I wonder how he found out. I’m guessing the person who leaked it on 4Chan is probably a political staffer, or something. Initially I thought it was a prison guard or a paramedic. But, I’d have expected them to leak it sooner. Say you’re a 4Chan user and you’re a prison guard. Would you really discover his body, call an ambulance… and then wait over an hour and a half before posting on 4Chan?

At 8:16 a.m. on August 10, 2019, an anonymous 4Chan user posted…

It beat ABC News journalist Aaron Katersky’s post about Epstein’s death on Twitter, now known as X, by 38 minutes

Is that in any way surprising? Someone with insider knowledge posted about it before a journalist was informed?

In the Wikipedia article about his death they said that he was rushed to the hospital and pronounced dead at 6:39 AM. More than 90 minutes before even this post on 4Chan, he’d already been taken out of his cell, rushed to an ambulance, driven across NY, taken to a hospital, rushed into the emergency room, and pronounced dead. There were so many opportunities for someone to notice that and post it somewhere.

In a sense, this means you pretty much clear the jail guards, ambulance drivers and emergency room doctors, nurses, orderlies, etc. of suspicion. Can you imagine that they saw a dead Epstein, but sat on that for 90 minutes before posting it to 4Chan?

What’s surprising here isn’t that it was posted first to some forum used by random Internet chuds. That’s what you’d expect. What’s surprising is that they were competent enough to keep the news quiet for nearly 2 hours.

On the other hand, we all know he did not commit suicide and got killed by the Pedoresident following the playbook of his BFF putin to try to save his fat orange pedo ass

No, we don’t. That’s a dumb conspiracy theory.

I’m pretty sure Google’s AI is fed by the same spider that goes out and finds every new or changed web page (or a variant of that).

As soon as someone writes an article about how AI gets something wrong and provides a solution, that solution is now in the AI’s training data.

OTOH, that means it’s probably also ingesting a lot of AI generated slop, which causes its own set of problems.

It’s not literally guessing, because guessing implies it understands there’s a question and is trying to answer that question. It’s not even doing that. It’s just generating words that you could expect to find nearby.

3 in 10 people get this wrong‽‽

Maybe they’re picturing filling up a bucket and bringing it back to the car? Or dropping off keys to the car at the car wash?

It’s also the case that people are mostly consistent.

Take a question like “how long would it take to drive from here to [nearby city]”. You’d expect that someone’s answer to that question would be pretty consistent day-to-day. If you asked someone else, you might get a different answer, but you’d also expect that answer to be pretty consistent. If you asked someone that same question a week later and got a very different answer, you’d strongly suspect that they were making the answer up on the spot but pretending to know so they didn’t look stupid or something.

Part of what bothers me about LLMs is that they give that same sense of bullshitting answers while trying to cover that they don’t know. You know that if you ask the question again, or phrase it slightly differently, you might get a completely different answer.

The video of the thing that didn’t happen?

You seem to recall wrongly.

So, hardware that was still on the road.

Hardware that was still on the road, or something that had been recalled?

Now you have phantom braking.

Phantom braking is better than Wyle E. Coyoteing a wall.

and this time with no obvious cause.

Again, better than not braking because another sensor says there’s nothing ahead. I would hope that flaky sensors is something that would cause the vehicle to show a “needs service” light or something. But, even without that, if your car is doing phantom braking, I’d hope you’d take it in.

But, consider your scenario without radar and with only a camera sensor. The vision system “can see the road is clear”, and there’s no radar sensor to tell it otherwise. Turns out the vision system is buggy, or the lens is broken, or the camera got knocked out of alignment, or whatever. Now it’s claiming the road ahead is clear when in fact there’s a train currently in the train crossing directly ahead. Boom, now you hit the train. I’d much prefer phantom breaking and having multiple sensors each trying to detect dangers ahead.

Well, Waymo’s really at 0 deaths per 127 million miles.

The 2 deaths are deaths that happened were near Waymo cars in a collision involving the Waymo car. Not only did the Waymo not cause the accidents, they weren’t even involved in the fatal part of either event. In one case a motorcyclist was hit by another car, and in the other one a Tesla crashed into a second car after it had hit the Waymo (and a bunch of other cars).

The IIHS number takes the total number of deaths in a year, and divides it by the total distance driven in that year. It includes all vehicles, and all deaths. If you wanted the denominator to be “total distance driven by brand X in the year”, you wouldn’t keep the numerator as “all deaths” because that wouldn’t make sense, and “all deaths that happened in a collision where brand X was involved as part of the collision” would be of limited usefulness. If you’re after the safety of the passenger compartment you’d want “all deaths for occupants / drivers of a brand X vehicle” and if you were after the safety of the car to all road users you’d want something like “all deaths where the driver of a brand X vehicle was determined to be at fault”.

The IIHS does have statistics for driver death rates by make and model, but they use “per million registered vehicle years”, so you can’t directly compare with Waymo:

https://www.iihs.org/ratings/driver-death-rates-by-make-and-model

Also, in Waymo it would never be the driver who died, it would be other vehicle occupants, so I don’t know if that data is tracked for other vehicle models.

Not just lower, a tiny fraction of the human rate of accidents:

https://waymo.com/safety/impact/

Also, AFAIK this includes cases when the Waymo car isn’t even slightly at fault. Like, there have been 2 deaths involving a Waymo car. In one case a motorcyclist hit the car from behind, flipped over it, then was hit by another car and killed. In the other case, ironically, the real car at fault was a Tesla being driven by a human who claims he experienced “sudden unintended acceleration”. It was driving at 98 miles per hour in downtown SF and hit a bunch of stopped cars at a red light, then spun into oncoming traffic and killed a man and his dog who were in another car.

Whether or not self-driving cars are a good thing is up for debate. But, it must suck to work at Waymo and to be making safety a major focus, only to have Tesla ruin the market by making people associate self-driving cars with major safety issues.

Which one gets priority?

The one that says there’s a danger.