My understanding was that Waymo’s are autonomous and don’t have a remote driver?

https://en.wikipedia.org/wiki/Alice_Blunden

[1] https://www.youtube.com/watch?v=3nJrYPVJ88M

[2] https://www.youtube.com/watch?v=Z4l6eH-lmMA

I don't see how this is a good thing? I've been riding my bike since I was a little kid (in the Netherlands) and I've had zero people actively try to kill me, I'm not sure why any nonzero number is not a big deal.

Does it do that correctly though? I've always wondered why the formula is not w / h^3, since I imagine your weight should scale cubicly with your height.

Huh? That's not that low. In the Netherlands the highest bracket, 49.5%, kicks in at ~€68k EUR (~$78k USD).

So the standard argument against such a procedure is that if you generate N random bits, each of {0,1}^N bitstrings is equiprobable and therefore no mapping of {0,1}^N to {0..U-1} can map an equal number of bitstrings to each output.

A priori the method seems to work around this by conditionally sampling more bits, so that your domain is not one of fixed-length bitstrings. But then there is this paragraph:

> More intriguing still, this algorithm can be made unconditional by removing the early out, so that every value computed requires word size + 64 bits from the stream, which breaks the loop-carried dependency for fast generators, unlocking vectorization and parallelization where it was previously impossible. This is an especially powerful advantage when paired with bitstream generators that allow skip-ahead such as counter-based generators or PCG.

But now we are mapping {0, 1}^N into {0..U-1} right? So this mapping ought not be uniform? In fact I'm not sure why the early-termination method even works, because for a fixed U we know the maximum depth of the generated-bitstring-tree, so we can just pad it with imaginary random bits to arrive at the contradiction that U does not divide 2^N.

I imagine I missed something, what is it?

EDIT: thinking about it more, if you sample finitely many bits then each possible output has a probability that is a dyadic rational (fractions of the form a/2^k) which does not include all integer reciprocals.

> A typical hash function distributes keys randomly across the slots in a hash table, causing some slots to be empty, while others have collisions, which require some form of chaining of items

I.e. each field in the table is a linked list of values that hash to this position, and the new value is inserted in the shortest of the two lists it hashes to.

Also, how much of, say, our medical/biological knowledge actually only applies to the descendants of the bottleneck mentioned in the post? I understand the "very diverse" in the article have better things to do than be subjected to researchers, but reading the article I can't help but be curious what this genetic diversity means in practice?

*) not necessarily visually

Here's an interesting lecture on the topic: https://nisheethvishnoi.files.wordpress.com/2018/05/lecture4...