Building a recommendation system is hard. Not just the engineering, but the decision-making process before you write a single line of model code. Will you use collaborative filtering? Will you have sufficient user behavior signals to apply a deep learning approach? What if you’re launching a new product with zero data, a classic cold start […]
In the last few years, embeddings have become one of the most essential building blocks in AI systems, most especially in Search, Recommendation Engines, and Retrieval-Augmented Generation, or RAG. If you have worked with semantic search, vector databases, or LLM-powered assistants, you have already relied on embeddings, whether you know it or not. In this […]
