2,800 karma · joined March 14, 2015
My university level linear algebra class didn't touch practical applications at all, which was frustrating to me because I knew that it could be very useful to some background doing hobbyist game dev. I still wish I had a better understanding of the use cases for things like eigenvectors/values.
IIRC at the time I was testing with Sonnet 3.7, I haven't tried it on the newer models.
While you won't be able to share your back end models with the front end, OpenApi spec generation is pretty much automatic so you can generate the models or client code.
If you're using csharpier you don't need to use Roslynator formatters. No issue with the analyzers package. The csharpier docs have info on what StyleCop rules need to be adjusted so they can work together. Personally I don't use StyleCop anymore as it seems to be fairly dead, and I don't really feel the need for things like enforcing file layout or naming.
Edit: Also I will add that unless the landscape has changed recently, I believe csharpier is the only C# tool that has deterministic formatting good enough to enforce code formatting checks in CI.
Second, racking a slide is an action that requires fine motor control. Under the pressure and adrenaline dump that accompanies a life-or-death situation, fine motor control goes to crap. If you are fumbling with your pistol, it's useless.
Third, if you don't feel comfortable with your ability to safely handle a loaded gun, you probably shouldn't be carrying at all.
I played with Starship for an hour this morning - the joys of 50 person planning meetings - but ultimately uninstalled it. I did like some of its options like command timing and success/error, but all the tool versions ultimately just felt like noise. Not worth the effort to maintain a complex custom config to trim it down to what I'd want.
However this was a real problem during WW2, and high speed dives killed more than a few pilots. By 1942-43 most fighter planes were able to dive fast enough to get into trouble (500+ mph/800 kph) but weren't designed for it at all. The aerodynamics of supersonic flight just weren't understood at the time. In some cases the design of the plane made it essentially impossible to pull out once you went beyond a certain speed, all you could do was attempt to slow down enough to regain control. The P-38 Lightning was notorious for this. I don't have any specific sources handy but I recall reading accounts of things like pilots bracing their feet against the control panel trying to pull the control stick with all their strength, taking extreme measures like lowering the landing gear to slow down (risking it being ripped off and maybe tearing the whole plane apart), or only surviving due to sheer luck - sometimes the thicker air at lower altitudes would slow them down enough before it was too late.
What do you think happens when you try to use Python 3.9 to run a script that depends on features added in 3.10? This is inherent to anything that requires an interpreter or runtime. Most scripting tools just default "your stuff breaks if you get it wrong" whereas .Net requires you to explicitly define the dependency.
They can, of course, but this is how you end up with pre-release regression testing cycles that are weeks or even months long. A "large project" might easily have thousands of buttons (or more!), many of which are only seen when certain settings are enabled, certain options are chosen during a complex workflow, etc.
1. Instead of being expected to read N x-rays per hour/day/whatever, radiologists will soon be able expected review 3N or 4N AI diagnoses in the same time.
2. With far less time to spend on each case and an AI that is right most of the time (but imperfect) humans won't be great at catching AI mistakes, even if they're trying.
3. Pay and prestige for radiologists will drop, leading to a lack of quality people entering the field, exacerbating the problems in #2.
4. Eventually administrators and/or politicians will decide that (using made up numbers) very cheap AI-only review with 90% accuracy is "good enough", even though the more expensive AI+human combo can yield 93% accuracy or very expensive human-only review can yield 97% accuracy.