swift-bridge makes it easy to pass and share high-level types between Rust and Swift, such as String, Option<T>, Result<T, E>, struct, class and more.
It also helps you bridge higher level language features, such as async functions and generics.
Using swift-bridge should be safer, more performant and more ergonomic than managing Rust and Swift FFI by hand.

Хаотичное поведение Apple может привести к потере доверия российских пользователей. Думаю, компании следует объясниться: почему она лишает миллионы людей доступа к привычным сервисам, сначала банковским, потом транспортным, теперь коммуникационным

None of the tools at the application level surfaced any errors, crashes, or log entries that provided useful clues. Application-level observability can have a blind spot for bugs that live below its awareness.

The failure occurred intermittently, scaled with response size, couldn’t be reproduced with simple tools like curl, and disappeared when we observed the system more closely. These signals pointed to a timing-dependent bug in the connection layer, not in the application logic.

Our breakthrough came from using kernel-level tooling with strace, the one layer that records what actually happened on the socket. The underlying bug lived in the few milliseconds between a partial flush and a premature shutdown — a window that opened only after we made the system faster.

Rust png crate, also known as image-png, implements PNG encoding and decoding in safe Rust. It is compliant with the third edition of the PNG specification, including APNG support.
A year ago it was already the fastest PNG decoder in the world. Since then it has gotten even faster.

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image-png is used as the default PNG implementation in Chromium since M139 (August 2025) across all platforms [выделение моё], both on desktop and on mobile.

This required meeting a remarkably high bar in terms of features, performance, correctness, compatibility and security. It would only ship if there were no regressions in any of those categories!

The font shaping engine HarfBuzz, used in applications such as Firefox and Chrome, comes with a Wasm shaper allowing arbitrary code to be used to "shape" text.

In particular, this "arbitrary" code could in principle be an entire LLM inference engine with trained parameters bundled inside, relying on treating text containing magic symbols for fake "ligatures" to initialize the LLM and use it to generate text.

It could also in principle be an entire LLM inference engine (Llama in our case, hence the name) except instead of only being in principle it's what this is.