204 karma · joined November 30, 2014
When I discovered NLP models like Word2Vec and Thought-Vectors, which assign vectors to words or even whole sentences/concepts, intuitively, it felt like that was exactly what was happening in my mind. It might be an illusion but I do not think in sentences or words, I only think in concepts and images that appear in my mind's eye in an instant. To form a larger idea, I build a chain of concepts. I am sure that eventually probes can pick up a clear distinct vector that uniquely summarizes the entire concept of what I was thinking or visualizing.
And as you suggested we could start off with a smaller subset of semaphores or concepts or visualizations that at first are the easiest signals to pick up via probes. After practice, these signals only get crisper.
Some syntax is close to Python so some mental load is minimized, i.e use of snake_case, self, None and type annotation syntax, dict unpacking.
Some lines read like sentences i.e. for loops, single line if statements, impl Foo for Bar etc. Some design choices also read better I think, for example, let reads better than var.
Of course such preferences are personal. I've read other comments that mention that the tutorial covers only basic Rust features and it can get much more complicated when using more advanced features.
Edit: Added sentence about advanced features.
However when you take a high level feature like overriding operators which can be done elegantly in Python, for a complied language, Rust's way is quite concise, readable and to my eyes quite pretty.
Edit: Typos
I'm curious what other what other developers who primarily use Python think of this article and Rust in general?