Semantic-Search

NLP in Practice: Chatbots, Search, and Beyond NLP moves from research papers to real products. In the field, teams help users find answers, get help, and complete tasks faster. The best results come from clear goals, small steps, and good data. A thoughtful plan beats flashy ideas. Chatbots are common today. Start with a simple goal, like answering FAQs or guiding a user through an onboarding flow. Define a handful of user intents (order status, troubleshooting, booking) and create templates that steer the conversation. Build in a clear fallback path to a human when the bot cannot help. Track conversations to learn where users get stuck and where the bot shines. A small, frequent release cycle keeps the experience reliable and useful. ...

Vector Databases and AI-Driven Data Stores Vector databases store numerical representations of data, called embeddings. Each embedding places items in a high‑dimensional space where similar content sits near each other. This makes it easy to answer “which products or articles are most like this query?” by measuring distance in the space. Unlike traditional databases that rely on exact matches, vector stores excel at approximate similarity and fast retrieval over large text, image, or audio data. ...