ghkbrew

For columnar data storage I think. The description references Parquet and they appear to benchmark against Parquet, Vortex, and Lance.

Sounds like they're saying that since the distribution doesn't come from measuring or calculating the probability of something, it has the form of a probability distribution but isn't really one. Like saying 5 feet is a height that a person can have, but since I just made up that number it's not actually a person's height.

[Citation Needed]

Only if you're made of pure water at standard pressure. Which I'm not.

This title is clickbait.

From the abstract: "The Index captures technical exposure, where AI can perform occupational tasks, not displacement outcomes or adoption timelines." (emphasis mine)

The 11.7% figures is the modeled reduction in "wage value", which appears to be marketplace value of (human) work.

I think they prefer "Jovians".

Well no actually it'd still clear to me that they mean the the multiplication of 3 different variables X, N, and D.

I don't think of it as eliding obvious operators. Rather in mathematics juxtaposition is used as an operator to represent multiplication. You would never elide an addition operator.

So X next to D still means multiplication as long as you can tell that X and D are separate entities.

I would wonder why they switched conventions in the middle of an expression though.

I assume they use N⋅D rather than ND to make it explicit these are 2 different variables. That's not necessary for 6N because variable names don't start with a number by convention.

Mosh looks very cool, though I've never used it. Does Screen provide some advantage over tmux in this setup?

My calculations says that moving 1cm up or down earths gravity well (at the surface) changes the acceleration of gravity about 5x more than the acceleration you'd feel from a 100kg mass 1m away.

Assuming my math is correct, it's already affected by nearby human scale masses, for certain values of "near".

From tfa:

Often, randomness is thought of as something you want to keep hidden, such as when generating passwords or cryptographic keys. However, there are many applications where an independent and public source of randomness is useful. For example, randomizing public audits, selecting candidates for jury duty, or fairly assigning resources through a lottery.

The chance that a positive result is a false positive depends on the false positive rate of your test and on total population statistics.

E.g. imagine your test has a 5% false positive rate for a disease only 1 in 1 million people has. If you test 1 million people you expect 50,000 false positive and 1 true positive. So the chance that one of those positive results is a false positive is 50,000/50,001, not 5/100.

Using a p-value threshold of 0.05 similar to saying: I'm going to use a test that will call a false result positive 5% of the time.

The author said: chance that a positive result is a false positive == the false positive rate.

Here I am running just fine on a 3 year old phone