技术动态流

v0.3.0 ## 🚀 Zvec v0.3.0 Release Notes ### 📦 Platform Support * **Windows:** Added native support for Windows( tested with MSVC 2022/Visual Studio 17.0+ ). * **Mobile:** Enabled Android cross-compilation; verified integration in mobile application environments. * **Package Distribution:** Official Python and Node.js packages for Windows are now available. * **CI/CD:** Continuous Integration now covers macOS, Linux, and Windows (native), alongside Android (cross-compile). ### ⚡ Performance & Engineering * **Quantization:** Introduced the RabitQ algorithm, providing reduced memory usage and high

v0.2.1 delivers broad platform expansion (Android, macOS, Python 3.13/3.14), Jina Embeddings v5 & custom HTTP embedding support, IVF & int8 quantization performance gains, CI/tooling maturity (GitHub-hosted runners, buildwheel, continuous benchmarking), and robustness improvements across build, math, memory, and metric handling.

Electrobun v1.14.1-beta.0 simplifies setup by auto-downloading required CLI, core, and optional CEF binaries during build—no manual downloads needed. Just add electrobun as a dependency and follow the quick-start guide.

Release v26.1.3.52-stable includes stability improvements, bug fixes, and minor enhancements to the real-time analytics engine.

Initial release v0.1.0 of Pyrite64—expect missing features, incomplete documentation, and breaking API changes as the project is in early development.

v0.2.0 delivers major optimizations including on-device AI extension support, auto-scalable MMap metadata, unified search APIs, and native Linux ARM64 builds — alongside critical bug fixes, improved C++/Python DX, enhanced CI/CD for forks, and refreshed docs.

Release 0.84.0 provides updated dSYMs for Hermes (both legacy and V1) and React Native Core/Dependencies, enabling better debugging and crash symbolication on iOS.

TensorFlow 2.21.0-rc0 drops Python 3.9 support and introduces new quantized integer types (int2, int4, uint4) and operations in TensorFlow Lite, adds JPEG XL support in tf.image.decode_image, and exposes NoneTensorSpec in tf.data for better type introspection.