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한국어DiskANN
Concept
DiskANN is a graph-based approximate nearest neighbor search algorithm from Microsoft Research that keeps a compressed navigation layer in RAM and the full-precision graph on SSD. It is used in services such as Azure Cosmos DB and SQL Server vector search.
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Articles about DiskANN (4)
- Решение проблемы миллиарда векторов в Azure AI Search
· Mirko Peters
Добро пожаловать в наш подробный разбор одной из самых острых задач современного корпоративного искусственного интеллекта: масштабирования векторного поиска до миллиардов записей. - Решение проблемы миллиарда векторов в Azure AI Search
· Mirko Peters
Разберите уникальные технические сложности поиска по огромным наборам данных в масштабе. В этой статье рассказывается, как высокая размерность и ограничения памяти влияют на рабочи - Conquering the Billion-Vector Problem in Azure AI Search
· Mirko Peters
Welcome to our deep dive into one of the most pressing challenges in modern enterprise artificial intelligence: scaling vector search to billions of records. If you… - Solving the Billion-Vector Problem in Azure AI Search
· Mirko Peters
Explore the unique technical challenges of searching massive datasets at scale. This post breaks down how high dimensionality and memory constraints impact enterpri…
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Sources
- Profile: www.microsoft.com/research/publication/diskann-fast-accurate-billion-point-nearest-neighbor-search-on-a-single-node
- Feed for this topic (RSS): entity/diskann/feed.xml
- Articles on this topic: 4
Maintained by Mirko Peters (Microsoft MVP) · Last updated: