Synaptics and Google Launch Developer Board for Edge AI Products
Synaptics and Google Research unveiled the Coralboard, a development platform designed to help engineers build edge AI products faster. The board combines Synaptics' Astra processor and Torq neural processing unit with Google's Coral NPU technology, targeting developers who need to move from prototypes to production systems.
The Coralboard runs on a dual-core Synaptics Astra SL2619 processor with 2GB of RAM and a neural processing unit capable of 1 trillion operations per second. It includes camera and display connections, microphones, and support for Wi-Fi and Bluetooth modules. The compact design fits standard developer workflows without requiring extensive hardware setup.
What Developers Get Out of the Box
The board supports Google's Gemma 3 270M language model and uses Synaptics' Torq toolchain, an open-source framework for building and deploying AI models. Developers can work with vision, audio, and generative AI tasks using a single workflow across the platform.
At Google I/O 2026, Synaptics demonstrated a live installation called "Jellectronica" that shows practical use. The system ran object detection on a live jellyfish video stream, converting movement into control signals for a music generation model. The demo illustrates how developers can combine real-time computer vision and inference on a single device.
Who Benefits
The platform targets AI engineers, system architects, and manufacturers building next-generation products that need to run AI models locally without cloud connectivity. The focus on power efficiency addresses a core constraint: devices that must run all day on battery power.
Synaptics and Google are distributing Coralboards at Google I/O 2026, with attendees able to take home units pre-configured for immediate development work. The companies positioned the board as a way to reduce setup friction and let teams focus on building applications rather than configuring hardware.
For product developers looking to add AI capabilities to devices, understanding the technical requirements and toolchain options matters. AI for Product Development and AI Coding Courses can help teams evaluate how to integrate these technologies into their workflows.
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