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

An unsecured database exposed 4.3 billion LinkedIn-derived records, enabling large-scale phishing and identity-based attacks.

In the MCP era, there is no "expected behavior" to deviate from. Every workflow is unique. Every sequence of tool calls is ...

ManureDB, a publicly available database, houses U.S. manure and organic amendment data from multiple laboratory sources. The ...

Moreover, LLMs are inference machines that rapidly adapt to infer sensitive details, such as your political leanings, health ...

Oracle has said it might consider letting customers bring their own hardware to Oracle data centers. During last week's ...

Realsee3D is a large-scale multi-view RGB-D dataset designed to advance research in indoor 3D perception, reconstruction, and ...

1. Risk: AI Monoculture (Shared Blind Spots). This is the most critical and overlooked systemic vulnerability. Building your ...

Invent 2025 signals the shift from AI experimentation to AI architecture. Seven insights for business leaders navigating ...

The A to Z of over 100 electric vehicles on the market in terms of price, range and the EV's ability to provide external ...

When we prompted multiple AI models on why they lie, the first thing they wanted to do was differentiate lies from ...

Bharat Kumar Dokka spearheaded a comprehensive enterprise-wide SQL Server migration initiative across a major client's Administration Infrastructure project, successfully modernizing multiple ...