Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

EDB Delivers "Intelligence per Watt" Paradigm to Slash Token Consumption and Cut Data Center Emissions by up to 87%

AI can deliver 5x--12x faster vector indexing and up to 57% lower token usage, as the company proves that the most effective path to AI efficiency runs through the data layer, not the GPU. WILMINGTON, ...

Agentic workflows are making distributed, always-on databases nonnegotiable

Oracle tackles database infrastructure with its Globally Distributed AI Database, aiming to ensure zero data loss for mission ...

Scientel Releases Mix-Of-Vendor GPU support For AMD, Intel, Nvidia in Single Large Learning Model (LLM) system

Powered by Gensonix AI DB, Scientel ‘s MOV-LLM solution supports GPUs from AMD, Intel and Nvidia in a single LLM system ...
eWeek

Dell’s Vrashank Jain on The Data Problem That Could Break Your AI

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they ...

Databricks research shows multi-step agents consistently outperform single-turn RAG when answers span databases and documents

Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with ...
InfoWorld

Addressing the challenges of unstructured data governance for AI

As technology and regulations evolve, enterprises need to address data governance throughout pipelines, models, and AI agents ...
The Edge Singapore

Why agentic AI push hinges on data readiness, not model power

Oracle’s approach to bring AI to data (instead of the other way round) is being tested by SMRT, where safety demands ...