A new open-source benchmark, "apple-silicon-llm-bench," reveals that Google's LiteRT-LM runtime outperforms MLX-Swift on the iPhone 17 Pro for Gemma 4 E2B inference, achieving 55.4 tok/s with 4.5x les…
Google launched Coral, a full-stack platform for edge AI that combines an AI-first hardware architecture with a unified developer experience to enable efficient, local AI processing. The platform prov…
The article describes the development of Remora, a privacy-focused dream journaling app that uses Google's Gemma 4 E2B model for on-device AI analysis, avoiding cloud uploads. The engineering team fac…
SafeSMS is a privacy-focused Android application that uses the on-device Gemma 4 E4B AI model to detect SMS-based scams, phishing, and spam without sending data to the cloud. The app analyzes incoming…
LiteRT, a cross-platform framework for on-device AI, enables developers to leverage Neural Processing Units (NPUs) for faster and more efficient AI features like real-time video effects and speech rec…
Arm's Scalable Matrix Extension 2 (SME2) integrates a matrix-compute unit into the CPU, enabling up to 5x faster inference for generative AI workloads on mobile devices. It highlights how Google AI Ed…
LiteRT-LM, part of Google AI Edge, is an optimized runtime engine for deploying Gemma 4 models on-device across platforms like Chrome, ChromeOS, and Pixel Watch. It achieves high performance through a…
The Google Tensor ML SDK has moved from an Experimental Access Program to Beta, now integrating with LiteRT to provide a unified API for deploying machine learning models on the Tensor Processing Unit…