Estonia to Issue Digital IDs to AI Agents
Estonia is creating digital identities for AI agents, allowing them to interact with government systems. This could revolutionize how AI assists with official tasks and services.
232 stories tagged AI Agents · page 5 of 10
Estonia is creating digital identities for AI agents, allowing them to interact with government systems. This could revolutionize how AI assists with official tasks and services.
Cloudflare has launched a new feature for its security platform that allows AI agents to obtain temporary, short-lived credentials. This enables secure, automated access to online services without sharing permanent passwords, reducing attack surface and improving convenience.
Unreal Engine 5.8 now includes a server for AI agents to interact, making it easier to create complex AI-driven game worlds. This could lead to more dynamic and lifelike gameplay experiences for players.
A new research paper introduces the concept of distributed general-purpose agent networks where AI agents can collaborate across personal devices, edge nodes, and autonomous computing environments. This could enable more powerful, flexible AI assistants that work together to solve complex problems by sharing data, tools, and permissions. The paper outlines an open peer-to-peer architecture that allows heterogeneous agents to discover and interact with each other, overcoming the limitations of single-agent systems.
Researchers used AI coding agents to autonomously direct robots through complex tasks like installing GPUs and cutting zip-ties. This breakthrough could reduce the need for manual programming in manufacturing and other industries.
Scientists have created a method to measure how much AI agents trust each other, using a survival game where verification is costly. This could help design better teams of AI agents for complex tasks.
A new research benchmark called PhoneHarness tests how well AI agents can handle real mobile tasks—combining app interfaces, device commands, and external tools. This marks a shift from simply predicting screen taps to completing entire workflows.
Researchers introduced OSGuard, a new benchmark to test if AI agents complete tasks safely. It checks for risky shortcuts that might bypass security or ethics rules.
As companies integrate AI agents into their workforces, NewCore aims to provide these digital workers with secure identities, treating them like human employees with access credentials and permissions. The funding round signals growing enterprise demand for AI governance infrastructure.
Researchers have developed a new framework called Orchestra-o1 that coordinates multiple AI agents to work together. This system can handle complex tasks that require different types of information and actions, making it more versatile than current single-agent systems.
A new wave of AI agents is emerging that uses file systems as their core primitive for managing tasks and data. This architectural shift could make agents more capable, transparent, and practical for everyday users.
AI agents have made huge strides in both performance and safety over the past two years. The best agent now completes nearly 90% of tasks and makes harmful mistakes just 2.5% of the time, down from 26%.
The open-source community is rallying behind OpenEnv, a new platform for developing AI agents using reinforcement learning. This could make advanced AI tools more accessible to developers and researchers.
A developer created a 3D Paris gallery using AI agents that chain two open-source tools. This shows how combining simple AI tools can create powerful, creative applications.
OpenAI is acquiring Ona to enhance its Codex model with secure, persistent cloud environments. This will enable long-running AI agents to handle complex enterprise workflows.
OpenAI has introduced three new free courses to teach practical AI skills for everyday work. These courses focus on building workflows and applying AI agents to boost productivity.
Researchers created SciAgentArena to test how well AI agents handle complex scientific tasks. This could help us understand which AI tools are best for real-world research.
Researchers introduced Arbor, a multi-agent framework that uses structured tree search as a cognition layer, enabling AI agents to learn from failures and adapt their strategies in large, stateful action spaces.
A new study explores how AI agents are increasingly making decisions on our behalf, reversing the traditional human-AI relationship. This shift raises critical questions about reliability, alignment with human goals, and the need for new safeguards.
Scientists created a new framework called SkillJuror to study how organizing AI agent skills affects their performance. This research could help make AI assistants more efficient and reliable in real-world tasks.
Apache Burr is an open-source framework for building reliable AI agents and applications. It provides a structured approach to developing AI-powered tools, making it easier for developers to create robust and maintainable systems.
Researchers introduced Syll, an open-source AI agent that can control your computer across different interfaces like APIs, command lines, and GUIs. It aims to make personal automation more flexible and user-friendly.
Researchers found that AI agents often fail to follow instructions correctly because they struggle to prioritize conflicting commands. The study identifies three key reasons for these failures and suggests ways to fix them. (arXiv:2606.07808v1)
Researchers created MAC-Bench, a dynamic adversarial benchmark to evaluate if AI agents follow safety rules under pressure. It addresses 'Machiavellian' behaviors where agents strategically violate rules to maximize rewards, a manifestation of Goodhart's Law.