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Healthcare revolution: Vector databases for patient similarity search and precision diagnosis

Data Science Dojo

Traditional hea l t h c a r e databases struggle to grasp the complex relationships between patients and their clinical histories. Vector databases are revolutionizing healthcare data management. That’s where vector databases come in handy—they are made on purpose to handle this special kind of data.

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Top vector databases in market

Data Science Dojo

A vector database is a type of database that stores data as high-dimensional vectors. One way to think about a vector database is as a way of storing and organizing data that is similar to how the human brain stores and organizes memories. Pinecone is a vector database that is designed for machine learning applications.

Database 195
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Exploring the fundamentals of online transaction processing databases

Dataconomy

What is an online transaction processing database (OLTP)? But the true power of OLTP databases lies beyond the mere execution of transactions, and delving into their inner workings is to unravel a complex tapestry of data management, high-performance computing, and real-time responsiveness.

Database 159
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Google Research, 2022 & beyond: Algorithmic advances

Google Research AI blog

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. Hence, developing algorithms with improved efficiency, performance and speed remains a high priority as it empowers services ranging from Search and Ads to Maps and YouTube. You can find other posts in the series here.)

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OpenSearch Vector Engine is now disk-optimized for low cost, accurate vector search

Flipboard

A right-sized cluster will keep this compressed index in memory. Disk mode uses the HNSW algorithm to build indexes, so m is one of the algorithm parameters, and it defaults to 16. He leads the product initiatives for AI and machine learning (ML) on OpenSearch including OpenSearchs vector database capabilities.

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It’s time to shelve unused data

Dataconomy

Databases are the unsung heroes of AI Furthermore, data archiving improves the performance of applications and databases. By removing infrequently accessed data from primary storage systems, organizations can improve the performance of their applications and databases, which can lead to increased productivity and efficiency.

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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

For this post we’ll use a provisioned Amazon Redshift cluster. Set up the Amazon Redshift cluster We’ve created a CloudFormation template to set up the Amazon Redshift cluster. Implementation steps Load data to the Amazon Redshift cluster Connect to your Amazon Redshift cluster using Query Editor v2.