People who think Trump is the stupidest possible don't know about Ron DeSantis.

Middle-range drones are in use because anti-aircraft measures have gotten so good.

No. The lack of anti-aircraft measures is why middle-range drones are being used so extensively. Ukraine put a lot time and effort into degrading Russian AA, whether radar systems, S-300/400/500, Pantsir, or anything else. The last number I saw was about 1,700 AA of all types damaged or destroyed.

Once AA is reduced, this opens corridors for drones/missiles, which is exactly what Ukraine is doing. Crimea is now essentially an island, with supplies rapidly dwindling and people fleeing while they can. Moscow has three rings of AA to try (and faling) to protect itself. Meanwhile, oil refineries the length and breadth of Russia are going up in flames each week.

Ukraine does have Baba Yaga drones (heavy drones which can carry multiple, large mortars/bombs), and those are being used to take out fortified positions.

Single-use drones are stil highly in use, which is what a middle-range drone is.

It is figuratively a blank check, which is the opposite of "literally".

Many times. The late 1940s. After the Vietnam War. The "Peace Dividend" after the USSR's collapse, etc.

Woah... Dumb question, but would a wing spar be repairable or replaceable?

Just slap on some Cylon organic resin. Eventually it will infuse itself into the spar and act like cartilage.

You can get mid sized SUV for that price now if you get used, there's VW, Chevy, and Toyota's SUVs around that.

No problem here. Nothing about cookies or anything else. The problem must be on your end.

Ah well that would just be a "partial blind" study, then! :) Surely we also need a reason to involve a placebo.

You don't need a double blind study to establish causality, a double blind study is done to mitigate bias. This sort of basic scientific error has become very common in anti-intellectual circles, you have to be careful who you're picking up habits from. A correlative study is exactly what you'd expect to use when comparing different parameters such as these, you can generally set up the data set with slicers to compare stuff like the A pillar size, or blind spot monitors as you point out. Tellingly raising the front hood line, that they're pointing out here, doesn't really have any positive impacts (pun) correlated for anyone?

Almost got plowed into by one of these oversized trucks a few days ago. I was walking in the driving lane between rows and a guy in one of these oversized pickups drove through the parking spots into the lane. He stopped only a few feet from me, then admitted he didn't see me.

Aside from the oversized truck, this is why you don't drive through parking spots.

Why not? If they can get a better deal using one provider or source than another, why not take it? Or do you want them to just spend their money like a drunk sailor like most Americans do?

They accidentally discovered new species in this research it isn't unlikely that it is a novel fungal toxin.

Chemical feedstock would be a good use for it, but we don't really need to come up with industrial use cases for every kind of rock and sludge in the ground.

I don't know how they manage to mux all that I/O. It must be several hundred phones (maybe thousands) all connected to one computer.

The one you saw is probably the fake one. However, Chinese phone farms do exist and they advertise in the open.

Please, find me an example of this fantasy.

Here you go.

For a slightly less gruesome story, this guy misrepresened himself for years, lying about his credentials.

Most likely the next step change in AI improvement will come from the next generation learning from today's LLMs and diffusion models. But not being trained on their output. More likely they will be evaluated by current AI.

AI advancements have a predictable pattern. First we mimic how humans do something, then we use those AIs to evaluate the next generation which learns how to do it without mimicking humans. LLMs have been trained on human output and work by trying to determine what a human would do in any situation. The next generation will most likely learn how to think and speak without ever seeing a word of human generated text. Now that LLMs exist to evaluate their output we have the necessary building blocks to design the generation of AI that can really produce content far better than any human.

We are living in the era of early-to-mid 90s chess engines, where AI learned from human moves and brute forced its way to barely beating the best in the world. It took 10 years from the point where chess engines could compete with top humans players until chess engines were effectively unbeatable. And those unbeatable engines were trained by other AI, not by looking at human games. It got to the point where looking at how humans played would have just made it worse.