In Africa it is quite common to kill foreign aid workers in order to deny food aid to the enemy. Bureaucracy and rent-seeking has nothing to do with it, it's just child soldiers being brainwashed to kill their enemies at any price.

Only in a flat environment without too much atmospheric distortions. As soon as you get multipath effects from eg waves bouncing off buildings and mountains then the computational complexity goes through the roof. Also I don't think you should underestimate how much the signal degrades in a "target path" vs the "direct path". The article mentions -60 dB and I think that is fairly optimistic. The transmitter power needs to be HUGE to make it work, so it would be much easier to have stationary transmitters. Normal radars manage to do this because they are highly directional, but multistatic radars need to look in all directions at once and need to up the power as a result.

The survivability gains are also overhyped since 1. the enemy can just blow up the transmitters leaving you with a bunch of useless receivers and 2. most air defense doctrines already treat radars as something that should be distributed widely, so you can lose a few without the whole system collapsing.

The article goes into this only briefly, but modern radar systems don't just send out any random pulse but they very specifically tailor the waveform going out in order to do cool signal processing tricks like pulse compression. There is also the matter of frequency. The lower the frequency, the bigger the antenna you would need to get a proper direction reading out of it. Fire control radars typically operate in the X-band, around 10 GHz. Most civilian radio transmitters are around 100 MHz, so you'd need impractically large antennas and even then the bandwidth limitations would severely limit spatial resolution. One saving grace here is that stealth airplanes are typically most highly optimized against X-band radars from the direction they're going to bomb (forward), so you might have a better chance with a normal system, but then you still might not have a precise enough target to actually shoot at.

So while the multistatic system does offer some advantages, in practice it's just cheaper and (importantly for military use) requires less fiddly bits in the field to just use normal monostatic radars. Civilian use also doesn't benefit greatly from being multistatic. It's a bit like Tesla turbines or hyperloops: cool idea and it even "works" in a way, but the normal way of doing things is just way better when budgets and engineering realities come into play.

Source: I was a radar engineering officer in the Dutch navy about a decade back.

Isn't there? I would say that the key difference is that programming actually works, and works reliably. Even if it is opaque to normal people, at least the programmer themselves has a reasonable ability to understand why their program will work and critically can "call their shot": they can reliably predict the effect a certain program will have. Magic is not like that: even if the practitioner claims to understand how it works, their success rate is typically abysmal. AFAIK there are zero faith healers or other magic types whose claims consistently hold up when inspected, but programmers and other engineering types do it all the time. That's the objective difference right there, even if normal people struggle to discern the two.

I guess the difference between magic and science to me is that "not everyone can learn magic", but the core bit that makes science work is that in principle everyone can learn it. In practice of course we cannot know everything and so have to rely on the expertise of others, but that is a limitation in the humans and not in the knowledge. Meanwhile for "magic" you have to be chosen by the gods/genetically gifted/cursed/whatever.

In a universe where magic is just another skill that anyone can learn, that reasoning goes right out the window of course.

Programming is technology but not "occult" technology, and I don't really see the added value of treating it as occult. Quite the opposite actually, most good programmers I know acquired their skill because they have a decent grasp about the entire system rather than treating most of it as a black box.

And Sytse if you read this: beterschap en als dat niet helpt: sterkte. Cancer sucks.

I think the core problem is not so much that it is not "allowed", but that even the most basic types of automation involves programming. I mean "programming" here in the abstract sense of "methodically breaking up a problem into smaller steps and control flows". Many people are not interested in learning to automate things, or are only interested until they learn that it will involve having to learn new things.

There is no secret conspiracy stopping people from learning to automate things, rather I think it's quite the opposite: many forces in society are trying to push people to automate more and more, but most are simply not interested in learning to do so. See for example the bazillion different "learn to code" programs.

Yes. The research shows that they do (almost) always converge, but that they DON'T always converge to an accurate value. In particular, there can be behavioral biases at work that warp the perception of bettors in one direction or the other. A well documented case of this is when fans of a sports team pile in and bet for their favorite team, causing the price to shift too much towards the more popular team. Exposure to the predictions by other bettors then causes the total market to converge to the biased price. Interestingly enough, people still do this even though this phenomenon is well documented and they have to put their money on the line. People just don't care enough about their $10 bet to do thorough research.

In a similar way, I would not at all be surprised if some people are such fanboys of OpenAI that they start to display cultlike behavior. You can easily find such people online even on this very site. It's not such a weird thing to consider that people at the peak of a hype cycle don't always behave in rational ways, especially when they're just betting $10 when drunk on a Saturday evening.

The good news is that the grid operators have a good idea of what the problem was/is and it's well understood how to fix it. The downside is that it will require quite a bit of both time and money to reinforce the grid infrastructure.

- Most significantly, most scientific research focuses on things that are actually amenable to guesses with a normal distribution, like "amount of jellybeans in a jar" or "length of the border between country A and country B". An IPO is a binary choice where it either goes public or not. There is no correct value to converge to.

- It has been shown that as bettors gain more information about the bets of others, predictions lose accuracy and bettors converge to a consensus value instead. It seems to me that online prediction markets would be extremely prone to this as the bets of other people are all there in the market price.

- Prediction markets generally become more accurate as the diversity of the bettor pool grows. The users of polymarket and Kalshi heavily skew towards young men from certain socioeconomic groups, who may be biased towards one or the other outcome.

In the case of an OpenAI IPO, it seems likely multiple of these would converge as people start to fall prey to groupthink because "everybody knows that they'll IPO soon" in their local media bubble.