Latest Blog Posts

• Published on

  October 16, 2025

  

  Interpreting Vision Models with Grad-CAM and Attention Maps

  </>Computer-VisionInterpretabilityViT

  Why did my model classify this image as a 'cat'? This article dives deep into two key visualization techniques—Grad-CAM for CNNs and Attention Maps for Transformers—to answer that question. We explore the mechanics of how these maps are made, what influences them, and how they serve as powerful tools for debugging model biases and testing robustness.

  6 min read

  Read more →

• Published on

  October 8, 2025

  

  An Introduction to Explainable AI Methods

  AI-SecurityInterpretability

  Deep learning models are often 'black boxes,' making them difficult to trust. This article introduces the field of Explainable AI (XAI) and provides a comprehensive overview of five key post-hoc explanation methods: Occlusion Analysis, Saliency Maps, Grad-CAM, LIME, and SHAP. We explore how each technique works and its role in making AI more transparent.

  6 min read

  Read more →

• Published on

  September 30, 2025

  

  Architectures of Multimodal AI: Fusing Vision, Language, and Beyond

  AttentionComputer-VisionGenerative-AILLMsMultimodality

  Modern AI is moving beyond single-purpose models to systems that understand text, images, and audio simultaneously. This article explores the core architectural patterns—from early and late fusion to the sophisticated cross-attention mechanisms and joint embedding spaces—that enable multimodal AI to perceive the world in a more holistic way.

  5 min read

  Read more →