Lattice, NVIDIA Boost Edge AI

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At the Lattice Developers Conference, Lattice Semiconductor (NASDAQ: LSCC) unveiled a collaborative effort with NVIDIA, introducing a new reference sensor-bridging design aimed at expediting the advancement of edge AI applications.

 

This innovative reference board, combining the efficiency of Lattice FPGAs with NVIDIA’s Jetson Orin and IGX Orin platforms, stands as a significant stride in the realm of edge AI technology. Tailored to meet developers’ needs for enhanced sensor connectivity, design scalability, and minimized latency, the board targets the creation of high-performance edge AI applications in sectors such as healthcare, robotics, and embedded vision.

 

The collaboration between Lattice Semiconductor and NVIDIA aims to bolster the open-source developer community by enhancing the efficiency of sensor-to-edge AI compute applications, potentially fostering a wave of innovation.

 

Esam Elashmawi, Chief Strategy and Marketing Officer at Lattice Semiconductor, emphasized the transformative potential of AI across various sectors. He expressed anticipation for the collaboration, envisioning accelerated adoption of edge AI applications. Elashmawi stated, “We are excited to work with NVIDIA to extend the reach of our reference solutions, bringing more innovation to our customers and ecosystem to simplify and speed the implementation of edge AI applications.”

 

Amit Goel, Director of Embedded AI Product Management at NVIDIA, highlighted the increasing demand for real-time insights and autonomous decision-making driven by AI. He noted the growing trend of developers integrating diverse sensors into NVIDIA’s edge computing platforms. Goel commented, “This collaboration with Lattice will accelerate innovations in sensor processing and help simplify the deployment of edge-to-cloud AI applications.”

 

The FPGA-based reference board is now available for early-access customers. Lattice Semiconductor intends to broaden its availability, including application examples, in the first half of 2024, aiming for wider accessibility and the potential for significant advancements in AI development.

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