Heh, maybe that's because the nature of quality is qualitative rather than quantitative.
There are things that can be measured that might be correlated to quality ("bugs", sales, support, etc) but ultimately, classical quality seems to be to be a marriage of what was expected or desired with what was actually there. As a developer, my take is that quality usually stems from "developing" those expectations as much as making the relatively concrete thing to compare them too. When anyone can quantify the first half of this equation, please let me know at once.
I'm curious about the finances and the practical aspects of resuscitation. Do you stipulate when you want to be resuscitated and for how much money? Do some people volunteer to be early resuscitation subjects? Is there a discount for that?
1) Using object literals for values.
2) Using object literals with functions.
3) Using object literals with functions and calling them in contexts (`this`, `bind`, `apply`).
4) Using the `new` keyword.
5) Designing objects with inheritance hierarchies or prototype chains.
6) Designing mutable and stateful objects with indefinite life spans.
I don't understand the arguments that classical-ish inheritance in JS is bad while prototypical inheritance is somehow better. I've worked in codebases that liberally extend objects into different types of objects with long prototype chains, and IMHO they suffered from the same problems that people complain about in classical inheritance: tight coupling, premature/wrong abstractions, gradual violations of open/closed, etc.
Personally, I go through 1-4 liberally and 5 and 6 conservatively. IMHO, complaints about inheritance mechanisms seem to have something in common with the people who talk about the special needs of "large-scale applications". Why not just make smaller apps, or make smaller things that compose with less knowledge of where they are?
NB: It's entirely possible that I haven't run into the kind of complex requirements where liberal inheritance is a good fit. I'd be interested in hearing stories about when that worked out well.
> Why not just make smaller apps, or make smaller things that compose with less knowledge of where they are?
The easy answer to this is that successful apps have a tendency to grow larger than expected and splitting them up requires care and lots of work. Class based inheritance provides a familiar way to split up the state space via encapsulation. It provides some boundaries instead of none and theoretically allows you to separate out your concerns and not have to think about the system-wide implications when writing code in your class.
I'm in the functional camp and think classes aren't a great way to build software but I support the addition of `class` to ES6 since it shifts the ecosystem from a hundred slightly-incompatible versions to a single one. The mystery to me is why the people who advocate for JS classes are still writing JS rather than writing Typescript or Dart to further constrain their state space with a type system.
Alan Shepard freaking flew Mercury 3 by hand during a 11.6g reentry.
Ejections seats are 12-14g or worse.
Of course, max G is only part of the equation; duration is the other. You can handle really high forces if they aren't for long. Given the short duration and lack of need to keep the occupants awake they could go a lot harder. I'm actually a little surprised it's so gentle.
If my mental math comes out correct, that's 25 m/s in one second, so assuming straight against gravity, that's a bit over 3g for one second. Not too bad, considering how extreme of a situation is involved.
100MPH is about 45m/s, not 25. Fighting gravity, that's 55m/s^s acceleration, or 5.5g.
Still fairly mild, considering. The Soyuz launch escape system, for example, subjects its occupants to 14-17g for five seconds. Incidentally this is the only LES that's seen actual use, when it saved a crew from an exploding rocket in 1983.
Whilst it is true that there has only been one launch abort so far, if the Shuttle had a launch abort system it would have saved the seven astronauts aboard. Just mentioning this in case someone mistakes your post as arguing that launch abort systems are rarely useful.
Maybe somebody who knows about AI can answer this for me: what do we expect of an AGI machine to be able to do when it "turns on?" How will you know it works? To compare to a human, you might say that it can cry, suck milk, and learn to walk and talk over the span of a few years, and then slowly, with a lot of trial and error, learn to do more.