AIdventure.

Speeding up Attention Layers

Multi-head, Multi-Query & Grouped-Query Attention layers clearly explained. How cache works in the Attention layers

TF-IDF & BM25 Explained

TF-IDF and BM25 are two of the most used algorithms in Information Retrieval. In this post we will explain how they work

Precision, Recall and F1 Score metrics

Dive into the intuition behind Precision, Recall, and F1 Score. Understand how these metrics balance quality and quantity, from binary problems to object detection.

Load your datasets in Label Studio with JSON

Configure local file serving and JSON imports to handle thousands of files in seconds—the production-ready approach

The Receptive Field in Convolutional Neural Networks

Why do architectures use 3x3 filters? It is because of something called Receptive Fields.

Depthwise Separable Convolutions

Same results as standard convolutions with only a fraction of the computational cost. Explore the tricks behind MobileNet and efficient CNNs