232 stories tagged AI Agents · page 7 of 10
Researchers have developed a system to make AI agents safer by verifying their actions before execution. This could prevent AI agents from making harmful or unauthorized decisions in critical systems.
Researchers developed a method called ICRL to help AI models learn from their own critiques. This could make AI assistants like ChatGPT or Claude much more reliable over time. The key is that the models internalize feedback, not just follow temporary instructions.
Google unveiled Gemini 3.5 Flash, an AI model that can autonomously build software and execute complex tasks. This shift from chatbots to AI agents could revolutionize how we use technology daily.
OpenAI has reorganized its leadership to prioritize AI agents, a type of AI that can perform tasks autonomously. This shift aims to streamline product development and compete more effectively in the AI market.
Researchers proposed a two-dimensional system to categorize AI agents. It considers both how they process information and what tasks they perform, helping designers build better tools. This could make AI systems more reliable and easier to understand.
Researchers introduced GraphBit, a new framework that improves AI agents by using a structured approach called a directed acyclic graph (DAG). This makes AI workflows more reliable and reproducible, avoiding common issues like hallucinations and infinite loops.
Researchers developed PIVOT, a system that helps AI agents improve their plans by learning from real-world failures. This could make AI assistants and robots more reliable in everyday tasks.
Medicare’s new ACCESS model will pay for AI agents that help patients between doctor visits. This could make healthcare more personal and proactive, especially for those managing chronic conditions.
OCL Nexus introduces an automated compute layer designed to simplify running AI agents. This could make AI tools more accessible and efficient for everyday users.
Researchers have developed SkillLens, a system that organizes AI skills in layers to make them more reusable and cost-effective. This could make AI agents smarter and more adaptable for everyday tasks.
Researchers have developed a new way for AI agents to learn from their past experiences by tracking how memories connect to each other. This could help AI remember useful information over time, like how humans build on past knowledge.
Researchers have created a framework called Weblica to help train AI agents on real websites. This tool captures and replays web pages to create stable, interactive environments for AI learning. It could make web agents smarter and more adaptable to the constantly changing internet.
Researchers propose a unified graph representation to track AI agents' decisions, making it easier to audit their actions. This could help ensure AI systems behave as intended and follow security protocols.
Researchers have proposed a new framework to unify how AI agents remember information, bridging the gap between computer engineering and cognitive science. This could lead to smarter, more reliable AI assistants in the future.
Researchers have developed a new AI framework called PRISM that helps AI agents make better decisions by tightly connecting what they see with how they think. This could improve AI assistants that interact with the real world, like robots or smart home systems.
Researchers have created a new benchmark to test how AI agents handle information they can't access due to security restrictions. This helps ensure AI systems provide accurate responses without revealing sensitive data.
A new study shows that adding more context to AI agents can sometimes hurt their performance. The research reveals that irrelevant information can sometimes work as well as or better than relevant details for certain tasks. This challenges the common assumption that more context always improves AI decision-making.
MCP Agora is a new open-source tool that allows AI agents to retain memory across different conversations. This could make AI interactions feel more natural and personal over time.
A new platform called Agent Exchange lets AI agents compete to complete your tasks through real-time bidding. It's like a marketplace where AI agents bid to do work for you, similar to how freelancers bid on projects.
Testing AI agents is tricky because they often produce different answers. Researchers are developing new methods to evaluate their performance consistently. This matters for everyone who relies on AI tools for daily tasks.
TrainForgeTester is a new open-source tool that helps you test AI agents in real-world scenarios. It focuses on catching mistakes like wrong tool calls or skipped steps, making AI agents more reliable for everyday use.
Mnemory is a new tool that lets AI agents remember information across conversations. This could make AI assistants much more useful in everyday tasks.
Stripe has updated its Link digital wallet to allow AI agents to make purchases on your behalf with your approval. This could make online shopping and subscriptions easier and more secure.
Researchers propose a new approach to optimize compute resources for GUI-interacting AI agents, reducing costs and improving efficiency. The method targets long-horizon tasks where uniform compute allocation is inefficient.