MirahLabs Engineering Blog
Technical insights, tutorials, and architectures written by our design and backend engineers.
Diffusion Models Explained: DALL-E 3 and Stable Diffusion Mechanics
Understand the math and mechanics behind modern generative image models: forward diffusion, reverse denoising U-Nets, and classifier-free guidance.
Vector Search at Scale: Hierarchical Navigable Small World (HNSW) Indexes
Similarity searches on millions of high-dimensional vectors are computationally expensive. Learn how HNSW graph indexes make nearest-neighbor search sub-millisecond.
Vector Databases Compared: Pinecone vs Weaviate vs pgvector
A detailed comparison of three leading vector database solutions—Pinecone, Weaviate, and pgvector—covering performance, scalability, cost, and best-fit use cases.
Recommender Systems: Collaborative Filtering to Deep Learning Architectures
Explore the evolution of recommender systems, from simple matrix factorization algorithms to deep neural networks like Wide & Deep and Two-Tower architectures.
Computer Vision with YOLO and PyTorch: From Training to Edge Deployment
Object detection with YOLO achieves real-time performance even on edge devices. Learn how to train custom YOLO models with PyTorch and deploy them to edge hardware using TensorRT and ONNX.
Graph Neural Networks (GNNs): Concepts and Practical Applications
Graph Neural Networks (GNNs) extend deep learning to non-Euclidean domains. Explore graph convolutions, message passing, and real-world applications in recommendation systems.