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The JuicedShop series is designed to explore the capabilities of Burp Suite and web application testing. Divided into shorter, palatable CTF games, the JuicedShop series features the vulnerable Juice Shop web application. These challenges provide an opportunity to apply web application testing methodologies in a live environment for real-world use cases.

This lab will walk you through one of Intel's AI Reference Kits to develop an optimized semantic segmentation solution based on the Visual Geometry Group (VGG)-UNET architecture, aimed at assisting drones in safely landing by identifying and segmenting paved areas. The proposed system utilizes Intel® oneDNN optimized TensorFlow to accelerate the training and inference performance of drones equipped with Intel hardware. Additionally, Intel® Neural Compressor is applied to compress the trained segmentation model to further enhance inference speed. Explore the Developer Catalog for information on various use cases.

The WWT AI-Powered Predictive Maintenance Assistant uses machine learning and a large language model to predict equipment failures, schedule maintenance, generate instructions, and answer related questions. Through an interactive UI, users explore proactive, data-driven strategies to reduce downtime, extend machine life, and optimize resources, demonstrating AI's transformative potential in manufacturing environments.