myDevices vs. Mu

This system enables secure interactions with devices using both HTTP and MQTT protocols while simultaneously receiving data from LoRa Network Servers and various IoT Cloud streams. Recognized as a serverless computing solution, often termed function as a service (FaaS), it boasts online editing capabilities, along with support for codecs and various integrations. It efficiently processes and standardizes incoming data from devices, adeptly translating uplink messages and encoding downlink commands to facilitate the deployment of integration functions. The architecture is designed to manage device registration, configuration, provisioning, and it also streamlines Firmware Over The Air (FOTA) scheduling and batching. Users have the convenience of easily deregistering and reregistering devices via the LNS Switch feature. Furthermore, it securely retains LoRaWAN keys and SSL/TLS certificates, enabling users to access real-time insights into their data. With remarkable performance, the system manages substantial data volumes and allows for rapid queries across extensive telemetric and historical records. It is capable of processing millions of data points every second and provides both vertical and horizontal scalability, supported by a powerful data streaming processing engine. This adaptability ensures that data management remains not only efficient but also responsive, keeping pace with the continuously evolving needs of IoT applications. Moreover, the system's architecture is built to accommodate future growth, ensuring that as new devices and applications emerge, they can be integrated seamlessly.

On June 23, 2025, Microsoft introduced Mu, a cutting-edge language model boasting 330 million parameters and designed to significantly improve the agent experience in Windows environments by seamlessly converting natural language questions into functional calls for Settings, with all operations executed on-device via NPUs at an impressive speed exceeding 100 tokens per second while maintaining high accuracy. Utilizing Phi Silica optimizations, Mu's encoder-decoder architecture employs a fixed-length latent representation that notably minimizes computational requirements and memory consumption, achieving a 47 percent decrease in first-token latency and delivering a decoding speed that is 4.7 times faster on Qualcomm Hexagon NPUs in comparison to traditional decoder-only models. Furthermore, the model is enhanced by hardware-aware tuning methodologies, which incorporate a strategic 2/3–1/3 division of encoder and decoder parameters, shared weights for both input and output embeddings, Dual LayerNorm, rotary positional embeddings, and grouped-query attention, facilitating rapid inference rates that surpass 200 tokens per second on devices like the Surface Laptop 7, along with response times for settings-related queries that are under 500 ms. This impressive blend of features and optimizations establishes Mu as a revolutionary development in the realm of on-device language processing capabilities, setting new standards for speed and efficiency. As a result, users can expect a more intuitive and responsive experience when interacting with their Windows settings through natural language.