Show HN: Rustacean AI – Tracking Rust's Expanding Role in AI (rustacean.ai)

Rustacean AI is a new curated newsletter and tracker focused on Rust’s growing role in AI and machine learning, launching a regular series of short issues that surface tooling, libraries, model ports, deployment patterns and ecosystem news. The first issues (early October 2025) set out to map how Rust is being used from research prototypes to production inference and edge deployments, offering concise pointers for developers who want to follow or adopt a Rust-first ML stack. This matters because Rust uniquely combines low-level performance, predictable memory use and safe concurrency—attributes that help reduce latency, memory overhead and runtime bugs in ML systems. Expect coverage of Rust-native frameworks and bindings (e.g., tch-rs/libtorch, burn, candle, linfa, tract/ONNX runtimes), FFI and Python interop (pyo3/maturin), GPU and accelerator access (CUDA/Vulkan/WGPU crates), and WASM-based inference for browsers and embedded devices. For practitioners, that means clearer signals about when to trade Python convenience for Rust’s production advantages, how to integrate Rust into hybrid stacks, and which crates or deployment patterns are maturing enough for real-world workloads.