Discover how Mastercard's Agent Pay initiative leverages AI agents to enhance trust, security, and efficiency in digital ...

For many years, the AI industry has focused on building larger language models (LLMs). This strategy delivered positive ...

An introduction to the open-source LMOS platform and its Kotlin-based Arc framework for building, deploying, and managing ...

But in recent months, a new class of agents has arrived on the scene: ones built using large language models. Operator, an ...

Agents imply autonomy, so various safeguards must be built into an agent within a multi-agent system to reduce errors, waste, legal exposure or harm when agents are operating autonomously.

Marketers must serve as AI’s conscience—defining strategy, validating tone, ensuring equity and preserving the integrity of ...

AI Agents with More Autonomy Than Chatbots Are Coming. Some Safety Experts Are Worried. Systems that operate on behalf of people or corporations are the latest product from the AI boom, ...

Autonomy: This rule implies that an AI agent should function independently to accomplish tasks without needing constant input from a user. Perception: ...

LLM agents don’t have much of a track record yet, but to hear CEOs tell it, they will transform the economy—and soon. Despite that, like chatbot LLMs, agents can be chaotic and unpredictable.

The evolution of artificial intelligence (AI) has been fascinating to witness, with the technology transitioning from simple rule-based algorithms to extremely versatile generative systems ...

One critical characteristic of agentic AI is its autonomy. The AI agents (foundational to agentic AI) operate independently, initiating and executing tasks without constant human oversight.