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XLNet Explained: Generalized Autoregressive Pretraining for Enhanced Language Understanding
XLNet is a transformer-based language model that builds on BERT's limitations by introducing a new approach called permutation-based training.
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Florence: An Advanced Foundation Model for Computer Vision by Microsoft
Florence is a large-scale vision-language model developed by Microsoft, particularly effective for applications requiring multimodal capabilities.
Community
Understanding CoCa: Advancing Image-Text Foundation Models with Contrastive Captioners
Contrastive Captioners (CoCa) is an AI model developed by Microsoft that is designed to bridge the capabilities of language models and vision models.
Community
A Different Angle: Retrieval Optimized Embedding Models
This blog will demonstrate how GCL can be integrated with Milvus, a leading vector database, to create optimized Retrieval-Augmented Generation (RAG) systems.
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Unstructured Data Processing from Cloud to Edge
Edge computing brings data processing closer to the source on small devices; vectorDBs empower them to handle the growing unstructured data in real-time.
Community
What Are Rerankers and How Do They Enhance Information Retrieval?
This article will explore the concepts behind rerankers and demonstrate how to integrate rerankers with Milvus, a widely adopted open-source vector database, to enhance search and Retrieval Augmented Generation (RAG) applications.
Community
How Vector Databases are Revolutionizing Unstructured Data Search in AI Applications
Learn how vector databases have emerged as a transformative technology in the field of AI and machine learning, particularly for handling unstructured data. Their applications extend far beyond simple retrieval-augmented generation (RAG) systems, revolutionizing various domains including customer support, recommendation systems, drug discovery, and multimodal search.
VectorDB 101
Vector Database vs Graph Database
This article will comprehensively compare vector and graph databases, helping you understand their fundamental differences, strengths, and ideal applications
Community
Build Better Multimodal RAG Pipelines with FiftyOne, LlamaIndex, and Milvus
Enhance the capabilities of multimodal systems by efficiently leveraging text and visual data for improved data retrieval and context-rich responses.