March 2021 Summaries

MLOps is a systemic approach to AI model life cycle management, which involves monitoring a machine learning model throughout its lifecycle and governing everything from underlying data to the effectiveness of a production system that relies on a particular model. It is necessary for building, maintaining, and deploying AI applications at scale. Key components of MLOps include continuous integration/continuous delivery (CI/CD), model development environments (MDE), champion-challenger testing, model versioning, model store and rollback. Milvus is an open-source vector data management platform that supports the transition to Software 2.0 and manages model life cycles with MLOps.

The application of artificial intelligence (AI) in real estate is transforming home search processes. With the help of AI, tech-savvy real estate professionals can assist clients in finding suitable homes faster and simplify property purchasing. The coronavirus pandemic has accelerated interest, adoption, and investment in property technology (proptech), indicating its growing role in the industry. This article explores how Beike utilized vector similarity search to develop a house hunting platform that provides personalized results and recommends listings in near real-time. Vector similarity search is useful for various AI, deep learning, and traditional vector calculation scenarios, as it helps make sense of unstructured data such as images, video, audio, behavior data, documents, and more. Beike uses Milvus, an open-source vector database, to manage its AI real estate platform. The platform converts property listing data into feature vectors, which are then fed into Milvus for indexing and storage. This enables efficient similarity searches based on user queries, improving the home search experience for house hunters and helping agents close deals faster.

iYUNDONG is an Internet company that aims to engage sport lovers and participants of events such as marathon races. It builds artificial intelligence (AI) tools that can analyze media captured during sporting events to automatically generate highlights. One key feature of the iYUNDONG sports App, called "Find me in motion," allows users who took part in a sport event to retrieve their photos or video clips from a massive media dataset by uploading a selfie. The app uses Milvus, an open-source vector database, to power its image retrieval system and achieve quick and large-scale vector search. iYUNDONG chose Milvus for its ability to support multiple indexes, efficiently reduce RAM usage, and regularly release new versions with powerful out-of-the-box features.

Xiaomi, the multinational electronics manufacturer, has built an AI-powered news recommendation engine into its mobile web browser using Milvus, an open-source vector database. The application's core data management platform is designed for similarity search and artificial intelligence. This system uses AI to suggest personalized content and cut through the noise of news by recommending relevant articles based on user search history and interests. Xiaomi selected BERT as the language representation model in its recommendation engine, which can be used as a general natural language understanding (NLU) model for various natural language processing tasks. The AI-powered content recommendation system relies on three key components: vectorization, ID mapping, and approximate nearest neighbor (ANN) service.