I'm not an expert on rebuilding massively exploded launch infrastructure; but I have a suspicion that a 2026-2029 plan is now going to involve less Blue Origin than previously believed.

A software engineer says, "Yes, I've developed techniques for avoiding entire classes of bugs in C, but there are a few types I'm still struggling with."

Someone who has not yet developed the engineering mindset immediately comes up with excuses. "We can't do that."

An engineer looks for solutions, not excuses. It's easy to tell the difference once you recognize it.

Black Rock has been building data centers as an investment vehicle. It's not clear whether they are all being used or not.

That is to say, they are definitely not all being used. Whether or not a meaningful percentage of them are being left unused is still an open question.

I hope I never work with you.

Ok, time for some programming advice you should have learned right after college.

Every time you write a bug, ask yourself, "How do I avoid this bug in the future? What can I change?"

Start doing it, and your code will quickly improve.

You clearly didn't read my comment.

Apparently it's also called perfect randomness.

The numbers are just symbols. You can use anything, even A,B,C,D,E,F

It's really hard to take you seriously when both of your definitions are circular. Get a better dictionary.

I skimmed a few of the referenced papers back to something in 1986.

It turns out that the practical implementation of a theoretical perfect (quantum) random bit generator (the example given in one paper was a zener diode[1]) always has some skew. This might vary over time but, for example, a random bit stream that is biased to more ones than zeros over the last 10s is more likely than not suffering from some temporary bias that an attacker can at least theoretically use.

Using classical physics it's possible to remove this bias so that you have a pseudo-random stream that is, for all practical purposes perfect however it's (apparently[2]) provable that doing this in the classical domain is theoretically open to attack due to the original bias.

What this has done is allowed a quantum process to do that post filtering so that even the theoretical attack on the pseudo-random stream driven from an almost perfect RNG is gone.

[1] example here - different paper:
https://www.researchgate.net/f...

[2] I took it on trust - one paper said it was proved in another referenced paper, I didn't try to check if it really did say that and I certainly didn't even try to follow a proof...

They claim each outcome has precisely the same probability. For contrast, a die has small imperfections making some outcomes more likely than the others, or a coin is not perfectly weighted making very small imbalances in the probability.

I don't understand how they did it, but that is what they are claiming.

Even in a truly random sequence, you could flip a coin 50 times and land on heads each time. You can also calculate the probability of that happening.

In a truly random sequence, every number has the same probability of being next.

In a less random sequence, some numbers are more likely than others. For example, in a binary sequence the next number could have a 10% chance of being 1, and 90% chance of being 0.

In a random sequence, there is a higher probability of getting a 1, and a lower probability of getting a zero. But that is only in comparison with a non-random sequence. Compared to the other numbers in the random sequence, each has the same probability of being next.

A lot of people consider Buddhism as a training method or philosophy, because it Buddha is not considered a god.

Even anciently, some Buddhists believed in the supernatural and others didn't.

If there were a zero (plus 1-6), then you'd need to use base 7. The base is the number of digits.

I don't know.