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"The earlier implementation could not be driven to zero of them, because boxing was load-bearing in its emitter"

In the docs of the repo of their TS to C++ compiler. https://github.com/geastack/compiler


I see what you’re getting at, but let’s not pretend like “load-bearing” is something that AIs made up. It was a turn of phrase long before AIs became mainstream and people are still allowed to use it.

"geatsc: the GeaStack TypeScript-to-C++ compiler. A clean-room rewrite built on one rule — a statically typed value that reaches a dynamic carrier is a defect, not a fallback."

The whole thing is like this

But to be fair, it's late 2026 so it's to be expected now that the vast majority of code and surrounding artifacts are AI generated. It's just a fact of life.


Heh, we spent 6 months writing and rewriting the compiler a couple of times and were just too excited about the final architecture. Thank you, simplified.

I think there was a lot more brainpower invested in the media generation side of things. The noise-based diffusion technique is further developed. It had a discovery of applying a physics-based understanding of Brownian motion to guide it. Image generation has comparatively simple training process - this is an image with dog, and without dog (contrastive learning).

Might be worth to watch the diffusion based LLMs.


That's just https://en.wikipedia.org/wiki/Unsharp_masking and has been around since decades.

After you clamped the stem, the preload job of the cap is done and it can be replaced.


Mm. Yes, but I wouldn't trust that.


Had to remember how ads looked like when Flash was popular. We had fullscreen ads that interacted with the content!

Interactive Flash Banner Ads Animation from the 2000s https://www.youtube.com/watch?v=w0Lu8BsjvK0


You mean people come to hate code reviews.

If you don't use those rules, you'll argue about something else in the code reviews. Likely something even more ambigous that wasn't explicitly written down for everyone as a baseline.


I am surprised by the rather bad output. It doesn't achieve qwen image 1 quality in composition or anatomical correctness. Tested on chat.qwen.ai

I am seeing third legs and glowing eyes. It's a Microsoft Lens level of quality and that one was pulled.


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