Just in case this confuses the submitter, the actual title is "The Art of Computer Programming". And IIRC the code examples aren't in Pascal, but rather in "MIX" assembly, which is a hypothetical language for a hypothetical machine. Also, be forewarned that it has a steep learning curve...

Not sure if I'm missing the joke here (if so, apologies), but just because the book title is "Exceptional C++" doesn't mean the whole thing is about exceptions.

Exceptions are covered for a few chapters in that book, but some of the recommendations aren't really relevant anymore; C++11 deprecated many of the problematic parts of exceptions (e.g. exception specifications), and much like valarrays, no one really used them anyways

Well, C++ threads and the new memory model would take more than just a little more typing. Same for rvalue references.

Some operators shouldn't be overloaded (e.g. &, && and ||), but good luck writing any non-trivial container classes without overloading the assignment operator. You may think you're not overloading these, but the compiler is simply auto-generating them for you since you didn't provide one (namely, copy-assignment operator and move-assignment operators). As with any language feature it can be abused, but they can be quite useful when used judiciously. (i.e. if you're writing a Matrix library, you'll probably want to overload the arithmetic operators).

It's true that there are pitfalls to using templates, but I think you're grossly overstating their dangers (while ignoring all their benefits). You can do some pretty amazing things with templates; in the least they reduce code duplication, and at best they allow compile-time polymorphism, better error detection, and a whole different paradigm for using C++ (metaprogramming can pretty closely resemble functional programming).

In a word, C++ has the best binding support for GPGPU.

Both CUDA and OpenCL started off as C-based API -- CUDA has since moved to C++, and is moving towards more modern, idiomatic C++, both for its host-side API and device-side code (e.g. has support for kernel templates). OpenCL is a bit behind in this respect, although it also has both C and C++ bindings. You can also use fortran, but the majority of use-cases for GPGPU work is C++, and will be for the foreseeable future.

OpenCL and CUDA both do have other bindings (off the top of my head, .NET, java and python), but these are 2nd class support-wise.

Spoken like someone who doesn't know what they're talking about.

No benefits to software quality? Point out any new feature in C++11 that was added that didn't have a reason. (I would be very interested in fact, as I can't think of any off-hand); the newly added features are done with specific problems in mind. They might not be the problems that YOU encounter, but someone else has.

I use C++ almost daily -- if you're doing any CUDA (or OpenCL) work, then you'll want to be using C++.

If template error messages bother you, use Clang. It outputs much saner template error messages.

The "complex" rules for templates are laid out in painstaking detail in the standard. There can be surprising interactions with other language features(e.g. explicit template function specialization), but (based on personal experience), after having encountered them once or twice, you learn about them and avoid them in the future. On the other hand, having what would otherwise be runtime errors reported at compile time saves time on debugging, and generates more robust code.

Those with odd-numbered plates lucked out; apparently they've already discontinued the practice, after having issued roughly 4000 tickets.

One especially pertinent quote from the linked article: ""I know it's not great to say it but I'm willing to take my car and pay the fine to get my kids to school, because I don't have the choice," one woman told the TV network."

There have also been accounts of (wild) elephants helping humans

And what about the nepotism in the peer review process? Was that somehow by accident as well?