A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their ...

Duke University engineers are using artificial intelligence to do something scientists have chased for centuries; turn messy, ...

Here is the AI research roadmap for 2026: how agents that learn, self-correct, and simulate the real world will redefine ...

TomTom launches Orbis Lane Model Maps for fresh, lane-level precision at scale ...

A research team affiliated with UNIST has unveiled a novel AI system capable of grading and providing detailed feedback on ...

Pharaoh saw two dreams, which Joseph recognized as structurally equivalent and carrying the same message. A stable system ...

The third and final portion of Bryant’s exclusive video interview with PharmTech ® deals with the processes known as human-in ...

Traditional cloud architectures are buckling under the weight of generative AI. To move from pilots to production, ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

The year 2025 marked a major leap for AI in health care, with breakthroughs in drug discovery, diagnostics, genomics and ...

Live AI interpreters must grasp meaning, tone, and intent even when sentences unfold slowly or indirectly. Languages differ ...