Community
The Evolution of Multi-Agent Systems: From Early Neural Networks to Modern Distributed Learning (Methodological)
In this article, we'll explore the evolution of MAS from a methodological or approach-based perspective.
Community
The Evolution of Multi-Agent Systems: From Early Neural Networks to Modern Distributed Learning (Algorithmic)
In this article, we'll discuss the evolution of MAS from its early days to the most recent developments from an algorithmic perspective.
Paper Reading
Efficient Memory Management for Large Language Model Serving with PagedAttention
PagedAttention and vLLM solve important challenges in serving LLMs, particularly the high costs and inefficiencies in GPU memory usage when using it for inference.
Community
Deep Residual Learning for Image Recognition
Deep residual learning solves the degradation problem, allowing us to train a neural network while still potentially improving its performance.
Engineering
Up to 50x Cost Savings for Building GenAI Apps Using Zilliz Cloud Serverless
Zilliz Cloud Serverless allows users to store, index, and query massive amounts of vectors at only a fraction of the cost while keeping a competitive level of performance.
Community
Milvus on GPUs with NVIDIA RAPIDS cuVS
GPU-accelerated vector search through NVIDIA's cuVS library and CAGRA algorithm are highly beneficial for optimizing AI app performance in production.
Community
Improving Analytics with Time Series and Vector Databases
In this article, we'll explore time series databases in detail and walk you through a use case where we'll store time-series data in InfluxDB, query the data, transform it into vector embeddings, store the embeddings in Milvus, and finally perform a similarity search with Milvus.
Community
Understanding Boolean Retrieval Models in Information Retrieval
In this article, we'll discuss a specific information retrieval method known as Boolean Retrieval Models.
Community
Constitutional AI: Harmlessness from AI Feedback
In this article, we will discuss a method, Constitutional AI (CAI), presented by the Anthropic team in their paper “Constitutional AI: Harmlessness from AI Feedback".