Discover how the GPX10 processor enables on-device AI inference and incremental training without cloud dependency. See how real-time edge AI delivers low-latency, power-efficient, and secure intelligence for embedded applications.

Discover how the GPX10 delivers real-time AI inference for audio, vision, and sensor applications with ultra-low power consumption. Learn how it enables always-on edge intelligence without cloud dependency for wearables, smart sensors, and IIoT.

See how the GPX10 enables real-time fall detection using ultra-low-power edge AI. This demo showcases accurate, on-device inference without cloud dependency for applications including elderly care, worker safety, and smart wearables.

Learn how to install the Ambient SDK for GPX processors on Windows. This step-by-step guide covers SDK setup, drivers, toolchains, Eclipse IDE, Python, environment variables, and final verification to get your development environment ready.

Learn how to create, train, compile, and deploy a custom wake-word AI model on the GPX10 Development Kit using EdgeSphere and Ambient Scientific's TensorFlow/Keras toolchain, from dataset preparation and model training to live hardware validation.

Learn the complete EdgeSphere workflow for GPX processors, from firmware flashing and data collection to dataset validation and deployment. This tutorial covers audio and vision workflows for building edge AI applications.

Learn how to flash, run, and test your first AI model on the GPX10 Development Kit using the Ambient SDK. This tutorial walks through building, debugging, and validating an Alexa wake-word CNN model on real hardware.