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Segment Routing Maturity Model
Our Segment Routing Maturity Model provides a structured framework for moving from legacy routing to intent-based, automated traffic management. Discover where your organization stands today and how you can level up.
AI Maturity Model
A framework for organizational AI transformation that maximizes value while minimizing risk.
How Retailers Can Strike the Right Risk-Reward Balance in the Cloud
Capitalize on the benefits of cloud-powered experiences while minimizing disruption and maintaining customer trust.
Are Retailers' Channel-centric Mindsets Leaving Opportunities on the Table?
Outdated, channel-centric mindsets and organizational silos are partly to blame for retailers' inability to adopt unified commerce. Learn how to overcome this cultural conundrum so your organization can thrive.
5 Ways Retailers Are Using AI to Drive Growth, Loyalty and Efficiency
Not sure where to begin with AI? Consider these five essential use cases as starting points for transforming retail operations and customer experience with AI.
ATC Activity
Segment Routing Maturity Model
Our Segment Routing Maturity Model provides a structured framework for moving from legacy routing to intent-based, automated traffic management. Discover where your organization stands today and how you can level up.
JuicedShop Security Lab Series: Software and Data Integrity Failures
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.
Drone Landing Identification an Intel AI Reference Kit Lab
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.
AI-Powered Manufacturing Assistant
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.