The problem with "Defund the Police" is right there in the name, and its name only. It's understandable that those who lost hope on reforms felt the need to escalate into using the term "Defund."

But uninformed people that don't understand nuance nor care about policies and enforcement would likely judge that's extreme and leads to anarchy immediately, and dismiss its merits. And let's be honest, would you bet there're more informed people in the USA or uninformed ones? If there's ONE thing that USA does better than any other countries, it's politicizing the hell out of complex issues into sound bites. Pushing people into all-or-nothing For or Against camps. In the end, little gets done, but even more divisions & hate.

I watched on the news here in Canada (with its fair share of racial injustices in its policing not that far behind the USA, ) that the mayor of Toronto (our largest city in the country) picked up and used the term "Detask the Police"... I think that's a much better term to advance the cause.

Hahaha.. Cancels out. OK, yep. It's basic math here not a complex collision simulation...

Did you even read this bit,

"The partial rollover presents an additional injury risk beyond what the standard crash test criteria are intended to measure"

I'm only discounting some things it because it's irrelevant to the point which is you stating rolls or "flops" are better than an arbitrary situation that generally doesn't exist and certainly isn't the other option to a roll in this test.

You're massively oversimplifying things again. Where is your crumple zone math? Where is your math showing how much force is imparted into pushing the car in front forward based on whether it has it's brakes on, is still moving, etc, etc, etc.

Your personal experience is not extraordinary. I have been in accidents, I didn't bother to bring it up because it doesn't mean anything.

I'm not arguing that higher G forces don't correlate with more severe injuries, that's not the point . The point is that CSI injury is very complex, complexities that can cause severe injury with minor force in situations like.. a rollover.

from the report you mentioned,

"The partial rollover presents an additional injury risk beyond what the standard crash test criteria are intended to measure"

From the YT description:
Launch to orbit in real time Fuel Burn and Staging of the
1) Saturn V
2) Space Shuttle
3) Falcon Heavy
4) Space Launch System (SLS)
Launching from Kennedy Space Center Launch Complex 39

Red = Kerosene RP-1
Orange = Liquid Hydrogen LH2
Blue = Liquid Oxygen LOX

Anyone think that hairdresser inserted her own neuroses there? That poor innocent girl saw her hair sticking up everywhere and in every direction and made a comment on it. Then she was emotionally bowled over (double meaning here), which quickly upset amd confused her. I think we so often insert our own complex adult values in to the simple lives of children and ruin things. I love watching truly gifted young child educators talk to children about deep things, it's so open and honest. Versus this.

Your video, Massive old fully stocked Russian bunker complex, has made it into the Top 15 New Videos listing. Congratulations on your achievement. For your contribution you have been awarded 1 Power Point.

Did I say HE is a MAGA moron?
No, I did not, you inferred it, although it would be a relatively safe assumption based on his ignorant racist interruption and self centered disrespect paired with the inane irrationality of his question and blatantly racist comments.
Now who's making slanderous assumptions?

Your messiah slanders without (it's one word, Bob, not two) knowing daily. A bit hypocritical to denounce that when you so often applaud it, don't you think?

And my what is no better than the guy?
Your: possessive- belonging to you- "Your assumption is based in ignorance."
You're: conjunction- You are- "You're in desperate need of a better education because your English would fail a 3rd grade English class."

I might just WHAT another douchebag? You forgot the verb. You get an F for the day, Bobski. Nigerian princes have better English skills, and terrible English is an intentional part of their scam. (Or were you channeling Yoda but forgot the punctuation? As in "Look in the mirror, you might. Just another douchebag looking back.")

You need to watch some more school house rock and learn English better, then you might understand complex statements better and not jump to mistaken conclusions so often. Might I suggest starting with conjunction junction?

Also, I wrote MAGA, not MEGA, aside from MEGA making zero sense, I wouldn't ever insult MegaMan by conflating him with idiots like this guy. Besides an education, you seem to need glasses. Maybe that's why you can't see any of Trump's infinite character flaws?
Sad.

Why? Gotta feed the military industrial complex! Republicans always look to start a war somewhere, the Democrats' always lack the will to stop them cold.

Not sure that I'd call it trivial, but from what one can gather, using the panel of known colors as a calibrant for correction during processing does seem like an obvious approach. I'm assuming that the newsworthiness of this is in the trick or complexity of the post-processing - removing scatter, haze, correcting the full color spectrum with multiple calibration points - it won't be a simple linear correction. I ain't no expert, but have spent oodles of time trying to color correct videos and stills from our scuba trips, and the *automatic* color correction in current software is still pretty poor IMO, relying often on a single color as the calibrant (so, a "pure" white region in the photo, a "pure" black region in the photo etc.). Manual adjustment of the photo color balance for UW vids and photos is on my list of "What Hell must be like".

...Maybe? It would absolutely annihilate at something like chess, or Go. I have a hard time imaging a good use case for having it actually run a video game, but I'm guessing few people working on early traditional computers could've envisioned any of the delightful diversions we now take as a given. Probably when I'm 80 kids will be playing quantum Minecraft in a layered omniverse of worlds, where removing a block in one world has consequences in nearby dimensions, with chaos theory realistically modeled and incorporated.

Some complex tasks a QC would absolutely rock at however. Feed it a long list of employees, hours of availability, and coverage requirements, and it should spit out a 100% optimum schedule immediately. Air traffic controllers (particularly at large hub airports) would likely find it helpful in coordinating flight plans. Logistics for manufacturing, shipping, etc. The downside is that encryption will likely be utterly fucked for a while, as a quantum computer with a sufficient number of qubits could try all possible options at once. So it'll be interesting, but we're still 10+ years from any sort of commercial products, and they'll be like the computers of the 60s: huge and expensive, big iron for custom purposes. Or at least that's my semi-informed guess, I ain't no technoprophet.

Someone who really wants to get involved in bleeding-edge tech would do well to dive into this field. Writing the algorithms needed to run a task on a QC requires a completely different mindset than programming a traditional computer. I don't think people with years of experience with current programming methodologies would adapt well. At best they'd be nearly starting from scratch, at worst they'd have to work to un-learn what they already know.

It'll be useful eventually, but I wouldn't bank on soon. My final project in college was related to quantum computing, which at the time (18 years ago) was effectively entirely theoretical. I've enjoyed seeing the steady, albeit slow, progress.

The areas where quantum computing will really shine are problems which involve a huge number of possible answers, but only one best or correct one. The traveling salesman problem is a classic of computer science, as you can scale it up in complexity to the point where any traditional computer will eventually choke on the sheer number of permutations to test. Great way to demonstrate the need for clever solutions and well-written algorithms vs brute force approaches. An adequately sophisticated quantum computer, however, will theoretically be able to solve the traveling salesman problem nearly instantly, regardless of the level of complexity / number of nodes to navigate. Because it just tests all possible answers simultaneously.

This other video from the same channel is for a project that took 1,000 hours to complete. Looks to be 2-5x more complex than the card press, but it's a bit hard to guess with 1,000 hours compressed into 12 minutes.

https://www.youtube.com/watch?v=dU7iKNmQBIs

This isn't really true though and greatly understates how amazing this demo, and current AI actually is.

Saying the agents are obeying a set of human defined rules / freedoms / constraints and objective functions would lead one to imagine something more like video game AI.

Typically video game AI works on a set of weighted decisions and actions, where the weights, decisions and actions are defined by the developer; a more complex variation of:

if my health is low, move towards the health pack,
otherwise, move towards the opponent

In this demo, no such rules exist. It's not given any weights (health), rules (if health is low), nor any instructions (move towards health pack). I guess you could apply neural networks to traditional game AI to determine the weights for decision making (which are typically hard coded by the developer); but that would be far less interesting than what's actually happening here.

Instead, the agent is given a set of inputs, a set of available outputs, and a goal.

4 Inputs:
- Position of the agent itself
- Position and type (other agent, box, ramp) of objects within a limited forward facing conical view
- Position (but not type) of objects within a small radius around the agent
- Reward: Whether they are doing a good job or not

Note the agent is given no information about each type of object, or what they mean, or how they behave. You may as well call them A, B, C rather than agent, box, ramp.

3 Outputs:
- Move
- Grab
- Lock

Again, the agent knows nothing about what these mean, only that they can enable and disable each at any time. A good analogy is someone giving you a game controller for a game you've never played. The controller has a stick and two buttons and you figure out what they do by using them. It'd be accurate to call the outputs: stick, A, B rather than move, grab, lock.

Goal:
- Do a good job.

The goal is simply for the reward input to be maximised. A good analogy is saying 'good girl' or giving a treat to a dog that you are training when they do the right thing. It's up to the dog to figure out what it is that they're doing that's good.

The reward is entirely separate from the agent, and agent behaviour can be completely changed just by changing when the reward is given. The demo is about hide and seek, where the agents are rewarded for not being seen / seeing their opponent (and not leaving the play area). The agents also succeeded at other games, where the only difference to the agent was when the reward was given.

It isn't really different from physically building the same play space, dropping some rats in it, and rewarding them with cheese when they are hidden from their opponents - except rats are unlikely to figure out how to maximise their reward in such a 'complex' game.

Given this description of how the AI actually works, the fact they came up with complex strategies like blocking doors, ramp surfing, taking the ramp to stop their opponents from ramp surfing, and just the general cooperation with other agents, without any code describing any of those things - is pretty amazing.

You can find out more about how the agents were trained, and other exercises they performed here:

https://openai.com/blog/emergent-tool-use/

Another entrant in the incredibly long line of adaptation / adaptive learning / intelligent systems / artificial intelligence demonstrations that aren't. The agents act based on a set of rules / freedoms/constraints prescribed by a human. The agents "learn" based on the objective functions defined by the human. With enough iterations (how many times did the narrator say "millions" in the video) . Sure, it is a good demonstration of how adaptive learning works, but the hype-fog is getting a big thick and sickening folks. This is a very complex optimization problem being solved with impressive and current technologies, but it is certainly not behavioural intelligence.