Lattice sensAI is an AI/ML solution stack designed for low-power, small-footprint FPGA-based artificial intelligence (AI) and machine learning (ML) applications, primarily at the far-edge near-sensor devices. It provides a combination of FPGA hardware, software tools, and IP cores to enable AI inferencing on embedded systems.
Key Features of sensAI:
- Optimized for Low Power & Low Latency next to the sensor
- Designed to run AI/ML workloads efficiently on Lattice’s low-power FPGAs (like CrossLink-NX, Certus-NX, and Nexus-based devices).
- Ideal for always-on and real-time AI processing.
- Production-Ready End Use-Case and Applications
- Accelerate time-to-market with a growing library of validated use-cases and applications, reducing development risk and enabling quick deployment in real-world scenarios.
- Pre-Optimized IP Cores & Reference Designs
- Comes with pre-optimized neural network IP cores for functions like face detection, object recognition, anomaly detection, and gesture control.
- Helps accelerate development time for AI applications.
- Toolchain: Lattice sensAI Studio
- Provides an end-to-end AI development environment, integrating model training, optimization, compilation, and FPGA deployment.
- Supports hardware/software co-design, allowing users to fine-tune models for specific use cases.
- SDK: Lattice sensAI Edge Vision Engine
- The SDK and experience visualization tool enable next-generation Human-Machine Interface (HMI) applications with advanced computer vision capabilities in FPGA, ARM, or x86 platforms.
To learn more about this product design and to access the complete documentation in GitHub, please click below.
