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MCUs, NPUs, CPUs, GPUs. Build datasets, train models, and optimize libraries to run directly on device; from the smallest microcontrollers to gateways with the latest neural accelerators (and anything in between). The world’s most innovative companies choose Edge Impulse.
Edge Impulse empowers ML teams to run AI at peak performance on any edge hardware, with unmatched ease and speed.
Welcome to Edge Impulse! We enable professional developers and researchers to create the next generation of intelligent products with Edge AI. In this documentation, you'll find user guides, tutorials, and API documentation.
Edge Impulse is the leading edge AI platform for collecting data, training models, and deploying them to your edge computing devices. It provides an end-to-end framework that easily plugs into your edge MLOps workflow.
We’re building the future of data-driven engineering. Edge Impulse is ushering in the future of embedded machine learning by empowering developers to create and optimize solutions with real-world data.
The impulse runner is a powerful tool that allows you to run your impulse on your development board and interact with it using an embedded API server. This feature is useful for custom applications, IoT devices, web applications, and mobile applications that need to interact with the model running on the Linux device.
1 day ago · SAN JOSE, Calif., June 28, 2024--Edge Impulse has launched new capabilities that leverage generative AI to create synthetic data on the edge, from images, to speech, to audio data.
1 day ago · Edge Impulse’s technology empowers developers to bring more AI products to market, and helps enterprise teams rapidly develop production-ready solutions in weeks instead of years.
Using the Edge Impulse Python SDK with Weights & Biases. Using the Edge Impulse Python SDK with SageMaker Studio. Using the Edge Impulse Python SDK to upload and download data. Label image data using GPT-4o. Label audio data using your existing models. Generate synthetic datasets. Generate image datasets using Dall·E.
Edge machine learning (edge ML) is the process of running machine learning algorithms on computing devices at the periphery of a network to make decisions and predictions as close as possible to the originating source of data. It is also referred to as edge artificial intelligence or edge AI.
