively trying to predict the noise instead of the signal.
They should also be forced to walk around town with a GDPR cookie banner pasted over their face covering half of their field of view. And then although automatic doors open for most people, for them specifically, the automatic doors shut. The doors are postered with "would you like to subscribe" newsletter ads. They have to manually open each one of them.
Government cannot exactly "bar" terms of service. ToS isn't law. The most they can do is say they're unwilling to enforce them.
ToS is just conditions that you agree to in order to use a private service that is provided at-will. I can have a private coffee shop where the terms of service are that you must wear red to enter, and if you're not wearing red, you are not welcome on my property.
So it would be upto OpenAI and Anthropic to enforce them on their own terms (by banning accounts and IPs).
Right, the California HSR route doesn't travel through any really dark sky regions anyway.
My point was that if you want replace, say, San Francisco <-> Las Vegas with HSR you're going to inevitably have to wreck a chunk of Bortle 1 dark skies in the Sierra or Death Valley.
Doesn't mean I'm against HSR but it has to be done thoughtfully.
The main advantage is you can get to the station 20 minutes before your train and board, they are almost always on time, and they start moving almost immediately after you board them.
For trips less than 1500km that's usually a big win compared to the amount of buffer time you typically add for airport travel unpredictability, and then the the amount of time you spend on the plane NOT in motion on both ends.
> replacing the majority of air travel with high speed rail
I absolutely LOVE high speed rail, but I will note that it is correlated with far more light pollution than air traffic. I say correlated because typically high speed rail is routed through high-density population centers, but if there aren't population centers, you'll have to have plans to create them in order to support the rail system itself.
Basically there is nowhere in the world that has both high speed rail AND suitable for astronomy. If you want to find dark skies in China for example you have to get far away from all the high speed rail areas of the country.
Starlink gets a lot of flax for it but as an avid night sky photographer myself (IG: @dheeranet) who regularly goes to Bortle 1 parts of the world, I haven't found them to be an issue at all.
1. They are only visible when they are spinning up to orbit
2. They are too dim to desensitize your eyes, and are extremely easy to remove with the most basic of outlier rejection techniques; netizens often amplifiy outliers by max-stacking instead of outlier-rejected mean-stacking to make Starlink look much worse than it is
3. Lights from planes have ALWAYS been much, much, much, much worse than satellites. They still aren't particularly a problem for imaging if you know how to outlier reject, and their paths are known, predictable and trackable
I'm not an Elon-fan or anything but just giving a dose of objective reality here.
Not to detract from TFA's real issue which is light pollution from cities -- that's an actual issue as the regions of dark sky are shrinking.
You're nitpicking at details. I'm sure you're smart enough to figure out how to write it so that this isn't an issue, but it seems you're more interested in "taking the other side" rather than thinking together about how to increase job compensation transparency.
Here's the problem with minimums: Companies posting ranges of $100K-$900K. Yes, I've seen them.
Here's a hint for everyone else: For small companies and single openings they can just aggregate mean/median/std by job level (E5 average, M1 average), or aggregate horizontally by team (HR average, ops average), whatever. Anything to increase transparency. If you're criticizing the math instead of building on the math, you're clearly against job transparency.
I'm just tired of regulators realizing the right things to regulate but not implementing them correctly.
Job postings must include a salary range? Who the fuck thought of that? Did they even ask a mathematician whether providing the min() and max() would be useful rather than mean(), median(), and std(), which is what the law really should require?
https://www.quora.com/What%E2%80%99s-wrong-with-OpenID-Why-h...