Damn. And here I have a Gemini Pro subscription sitting unused for a year now.

Last time I checked only political posts (like related to offshore programmers) got any kind of attention. Most technical posts barely gets 10 comments. Some of the smaller subreddits (like /r/ProgrammingLanguages) are much better.

https://www.dw.com/en/south-korea-uneasy-as-us-moves-air-def...

https://edition.cnn.com/2026/03/05/middleeast/radar-bases-us...

Of course those that believe that AI will convert into AGI and destroy society as we know it won't be convinced.

Wait, this is how people vibe code? I thought it was just giving instruction line by line and refining your program. People are really creating a dense, huge spec for their project first?

I have not seen any benefit of AI in programming yet, so maybe I should try it with specs and like a auto-complete as well.

So casual. Actual ad giants like Meta and Google are serving many more people than 190M while bringing in actual profit.

Yes, let's say these are just the early days and they are burning money just like any other VC company. But how are they going to scale up their hardware/usage and get a profit at the same time?

AI hardware is getting optimized YOY too but the flagship models are getting bigger every year as well. I don't see how they are going to get profit without jacking their prices at the same time. And price increases always hits usage growth.

Serving an ad is very cheap these days, while serving a big model is very much expensive.

Also, one thing that annoyed me when I used iPhones is that you can't remove an app's cache without reinstalling it and losing all your data. And most modern applications think cache is free so they use a lot of it. Many times it will exceed even your installed apps or data size.

SO was dying even before ChatGPT was released. LLMs just accelerated that process.

But why? If you do that you are just taking memory away from other processes. Is there any significant speed improvement over just dynamic allocation?

It is always the eternal tomorrow with AI.

Even if they ask about the syntax design people just dismiss their question with saying "syntax is not important". Python did the opposite, it focused on syntax over everything else. That caught on with beginners and now here we are.

Of course with AI Python got even more popular, but even before ChatGPT was released it was already dominant.

You can do the same thing in other languages but it won't be built in like that.

This was my biggest problem when I used to write Rust. The article has a small example but when you start working on large codebases these problems pop up more frequently.

Everyone says the Rust compiler will save you from bugs like this but as the article shows you can compile bugs into your codebase and when you finally get an unrelated error you have to debug all the bugs in your code. Even the ones that were working previously.

> Rust does not know more about the semantics of your program than you do

Also this. Some people absolutely refuse to believe it though.

Taking the current RIIR movement and casting it on Zig as the next hyped language is clever.

> ITER achieves net positive energy for 20 consecutive minutes

Hilarious. I guess not many people talk about the challenge of proper shielding material against fusion radiation. Otherwise we would get hallucinations about new exotic heavy metals too.

Also, I don't think their every service got affected. I am using their proxy and pages service and both are still up.