
Apple has announced a new version of Siri AI, aiming to enhance its capabilities across its ecosystem. The updated Siri is designed to be more conversational and can interact with apps, read onscreen content, and manage tasks. It is built on new Apple Foundation Models developed in collaboration with Google. Despite these advancements, the rollout is limited to certain devices and regions, with initial availability only in English. Apple's approach emphasizes privacy, processing queries on-device or via its Private Cloud Compute.
Read originalLlama.cpp's latest update introduces speculative decoding support for GLM-5.2, enhancing its capabilities with NextN/MTP features. This addition allows for more efficient tensor loading and context management, particularly benefiting models using the GLM_DSA architecture. The update also includes options for exporting models with or without the MTP feature, providing flexibility for developers. This release marks a step forward in optimizing model performance and adaptability, especially for those leveraging the GLM-5.2 framework.
The b10178 release of llama.cpp enhances its server capabilities by adding trace logging for slot similarity checking, offering developers detailed insights into prompt cache slot selection processes. This update includes specifics on skip reasons and similarity calculations, which can aid in performance optimization. While no new model architectures are introduced, the release continues to support a wide array of platforms, such as macOS with KleidiAI, Ubuntu with ROCm 7.2, and Windows with CUDA 12 and 13. This makes llama.cpp a more versatile tool for developers working on different systems, reinforcing its position as a comprehensive inference runtime.