Even if it happens at the edge, on every conversation turn, I may assume non captured small subtleties of meaning over time can accumulate into significant error.

It’s not! And I’ve never said that.

Anyways, I’m not even sure what we are arguing about, as it’s 100% fact that SOTA models perform better in English, the only interesting question here how much better, is it negligible or actually makes a difference in real world use-cases.

It just can’t be a case simply because how ML works. In short, the more diverse and high quality texts with reasoning reach examples were in the training set, the better model performs on a given language.

So unless Spanish subset had much more quality-dense examples, to make up for volume, there is no way the quality of reasoning in Spanish is on par with English.

I apologise for the rambling explanation, I sure someone with ML expertise here can it explain it better.

Not to defend Nodejs ecosystem - your points are 100% valid.

With that in mind, I think Go is much better option.

What I actually meant to say is “not staggered”.

The matter I want to preach about tho are split ortolinear keyboards. I believe absolutely every typist should use them. Conventional keyboards are just bad from ergonomics perspective and eventually it’d have a toll on your wrists health. And many of these keyboards stores key mappings directly on the chip so no need to mess with weird mapping software.

Having said that, my split keyboard is one of the best investments I did in my life.

Granted, self-hosting git is not feasible for everyone, but GitHub + self hosted runners seems like a very good option.

I’m just kidding. LinkedIn feed became so unbearable, that I had to install an extension to turn it off.