Just wait until every country’s base uses its own capital’s time. The time zones won’t even be in vague order around the moon like they generally are on earth but distributed randomly based on whatever country has the biggest base in the area.

Worse, if different countries bases and teams are using different home time zones than you don’t even have time zones. Two people from different countries in the same room could be different time zones, purely based on the country they work for.

If this fails and everyone with a space program can’t agree to just use the same standard, then time zones could get very, very bad in the future.

Unfortunately, the rediscovery of private money along with the hobbling of the financial regulation put into place after the gold standard brought us into the great depression means that the least scrupulous peopkr in finance have a lot of power to try and make fetch happen.

The recent resurgence in crypto is owed entirely to the coordinated lobbying to tie such assets more closely into legitimate financial institutions, making it easier to dupe the working class into putting some of their life savings into the MLM ‘s for dudes.

While this article does a pretty poor job at it, I do think it is important for a financial community to call out that much like how MLM’s use the veneer of legitimacy granted by the government not considering them pyramid schemes to convince people to pay up these people have successfully lobbied the government to get added to these legitimate financial platforms to draw in more exit liquidity after NFT’s fell apart as a way to do that.

OpenAI’s algorithm like all LLM’s is designed to give you the next most likely word in a sentence based on what most frequently came next in its training data. Their main strategy has actually been to use a older and simpler transformer algorithm, and to just vastly increase the scrapped text content and recently bias with each new release.

I would argue that any system that works by stringing sudorandom words together based on how often they appear in its input sources is not going to be able to do anything but generate bullshit, albeit bullshit that may happen to be correct by pure accident when it’s near directly quoting said input sources.

Lower resolution and they operate in different bands of light. Nancy’s main thing is that it has about equal detail to Hubble, but a lot wider field of view. The main mission is to map a lot more of the night sky at decent resolution rather than to get better images of things we’ve already seen.

About 22 percent of the US government’s national dept is money one department of the government owes another part.

Offhand, the majority of the government dept is in government lines and bonds. While the government can buy back its own bonds, people tend not to sell said bonds for less than their worth and so you would need more money than what it takes to just pay off the bond. Moreover, said bonds are generally low interest, and so often get smaller with inflation.

In addition, most banks, mutual funds, hedge funds, large corporations, etc… tend to have rules that say that there is only so much financial risk they can be exposed to, so if they want to make a high risk high reward bet, they need to have a certain amount of low risk of investments aswell. Government bonds are seen as about the lowest risk investments possible, and so can often be more valuable than just the money the bond itself is actually for when used as the bedrock upon which the modern risk based US financial system is built on.

Given that bonds have an limited lifespan, it’s almost always cheaper for the government to let it time out then to buy it back.

Similarly, a not insignificant part of it is in pentions. Basically when you work for the government your paycheck says you get X part of your pay now, and Y when you retire. The idea is that no matter how bad you are at managing money or if you get a bunch of medical dept or such, you have a guaranteed retirement fund. Meanwhile, from the governments perspective, thanks to inflation Y is going to be worth a lot less real money when you take it out then if they gave it to you now. Y is dept, and since the government employs a lot of people, Y is actually quite a lot of dept.

It’s worth noting that a solid link between money printing and inflation has to my knowledge never been demonstrated outside of hyperinflation scenarios. The chief problem being that there are far to many inputs to inflation and deflation to solidly say how much influence some of the smaller ones like total money supply have.

I know, given the relevant track records and experience of the two companies, one would think that it would be ULA buying out their first stage engine manufacturer, not getting bought out.

Yep, it looks like a good orbital insertion too. About a 30min coast until translunar injection.

It’s unfortunately not certain that they will take such measures with their patients even though most try, and indeed ethic discrepancies are one of the things likely to be made worse with machine learning given that there is often little thought or training data given to them, but age of the hospitals machine is not a good proxy for risk factors. It might be statistically corralled, the actual patients risk isn’t. Less at risk people may go to a cheaper hospital, and more at risk people might live in a city which also has a very up to date hospital.

I believe it was from a study on detecting Tuberculosis, but unfortunately google isn’t been very helpful for me.

The problem with that would be that people in poorer areas are more at risk from TB is not a new discovery, and a model which is intended and billed as detecting TB from a scan should ideally not be using a factor like hospital is old and poor to determine if a scan has diseased tissue, given that intrinsically means your model is more likely to miss it in patients at better hospitals while over-diagnosing it in poorer ones, and that of course at risk people can still go to newer hospitals.

A Doctor will take risk factors into consideration, but would also know that just because their hospital got a new machine doesn’t mean that their patients are now less likely to have a potentially fatal disease. This results in worse diagnosis, even if it technically scores better with the training set.

While i haven’t been paying much attention to it, from my understanding the reported ghost towns were places where there was only half or so of completed residential units occupied, and which some less than scrupulous reporters then exaggerated to being near entirely empty.

Didn’t it turn out that the CT scan analysis thing was just the model figuring out the rough age of machine, becuse older machines tend to be in poorer places with more cancer and are more likely to only be used on serious illnesses?

Offhand, I find it kind of funny that low housing costs and low inflation are bad things when they happen in China, but high housing costs and high inflation are the fall of western civilization when they happen here.