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

For much of the last two years, multi-agent systems have been treated as the natural next step in artificial intelligence. If one large language model can reason, plan, and act, then several working ...

Sabre is using its first CES appearance to showcase a live “agentic” travel demo based on its latest AI tools.  Product ...

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

Nearly every SaaS product is either integrating AI or planning to do so. However, the term “AI” has become so broad that it’s often misunderstood, especially by non-technical founders. Words like ...

The idea of the Instructed Retriever architecture is that it turns these implied conditions into explicit search parameters.

AI agents will reshape 2026: they’ll feed on synthetic/structured data, remake the web, swarm unpredictably, and empower ...

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.

AI agents are the fastest-growing and least-governed class of these machine identities — and they don’t just authenticate, ...

Researchers explored the nuanced dynamics of how people balance their desire to speak out vs their fear of punishment in a ...

For IT and HR teams, SLMs can reduce the burden of repetitive tasks by automating ticket handling, routing, and approvals, ...

AI agents have emerged from the lab, bringing promise and peril. A Carnegie Mellon University researcher explains what's ...