Search Results for "arm"

...It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64). Scalable. It can detect multiple always-listening voice commands with no added runtime footprint. Self-service. Developers can train custom wake word models using Picovoice Console. ...

Create, share, fetch, and model Atomic Data! AtomicServer is a lightweight, yet powerful CMS / Graph Database. Atomic Data is a modular specification for sharing, modifying, and modeling graph data. It combines the ease of use of JSON, the connectivity of RDF (linked data), and the reliability of type-safety. Atomic Data uses links to connect pieces of data, and therefore makes it easier to connect datasets to each other - even when these datasets exist on separate machines.

This repository is for the Azure SDK for JavaScript (Node.js & Browser). It contains libraries for the breadth of Azure services. Management libraries are packages that you would use to provision and manage Azure resources. Client libraries are packages that you would use to consume these resources and interact with them. The readme for each package contains code samples and package information. This readme can be found in the corresponding package folder under the folder of the service of...

...Complete control over what data should be backed up and where. How long data should be retained and how many versions to keep. Open source based with multi platform support for Windows, Mac (ARM and Intel), Linux and a generic Java 17 package.

tvm-cn is a community-driven project that provides Chinese documentation for the Apache TVM deep learning compiler stack. Apache TVM is an open-source system designed to optimize and deploy machine learning models efficiently across different hardware platforms such as CPUs, GPUs, and ARM devices. The goal of the repository is to centralize translated learning materials and technical documentation so that Chinese-speaking developers can study the TVM ecosystem more easily. The project translates official TVM guides and organizes them into structured documentation that explains how to compile, optimize, and deploy deep learning models on heterogeneous hardware architectures. ...