AI

What if a signature matches perfectly because a fraudster copied the genuine signature?

That’s why signature verification needs more than one neural network.

This project combines:

YOLO detection → Siamese embeddings → structural analysis → document forensics → evidence fusion → explainable reports.

It’s a great example of how real AI systems move beyond model.predict().

Can AI tell whether a document contains a handwritten signature?

Finding the signature is only the beginning.

In this project, we combine YOLO, Segment Anything, OpenCV, feature extraction, quality gates, and human review to build an AI-assisted signature analysis pipeline.

Along the way, you’ll learn one of the most important lessons in applied AI:

a model should never claim more than its input can prove.

Learn how to build an AI-powered deepfake image detection system that combines computer vision, image forensics, metadata analysis, and explainable AI to detect manipulated images with confidence.

Banks process enormous volumes of market data every day—but one stale or incorrect price can affect valuations, P&L, risk metrics, and regulatory reporting.

In this hands-on Python project, we build an AI-powered Market Risk Control Cockpit that combines deterministic rules, Isolation Forest, portfolio exposure, scenario analysis, Streamlit, and generative AI.

The goal is not to replace market-risk analysts.

It is to help them find the alerts that matter.

Can AI tell whether two photos belong to the same person?

In this week’s hands-on AI project, you’ll build a complete face recognition system using Python and InsightFace. Learn how AI detects faces, generates facial embeddings, compares identities, and ranks the closest matches—all while understanding the concepts behind the code. Perfect for beginners looking to build a real-world computer vision project.

Can an AI predict how fluid moves?

In this piece, I explore how a physics foundation model—WALRUS—learns to forecast the evolution of a heated fluid system. Instead of solving equations, the model observes patterns and generates its own version of the future. The result is a striking simulation that reveals both the power and the limits of AI in modeling the physical world.

Can AI help us understand how medicines interact with the body?
In this edition, I explore a beginner-friendly experiment where I used AI tools like AlphaFold and AutoDock Vina to go from a protein sequence to a plausible drug-binding hypothesis—all on a laptop. A simple walkthrough, even if you’re new to biology.

What if you could test your product idea before having real users?
In this post, I show how to use AI personas to build a synthetic focus group—generate surveys, simulate responses, and uncover insights early.

Earth Models, World Models, and Global Models are three fast-growing “families” of AI systems that are often mentioned together—but they solve very different problems. This blog provides an accessible, research-oriented map of the landscape for readers who are new to AI (and for technical readers entering the field).