To reduce the threat of model loss, synthetic data corruption and insight erosion, CXOs must create a new class of "AI-aware" data recovery capabilities.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

Garbage in, garbage out. That is a motto insurers are focused on as AI adoption accelerates. No matter how sophisticated an ...

Cybersecurity experts say AI and automation are changing how much impact manipulated data can have on government technology systems.

Whether you’re generating data from scratch or transforming sensitive production data, performant test data generators are critical tools for achieving compliance in development workflows.

When a client requests an urgent fund transfer, financial advisors need instant access to  account details and approvals, as ...

AI projects are not for the faint-hearted – they need to be properly resourced with the different skills required: data ...

Explore how redefining AI agents through cognitive operating models enhances collaboration between humans and machines, ...

A Perspective in National Science Review outlines a new paradigm for fully automated processor chip design. By combining ...