I am not into cars and I will certainly not pay for a luxury car anytime soon, so not the most relevant opinion. Still, when I buy a car again, I'd love to have this interior design. The exterior on the other hand, I don't know what they tried to achieve here.

Designers seem to struggle with exterior electronic car design in general. Are they trying too hard to be iconic?

Then, I met software and computer science abstractions, they all seemed so arbitrary to me, I often didn't even understand what the recipe was supposed to cook. And though I have gotten better over time (and can now write good solutions in certain domains), to this day I did not develop a "physics" level understanding of software or computer science.

It feels really strange and messes with your sense of intelligence. Wondering if anyone here has a similar experience and was able to resolve it.

I will never, ever go back to the time before.

The goal of social market economy is to 'correct undesirable effects' of free markets. Depending on your perspective, you categorize it as capitalist, socialist or in-between system.

And yet I agree with you. Economically, he disappointed through and through. Same for climate change, which ironically is at the heart of the Green party he belongs to. For example, to more conservative voters, he's will mostly remembered as the politician who wanted to bring a central planning approach into their homes, forcing everyone to install costly heat pumps, with their own money, without much regard to their specific household situation. All to achieve no effective carbon emission reduction.

But to his left-green electorate, he remains sacrosanct, his critics are dismissed, often as far-right.

You might have attended a good degree, where the learned information was actually beneficial. But I'd bet for most degrees out there, rote memorization is the consequence of professors wanting easily gradable exams, existing for their benefit, not the students.

Which means the actual problem is low quality education and degrees and we might find common ground here.

Me and most of my peers in college had the choice between two courses. Course A was interesting, yet vastly more challenging and therefore time consuming, with the additional downside of lower grade expectation. Course B was boring, a gentle breeze in comparison, yet with an almost guaranteed perfect grade.

Imagine which course most students choose?

Even if a student wants to take on the more interesting course, incentives matter, and the incentive is: better grades qualify for better compensated positions and prestigious degrees. Only students who didn't care about this or were confident enough in their ability did choose Course A. In the end, barely a handful of students out of hundreds went with A.

I have a running bet with friend that humans encode deterministic operations in neural networks, too, while he thinks there has to be another process at play. But there might be something extra helping our neural networks learn the strong weights required for it. Or the answer is again: "more data".