There's a lot of current research around using machine learning to optimize software. One paper I'm thinking of is: https://dl.acm.org/doi/10.1145/3533028.3533308 where they use ML to optimize latency and hardware usage of Apache Flink dataflow programs.
Zig is great. The editor tooling could use some more work but I think after their new stage2 compiler is more ready, it sounds like they’ll invest more into that.
Cherry MX browns are the second product for r/mechanicalkeyboards, but I can't say all the talk about them is positive. Most people meme on how bad they are. So in this case popularity in discussion doesn't really correlate to a product you should buy.
The purpose of a title is both to summarize content and grab the readers attention. It's up the author which one they put for emphasis on.
You clicked so it worked, even if you don't like it.
The user only saw the headline and closed, isn't the author aiming visitors to read the content or clicks?
The same analogy could be made to a baker luring customers in their bakery with an attractive facade but the very same "customers" just give a quick glimpse and leave.
In fairness, I did in fact read more or less the whole thing. I walked away with a fairly low opinion of the article and the author, but I did read it :)