Business is moving faster than ever. Customers expect instant updates. Supply chains shift by the minute. Competitors launch and adapt in real time. Yet many companies still operate on delayed cycles.

Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

If models get better at navigating human emotions, those manipulations could become more effective — but much of the issue comes down to the fundamental biases of model training.

Meta's $14 billion investment in Scale AI set off a flurry of dealmaking in the AI data industry, as Meta's rivals cut ties with Scale for other data companies ...

GitHub and Microsoft, GitHub's corporate parent, are joining the steering committee for MCP, Anthropic’s standard for connecting AI models to the systems where data resides.

The primary differences between these data management solutions lie in their data structure, schema approach, use cases, and cost. Data Lakes: Store raw data in its native format and use a ...

A new crowd-trained way to develop LLMs over the internet could shake up the AI industry with a giant 100 billion-parameter model later this year.

With the continuous improvement of the informatization level of the power system, the security of the power data transmission network is crucial. This article explores the application of data mining ...

Understanding the differences between data mesh, data fabric, and data virtualization can help organizations turn scattered data into a strategic advantage.

As artificial intelligence (AI) continues to expand at a fast pace, data centers needs to evolve to handle its demands. AI data centers are designed to support complex AI workloads, while traditional ...

Data management has been changing rapidly in the era of generative and agentic AI, with even more change from the vendors covered here likely in store in 2025.