> I could not imagine this ever happening when dealing with the IRS.
Have you tried? I haven’t tried it with the IRS, but I have tried asking my states permitting and planning department about the legality of various rental schemes for a property (that I didn’t own) and they were happy to look up the permits and tell me that indeed what I was asking about was not legal for that property. And further they let me know that tons of people do it anyway and that they don’t really check, but it’s a risk.
Thank you, I didn't know!
I'd love to, but I'd need another 24 hours in a day to also process the data - I'm glad I can build on a work of others and use the friendly APIs :).
I'm in this situation with my car right now, I have the money to pay it off but why bother when I can make the monthly payment with savings account interest.
Depends... It would depend on the price to service the mortgage. I would do a quick model to see the timeline to "break even" on paying in full verses the total amount of interest paid to service the loan for duration of the term.
> If they weren't, Delta would say so, since it makes them look better. That they won't say means the parts were used in service.
More likely they would just never comment whether it makes them look better or not, because otherwise for the reason you stated you could always gather the information they didn’t want you to have in the negative case.
It’s because most of the people doing these computations don’t have the capacity to become experts in multiple fields. They understand the math and analytics very well, and they expend all their time thinking about that, not about type systems, memory management, etc. Python lets them code without having to think about a lot of that stuff so they can focus on the things they care about. These aren’t computer scientists or programmers, they’re meteorologists, astronomers, oil and gas analysts, investment bankers etc. That’s why some truly great computer scientists and programmers invested their time into building these tools for python vs other languages.
The explanation I’ve always heard for why New Zealand was settled by Polynesians so late is that they preferred to start their voyages against the currents when they were fresh so that they wouldn’t have to fight the currents on their way back if they weren’t able to find any new lands to rest and recharge
Kiwi here, I haven't heard that before. New Zealand is very isolated and far south. Polynesian explorers went from the North to the South, so New Zealand was last.
I am unsure why there wasn't earlier immigration from Australia, possibly technological or cultural. Australia is huge, so maybe there wasn't population or resource motivation to explore and settle new lands.
> I am unsure why there wasn't earlier immigration from Australia, possibly technological or cultural.
Indigenous Australians were not mariners, they reached australia by island hopping, and at a time when the sea levels were even lowers and thus the distances between islands were lower (Tasmania was a peninsula at the time).
While NZ is close to Australia by air, the Tasman sea is 1700km of open unforgiving ocean. This is not a distance you can reasonably cross as a people with little history of navigation, or even a lot of it. Scandinavia to Iceland is 2/3rds that distance and Iceland was only colonised in the 9th century, by a reasonably maritime culture (mid-era norse).
Indigenous Australians never reached New Caledonia either even though it’s much closer to Australia (~1200km), as far as I know the earliest arrivals were circa 1500~1000BCE at the earliest and from the other side (the Lapita reached New Caledonia from through).
who lived on islands and travelled between PNG and Queensland, Australia but didn't venture south past the Great Barrier Reef and to New ZEaland - but did have the boats and seafaring skills.
Sounds like largely coastal navigation, with some longer hops, a pretty different beast from the open water austronesian (/ Melanesian / Polynesian) navigation.
Mining is not needed to keep the grid reliable or smooth imbalances. You can achieve this by dispatching or cutting off the marginal generators needed to serve the load in real time (the marginal generators serving the load of these facilities are already quick response generators that don’t benefit from already being on and switching from mining facility to demand bursts elsewhere). They increase demand and necessarily move dispatch up the supply stack, increasing the marginal power price which sets the clearing price for all megawatts in the iso auctions and consequently the power prices for all customers. They also increase congestion by requiring more megawatts to flow increasing the congestion price component of the nodal LMPs (locational power prices).
Here is how prices are set in an iso auction. This is from iso New England. But works the same way in all isos including ERCOT.
It doesn’t matter to me if the mining operations are running or not, but they’re not helping the grid. Citing a crypto company on this is comically biased.
Dask added an actor model after seeing it in Ray. I’ve used dasks in some computationally intensive applications (already had existing dask infrastructure which is why we didn’t go with rays)
This is why you see a lot of 1 year and 1 day sentences. Any federal sentence 1 year or less must be served 100% in full. If it’s 1 year and 1 day it’s eligible for the time reduction credit and you can serve less than 1 year.
