The Armv8/9-A architecture reference manual is clear that speculative instruction fetches are permitted in Device memory unless that memory is also marked NX. So if your hardware has side-effects from a certain address, but it maps it as Device non-NX memory, then your code is not "perfectly good and correct". Assigning correct memory attributes is one of the many things needed for correct code.

It's crazy that Armv8/9-A permits speculative instruction fetches to device memory. Crazy enough that I had to look it up to believe it:

"Hardware does not prevent speculative instruction fetches from a memory location with any of the Device memory attributes unless the memory location is also marked as execute-never for all Exception levels." - ARM DDI 0487K.a § B2.15.2

The Armv7-M spec is less clear. It does say: "The architecture does not permit speculative accesses to memory marked as Device," in contrast to Armv8/9-A which qualifies a similar statement with "data accesses". But then it later says "To ensure correctness, read-sensitive locations must be marked as non-executable". (This is all from ARM DDI 0403E.e § A3.5.7)

I don't have v7-A older handy to compare what they say.

I’m talking about turbo props because the article’s hybrid technology is specifically for turbo props.

My challenge stands: find me a turbo prop that would be happy at idle thrust for either approach or cruise descent.

My assertion is that there are no turboprop plans that can maintain a 3° glideslope at normal approach speed without thrust from the engines. If you think there is such a plane, name the type, and show me a citation from it's POH to support the claim.

On an airplane, most of the energy in cruise is spent overcoming parasitic drag, not induced drag. It’s spent pushing the airmass out of the way as it moves forward, not creating lift to stay aloft.

For that reason, a change in weight does not significantly change cruise fuel usage.

Weight is still precious, but that’s because airplanes’ load are more often weight constrained than volume constrained, and capital and operating costs are such that you want to maximize the load.

If I had a need to spend $2k, I could do so easily, but I still think it’s a lot of money to burn. I wouldn’t spend it on a whim; I would not spend it without carefully, considering the value of what I get.

I would not even spend that much money in the businesses that I own, or recommended that my well capitalized employer spend that much money without being reasonably confident that the business would get good value for its money.

* Toll enforcement (the only thing allowed by the law)

* Speeding enforcement

* Parking enforcement

* Real-time alerting for vehicles that could be pulled over if you knew nothing other than the vehicle's identity. Stolen, unregistered, uninsured, amber-alert, etc. [1]

I think the following are all unreasonable, and I think most people would agree with me:

* Selling the data for any commercial purposes (perhaps with the exception of aggregated statistical data)

* Mining the data "suspicious patterns of activity".

I think the following is reasonable, but some people may disagree:

* Retaining the data for a limited time, so that if a crime is reported involving a specific vehicle, you can look back for sightings of the vehicle contemporaneous with the crime to help catch the bad guys.

Given my thoughts on what is and is not reasonable, I think the ideal policy is one that focuses on limiting retention, limiting sharing, and limiting the types of queries that can be performed on the data. Something like:

* Can retain the data for 90 days. Data that is evidence of a specific crime can be kept longer with the evidence file for that crime, and destroyed when the investigation is done.

* Can use the data where knowing a series of (time, place) pairs for a vehicle is probable cause of an infraction (or toll due). This covers speeding and parking and tools and red lights and registration/etc, but doesn't allow looking for suspicious patterns of activity.

* Can query the data for sightings of a specific vehicle with reasonable suspicion that the vehicle was involved in a crime. Need to keep records of these queries to identify abuse. Maybe need to notify owner when such a query is made.

* Can not disclose the data to third parties, except in the case when they agree to follow all these same rules (so you can share with other departments or law enforcement service providers, but that doesn't enable an end-run around the rules)

[1]: And I think it's important here that if data about a vehicle be eligible to be pulled over knowing nothing but it's license plate is out of date or otherwise wrong, then someone gets in serious trouble. Otherwise nobody is incentivized to keep their database up to date.

1. Close to 20 years ago I read about someone who converted a car to an EV with an old electric forklift motor, but then couldn't register the car. It was a model year that still required smog checks, but it couldn't pass a smog check because the original emissions equipment wasn't installed anymore.

2. My brother inherited our dad's 1992 pickup, and tries to keep it in running order mostly out of nostalgia. He would like to replace the engine with a newer model that would burn less fuel, produce more power, and correctly installed, no doubt would have lower emissions. But then it wouldn't pass the smog check, because it wouldn't still have the original emissions equipment.

Having said all that, I agree that it disproportionately impacts the poor, because the poor tend to drive older cars that are more likely to need repairs to pass an inspection, and because the inspection fees make a larger impact on the budget of the poor, and because the employment flexibility to be without their car for half a day for the inspection, or longer if repairs are needed, is not as common among the poor. You could subsidize the inspections for low value cars, which would help with the cost aspect, but I don't know a way to solve the other aspects beyond trying to find the minimum amount of inspection that meets the policy goals.

There's a niche available for a language which is relatively easy for a human to read, but with a very powerful at the expense of difficult to use type system. The language would let you make all sorts of assertions whose meaning are easy for the human to see, but to compile would need to come along with correctness proofs. The language is meant to be written by AI, which can battle the compiler, and write the proofs, but then read by humans who can verify that the AI wrote the program they wanted and/or direct the AI to make changes.

It occurs to me that the existence of paparazzi seems to be evidence against your position.

The fundamental problem is that among the 350 million people living in the United States, there are a lot of pairs of people who look pretty darn similar. It used to be impractical to ask a question like "who in the US looks like the person in this security footage", and so as a matter of practicality, once you found someone who looks like the suspect, you probably also have other evidence, even if it's pretty weak, linking them to the crime.

But with AI, you can ask "who in the US looks like this person", and so we need to re-calibrate what it means if all you know is that someone looks like a suspect. I am of the opinion that "looks like someone," in the absence of any other evidence, is reasonable suspicion, but not probable cause, that you are the person you look like. Reasonable suspicion is enough for the police to stop you on the street and ask for your ID, but not enough to arrest you. There are other data points that alone might not even be reasonable suspicion, but could be combined with "looks like someone" to make probable cause, such as "was near the place at the time the crime happened".

AI isn't really the problem, even whether or not the AI's determination that two people look alike is valid or reviewed by a human isn't the problem. The problem is assuming that because two people look alike they must be the same person, even if you have no other evidence of them being the same person.