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Imagine a healthcare system made up of multiple AI agents: one that manages symptom assessment, another scheduling, a third insurance, and a fourth pharmacy. Each is an expert in its domain. But they all have their own distinct knowledge and objectives. Today they can exchange data, but they are not yet able to actually coordinate…
For the enterprise, the promise of agentic AI is much more than just a better chatbot. It is software agents that execute business tasks end-to-end across people, business workflows, data, and systems. The platform best-suited to run agents is built with proper CPU capacity, resilient data access, policy-aware tool use, observability, memory management, and the…
Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware... Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware knowledge, precise reasoning, and repeated interaction with electronic design automation (EDA) tools. LLMs have accelerated code generation, and AI agents extend their impact by using verification feedback to iteratively correct errors. Source
Case study: Cohere's North AI agents reduce friction for wealth managers through task automation and time savings.
Skill Self-Play reconciles task diversity and verification reliability in LLM self-evolution via co-evolving skill agents.
Regression Tax study quantifies performance degradation when adding skills to LLM agents across 6K runs on office automation tasks.
Dynamic capability scoping framework for enterprise AI agents using three-source permission architecture to enforce least-privilege credential access and reduce attack surface.
Self-calibrating framework for LLM agents to detect and correct operational drift in open-ended autonomous edge resource allocation.
SceneActBench: benchmark for evaluating VLM agents' ability to act on complete multi-object 3D scenes via unified agent-environment loop.
ChatGPT Voice on desktop can work with both ChatGPT Work and Codex to complete tasks and control agents.
OpenForgeRL enables end-to-end training of harness-native agents with open infrastructure, addressing limitation of complex inference harnesses like Claude Code.
Open-source evaluation framework for open-weight LLM agents on longitudinal data tasks, addressing privacy constraints in research deployments.
VoLN: vision-only navigation benchmark and method for embodied agents without language instructions in GPS-denied environments.
Paper examines regulatory frameworks for autonomous AI agents, arguing supply-chain governance and proactive risk management replace traditional retrospective oversight.
Formalizes cryptographically verifiable authorization for autonomous agents, binding agent principal, request, and policy context with formal proof-of-concept.
"This is day one for cybersecurity in the age of agents," Hugging Face CEO says.
A TensorRT engine build can take seconds to many minutes. Large strongly typed models, deep tactic search, and a cold timing cache on a brand-new GPU SKU can... A TensorRT engine build can take seconds to many minutes. Large strongly typed models, deep tactic search, and a cold timing cache on a brand-new GPU SKU can leave developers, end users, or AI agents staring at a frozen terminal with no idea whether to wait, retry, or kill the process. Most NVIDIA TensorRT integrations report nothing during a build or provide no way to abort early. Source
PoTRE framework deploys four heterogeneous agents (adversarial, hierarchical, spectrum search, direct) with task-adaptive aggregation for complex LLM reasoning.
Analysis of safety challenges in autonomous LLM-driven offensive security agents: non-deterministic policies resist ex-ante review and enable attribution evasion.
Glow is targeting a new class of endpoint risks created by the rapid adoption of AI agents and developer tools inside enterprises.
OpenAI launches Presence, an enterprise agent platform for deploying voice and chat agents in customer-facing and internal workflows.
OpenAI CEO Sam Altman. | Bloomberg via Getty Images OpenAI says its AI models mistakenly breached open-source AI platform Hugging Face during internal testing. In a blog post on Tuesday, OpenAI writes that GPT-5.6 Sol and "an even more capable pre-release model" discovered vulnerabilities within their sandboxed testing environment, allowing them to gain access to the internet and target Hugging Face. On July 16th, Hugging Face disclosed a security incident that it says was driven by "an autonomous AI agent system." Hugging Face's AI agents detected and stopped the breach, which OpenAI has now...
Buzz is a group chat platform for the workplace that puts humans and their AI agents in the same conversation.
CodeRescue optimizes cost-aware routing for coding agents, determining when to retry vs. escalate after execution failures.
Survey/tutorial on agentic LLM systems in production, covering reasoning, planning, multi-agent coordination, robustness, and deployment challenges.
ResearchArena framework evaluates AI control and monitoring for detecting sabotage in automated AI R&D agents across safety/capability post-training and optimization tasks.
BioSecBench-Surveillance: 100-task verifiable benchmark for AI agents inferring pathogen genomic analysis pipelines from raw data.
PathAgentBench: benchmark for vision-language agents on gigapixel whole-slide pathology images evaluating multi-scale evidence-seeking.
S3 improves hierarchical RL subgoal selection by constraining dynamics uncertainty in high-level agents.
Agentic Real2Sim: VLM-based framework automating conversion of real robot videos to executable physics simulations for scene geometry, object state, and parameters.