Accelerate Edge AI with Lattice sensAI
The Lattice sensAI solution stack is a comprehensive suite of tools and resources designed to accelerate the integration of flexible, low-power inferencing at the edge.
The full-featured Lattice sensAI stack includes everything you need to evaluate, develop, and deploy FPGA-based Machine Learning / Artificial Intelligence solutions - modular hardware platforms, example demonstrations, reference designs, neural network IP cores, software tools for development, and custom design services.
The Lattice’s FPGA-based machine learning solutions are highly flexible, easy to implement, low power (from under 1 mW - 5 W), small (package sizes starting at 5.5 mm2) and priced for high volume production.
Lattice can help you accelerate deployment of always-on, on-device AI into a wide range of Edge applications including mobile, smart home, smart city, smart factory, and smart car products with end-to-end solutions targeting HMI.
To learn more about Lattice sensAI and how Lattice can help you innovate your AI application development, visit Lattice sensAI.
CrossLink-NX Voice and Vision Machine Learning Board
A board specifically designed with low power machine learning applications in mind, using CrossLink-NX 40K, a powerful FPGA with an AI accelerator.
Lattice Neural Network Compiler
Rapidly analyze, simulate, and compile various networks for implementation onto Lattice CNN/CNN Compact Accelerator IP cores.
Lattice sensAI Studio
End to end Model Zoo, data labeling, model training, validation and deployment tool.
User Attention sensing Demo
The Lattice sensAI smart vision sensing technology tracks device user's attention and intent to use making edge devices smarter and more aware of their surroundings than ever before.
Rapidly analyze, simulate, and compile various networks for implementation onto Lattice CNN/CNN Compact Accelerator IP cores.
Object Classification Reference Design
A complete design example running on popular Lattice development boards (including FPGA RTL) include Neural Network Models and sample training datasets and scripts to recreate and update the example as needed. Same examples are provided through sensAI Studio.
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