There seems to be a recent surge in the "HTML is/isn't a programming language" discussion.
While there are a lot of honest misconceptions and also outright bullshit, I still think if we allow for some nuance there is a meaningful discussion to have about it.
My two cents 👇
First, to be bluntly clear, if a person is using this argument to make a judgment of character, to imply that someone is lesser because of their knowledge (or lack of) about HTML or other skills of any nature, then that person is an asshole.
With that out the way...
Why is this discussion meaningful at all?
If you are newcomer to the dev world and you have some misconceptions about it, you can find yourself getting into compromises you're not yet ready for, or letting go options you could take.
One of the very interesting questions that really got me thinking yesterday (they all did to an important degree) was from @Jeande_d regarding how to balance between learning foundational/transferable skills vs focusing on specific tools.
@Jeande_d My reasoning was that one should try hard not to learn too much of a tool, because any tool will eventually disappear. But tools are crucial to be productive, so one should still learn enough to really take advantage of the unique features of that tool.
@Jeande_d One way I think you can try to hit that sweet spot is practice some sort of dropout regularization on your common tool set.
In every new project, substitute one of your usual tools for some convenient alternative. It will make you a bit less productive, to be sure...
A big problem with social and political sciences is that they *look* so intuitive and approachable that literally everyone has an opinion.
If I say "this is how quantum entanglement works" almost no one will dare to reply.
But if I say "this is how content moderation works"...
And the thing is, there is huge amount of actual, solid science on almost any socially relevant topic, and most of us are as uninformed in that as we are on any dark corner of particle physics.
We just believe we can have an opinion, because the topic seems less objective.
So we are paying a huge disrespect to social scientists, who have to deal every day with the false notion that what they have been researching for years is something that anyone, thinking for maybe five minutes, can weigh in. This is of course nonsense.
A day to share with you amazing things from every corner of Computer Science.
Today I want to talk about Generative Adversarial Networks 👇
🍬 But let's begin with some eye candy.
Take a look at this mind-blowing 2-minute video and, if you like it, then read on, I'll tell you a couple of things about it...
Generative Adversarial Networks (GAN) have taken by surprise the machine learning world with their uncanny ability to generate hyper-realistic examples of human faces, cars, landscapes, and a lot of other stuff, as you just saw.