How Oracle AI Database 26ai Addresses The Enterprise AI Data Paradox

Oracle Database 26ai embeds AI capabilities directly into production databases, enabling enterprises to deploy AI securely ...

How OpenAI is scaling the PostgreSQL database to 800 million users

For enterprises deploying AI applications with similar read-heavy workloads and unpredictable traffic spikes, OpenAI's ...
Business Wire

Yugabyte Releases Distributed Database Trends Report, Unveils Vision for Database Modernization for Scalable and Resilient AI Applications

SUNNYVALE, Calif.--(BUSINESS WIRE)--Yugabyte, the distributed database experts, today announced the findings of its independent Distributed Database Trends Report and its vision for agentic database ...
dbta

Smarter, More Distributed, More Diverse—And a New Role for RDMSes: The Next Revolution For Databases

For the database world, the future looks extremely challenging—and, even more, exceedingly promising. Looking ahead over the next few years, organizations will be relying on their databases in ways ...
The Next Platform

Oracle Cloud Launches Database Service for Agentic AI, Analytics Workloads

A decade and a half of enterprise cloud adoption has spread vast amounts of data and processing around the globe, and the onslaught of generative AI – and now agentic AI – is only accelerating it.
GitHub

example_data folder missing from Windows distribution

The \example_data folder is not included in the Windows distribution of 6.1.0! @jamescrake-merani has independently checked for and verified this bug. The \example_data folder is present in 6.0.1 & ...
Scientific Research Publishing

Deep, G., Sidhu, J. and Mohana, R. (2022) Insider Threat Prevention in Distributed Database as a Service Cloud Environment. Computers & Industrial Engineering, 169, Article 108278.

ABSTRACT: Security and privacy have always been major concerns in cloud computing environments, and with the increasing complexity of distributed cloud systems, these concerns have become even more ...
IEEE

Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples

Abstract: Semi-supervised learning (SSL) methods have shown promising results in solving many practical problems when only a few labels are available. The existing methods assume that the class ...