Almost none of these tech leaders deserve their station except by virtue of luck or often borderline sociopathic tendencies. To flaunt it so egregiously is a bit over the top.

That’s just what I’ve seen at a personal level though.

A lot of them barely rise above the level of collected anecdote, nor explore long term or more elusive factors (such as cross-system entropy). They’re also targeting an area that is fairly difficult to measure and control for.

It reminded me of a mathematician in my field who had rather brilliant ideas, but whose papers were largely unreadable due to idiosyncratic symbology and style. Fortunately in that case one can still leverage an information dense symbology that points to a well-specified formalism.

Might as well call advertising “fun programming breaks” while we are at it.

When thinking about these things you have to factor in the prior probability that a driver is fully attentive, not just assume they are.

If you’ve ever been in a Waymo you quickly realize their field of view is pretty good. You often see the vehicle sensing small pets and children that are occluded to a passenger or driver. For this reason and my experience with humans near aforementioned school, I doubt a human would out perform the Waymo in this particular incident and it’s debatable they even have more context to inform their decisions.

All that said, despite having many hours in a Waymo, it’s not at all clear to me how they factor in sidewalk context. You get the sense that pedestrians movement vectors are accounted for near intersections, but I can’t say I’ve experienced something like a slow down when throngs of people are about.

This is obvious to any adult in the room. But the benefactors of said biases do not want to acknowledge it since it lays bare their utter mediocrity.

A string of not necessarily related words with nonsensical grammar is about as far from natural as you can get.

One of the worst systems I’ve ever had to deal with. Not necessarily because of the db itself, but because of the implications of its use. It serves an incredibly narrow purpose. Everywhere I’ve worked at has had a team practically dedicated to moving data from a document store to a relational db so it could be actually usefully used for analytics and across disparate systems.

Just think about the type of code these things are trained on and the fact you’re clearly some random non-specialist.

Look at the more technical descriptions using conditional probabilities of the Monty Hall problem as it is essentially equivalent. You’re trying to factor in the probability of whether Monty knows if a goat is behind a door when the observable information is that there is an open door with a goat. One you make that observation many things collapse.

Lettuce is one of the least appealing things I can imagine adding to a half decent burger. I’ve also never once cooked a burger I’d describe as “slimy”.

Obviously it’s all subjective at the end of the day.

Authoring plugins is a lot more attractive in lua, imho.