Abstract: Lifelong learning, also known as continual or incremental learning, is a crucial component for advancing Artificial General Intelligence (AGI) by enabling systems to continuously adapt in ...

This paper introduces OMAR: One Model, All Roles, a reinforcement learning framework that enables AI to develop social intelligence through multi-turn, multi-agent conversational self-play. Unlike ...

OpenAI has launched a new product to help enterprises navigate the world of AI agents, focusing on agent management as critical infrastructure for enterprise AI adoption. On Thursday, AI giant OpenAI ...

On Thursday, Anthropic released the latest version of Opus — its most advanced model and a particularly important model for Claude Code. Opus 4.5 was only released last November, and with 4.6, the ...

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Researchers have developed a new artificial intelligence approach that exposes critical weaknesses in multi-agent reinforcement learning systems, enabling stronger coordinated attacks with broad ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines. By Daniel Fusch Neel Somani, a ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

For all their superhuman power, today’s AI models suffer from a surprisingly human flaw: They forget. Give an AI assistant a sprawling conversation, a multi-step reasoning task or a project spanning ...

As health system executives explore the potential benefits of agentic AI, many see call centers as low hanging fruit to test out conversational AI. Calls centers are costly to run, are often short on ...