Edge Impulse
Ambiq’s Apollo4 Plus SoC Leverages Edge Impulse for Scalable Edge AI Solutions - News
November 21, 2024Austin, Texas. Ambiq is joining the Edge Impulse network to deliver scalable AI models on the Apollo4 Plus System-on-Chip (SoC) ideal for edge AI such as speech, health, and more AI applications. The Apollo4 Plus utilizes Subthreshold Power Optimization Technology (SPOT) to achieve 10X more proficiency for AI processing vs. other Arm M4-based solutions.
The Road to embedded world North America: Edge Impulse Empowers Developers to Innovate Edge AI - Blog
September 27, 2024Join Edge Impulse at Embedded World North America to witness how it is transforming edge AI projects by empowering developers and ML engineers to build datasets (including with synthetic data), train models, and optimize libraries to run directly on device, from the smallest microcontrollers to gateways, with the latest neural accelerators (and everything in between).
Edge Impulse Enables Visual Anomaly Detection on any Edge Device - News
July 22, 2024San Jose, California. Edge Impulse announced an innovation enabling visual anomaly detection on any edge device, from NVIDIA GPUs to Arm MCUs, through the first model architecture of its kind, FOMO-AD (Faster Objects, More Objects - Anomaly Detection). To enhance the productivity of visual inspection systems, the scalable FOMO-AD can train models to identify and index anything outside set criteria as an anomaly in video and image data.
Edge Impulse and Particle Team-Up For ML IoT - News
June 29, 2023San Jose, California. The Edge Impulse Studio platform now has native support for Particle's new Photon 2 board. The team-up of Edge Impulse and Particle powers edge AI with the integration of the Particle ecosystem into deployment of trained AI models to the Photon 2 board. The collaboration is the first IoT Integration for Edge Impulse.
Best in Show Nominee: Edge Impulse - BrickML - Product
March 10, 2023BrickML is a standalone device for measuring and monitoring machine health with machine learning (ML). It tracks current (MCSA), vibration, temperature, and audio via its integrated sensors and onboard computer. Using advanced ML algorithms, BrickML analyzes data on the device itself to detect subtle changes in machine behavior, predicting potential failures before they occur. The compact design allows for easy integration into existing systems, providing real-time data analysis and actionable insights, right at the edge. It is fully integrated into the Edge Impulse platform, allowing users to quickly and easily create AI algorithms for their specific use cases.
Syntiant Brings Artificial Intelligence Development with Introduction of TinyML Platform - News
October 04, 2021Syntiant Corp unveiled its TinyML Development Board, a developer kit aimed at both technical and non-technical users building machine learning-powered applications in smart products, such as speech commands, wake word detection, acoustic event detection, and other sensor use cases.