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KAUST doctoral student wins international InnovateFPGA Design Contest for coral medicine project

KAUST · Aug 10

KAUST doctoral student Jose Filho won the 2022 InnovateFPGA Design Contest for his "Customized Medicine for Corals" project. The project uses an automatic feeder technology to deliver coral probiotics and monitor their efficacy via cloud connectivity, computer vision, and an FPGA. The system gathers data from cameras, temperature sensors, and luminosity sensors, using AI to determine the coral's bleaching stage and deploy beneficial microorganisms. Why it matters: This win highlights KAUST's innovative research in applying AI and cloud technology to address critical environmental challenges like coral bleaching, demonstrating the potential for technology to aid marine conservation efforts.

Low-Complexity NN Technology: Model and Precision Search, Acceleration Circuit, and Applications

MBZUAI · Invalid Date

Researchers at National Taiwan University are developing low-complexity neural network technologies using quantization to reduce model size while maintaining accuracy. Their work includes binary-weighted CNNs and transformers, along with a neural architecture search scheme (TPC-NAS) applied to image recognition, object detection, and NLP tasks. They have also built a PE-based CNN/transformer hardware accelerator in Xilinx FPGA SoC with a PyTorch-based software framework. Why it matters: This research provides practical methods for deploying efficient deep learning models on resource-constrained hardware, potentially enabling broader adoption of AI in embedded systems and edge devices.