Did they train autocomplete? I mean the code is open source so anyone can scrape it and train it too. I'm kind of glad they did train it because otherwise we'd still be stuck with Apple level AI models right now.

The whole reason we have so many models, including open weight models, that are all competitive with each other is because the data is free and anyone can be training off it. If the goal was to monetize the source code I guess the authors shouldn't make it open source.

You can argue all day about whether A is slightly more rotten than B, but if they are both rotten then in the grand scheme they will both end up being the same thing if something doesn’t get fixed.

If I found some DVD lying on the ground and watched it and I didn't pay for it, it's really up to me to decide if I want to pay the creator so they can continue to produce content. If I don't pay then obviously it doesn't help them produce more content... but the consumption of the content itself neither felt nor heard by the creators.

The coding models work really well with esoteric syntaxes so if the biggest hurdle to adoption of haskell was syntax, that's definitely less of a hurdle now.

> Instead, you're writing non-trivial proofs about all possible runs of the program.

All possible runs of a program is exactly what HM type systems type check for. This fed into the coding model automatically iterates until it finds a solution that doesn't violate any possible run of the program.

These aren’t just strict type systems but the language allows for algebraic data types, nominal types, etc, which allow for encoding higher level types enforced by the language compiler.

The AI essentially becomes a glorified blank filler filling in the blanks. Basic syntax errors or type errors, while common, are automatically caught by the compiler as part of the vibe coding feedback loop.

Aircaps demos show it to be pretty fast and almost real time. Meta's live captioning works really fast and is supposed to be able to pick out who is talking in a noisy environment by having you look at the person.

I think most of your issues are just a matter of the models improving themselves and running faster. I've found translations tend to not be out of whack, but this is something that can't really be solved except by having better translation models. In the case of Airpods live translate the app will show both people's text.