Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...

Sudhir Kumar Rai, Director of Data Science at Trellix, drives responsible generative AI innovation for enterprise systems, ...

Embedded World 2026 showed that edge AI is no longer an emerging trend, but is now the industry’s centre of gravity.

Thank you, Sylvie. 2025 was a defining year for One Stop Systems, Inc. and reflects the successful execution of a multiyear strategy to reposition the company around high-performance, ruggedized ...

Two parallel experiments in protein self-assembly produced strikingly different results, demonstrating that protein designers ...

A new academic study argues that the structural reliance of artificial intelligence (AI) systems on classification models creates significant challenges when AI systems attempt to represent fluid and ...

Cross-functional teams can help manufacturers break down silos and overcome the hurdles that prevent real-time operational visibility.

Explainability tools are commonly used in AI development to provide visibility into how models interpret data. In healthcare machine learning systems, explainability techniques may highlight factors ...

Humanoid robots are rapidly improving in motion fluidity, making them more human-like and suitable for complex tasks.

The computing community has largely treated AI hallucinations as a model problem. The default path to reliability has been model improvement: better training data, larger context windows, retrieval ...

What’s the first thing you think of when you hear about ai security threats and vulnerabilities? If you’re like most people, your mind probably jumps to Large Language Model (LLM) ...