Mihai Bratan@Martel

WaferSight by Team MiniTehnicus is an end-to-end semiconductor yield intelligence platform designed to catch wafer defects and process drift before they result in costly scrapped silicon. Built and accelerated using the AMD AI Notebook, WaferSight classifies spatial defect patterns—such as Center, Edge-Ring, Edge-Loc, and Scratch—with high precision across single wafers and 25-wafer production lots. Rather than acting as a black-box classifier, WaferSight provides full explainability through Grad-CAM spatial heatmaps and cosine similarity search over CNN embeddings to retrieve the top five matching historical wafers. When recurring defects trigger a statistical drift alarm (at least three of the last five wafers), an integrated AI Agent cross-references fabrication troubleshooting manuals to deliver immediate root-cause diagnostics. Finally, WaferSight translates AI predictions into real-time economic decisions—comparing expected scrap costs against line downtime to automatically recommend whether engineers should Hold or Continue production.

🌎 Hybrid Hackathon | 💻 Online Build: 12-17 October 2026 | On-site phase: 17-18 October 2026 To participate in the hackathon, simply click Sign up with AMD. If you are not already a member of the AMD AI Developer Program (ADP), you will need to create an account. The AMD Developer Hackathon: ACT III is a hands-on event for developers, founders, engineers and builders who want to push what’s possible with AI on real infrastructure. 📍 If approved for the on-site experience, you'll also have the opportunity to showcase your project live. Travel and accommodation will not be covered.