How Jaiveer Singh Is Helping Robots — and Developers — Move Faster
When Jaiveer Singh talks about robots, he doesn’t begin with spectacle. He begins with infrastructure: the boards inside machines, the software that lets developers see through a robot’s cameras and the engineering required before a robot can leave a demo floor to do something useful. As a robotics ...
Define a tool once as an MCP server and any MCP-compatible client, any model, any framework, can discover and call it with zero custom integration code per model.
Into the Omniverse: Three Workflows for Improving Vision AI Agent Accuracy With Synthetic Data and Fine-Tuning
Editor’s note: This post is part of Into the Omniverse, a series focused on how developers, 3D practitioners, and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Vision AI agents are becoming a practical way to automatically turn video data from t...
Context Window Management for Long-Running Agents: Strategies and Tradeoffs
In this article, you will learn five practical strategies for managing context windows in long-running AI agent applications, along with the key tradeoffs each approach...
In late 2025, the security community stopped treating indirect prompt injection as a theoretical risk. It had spent two years as a tidy lab demonstration; then production systems started getting hit. The OWASP Top 10 for LLM applications now ranks prompt injection as the number-one risk, NIST has ca...
Can AI Draw Science? A Benchmark for Evaluating Scientific Figure Generation by Text-to-Image and Multimodal Models
arXiv:2606.28406v1 Announce Type: new
Abstract: Text-to-image and multimodal generative models are increasingly used to produce scientific figures such as mechanism diagrams, experimental-design schematics, conceptual frameworks, and graphical abstracts. Yet existing image-generation benchmarks (e....
On the Necessity of a Liquid Substrate for Mesh Intelligence
arXiv:2606.28413v1 Announce Type: new
Abstract: A mesh of sovereign agents has no center: no shared clock, no shared model, and no coordinator to gather data or retrain. Its competence rests on each agent folding the projections its peers emit into a single internal state, online, from observations...
Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy
arXiv:2606.28433v1 Announce Type: new
Abstract: One goal in reinforcement learning (RL) research is to understand general-purpose sequential decision-making, using benchmark simulators as a proxy for learning in deployment settings. When running experiments, however, the goal of achieving high perf...
Learning to Distributedly Estimate under Partially Known Dynamics: A Covariance-Agnostic Neural Kalman Consensus Filter
arXiv:2606.28441v1 Announce Type: new
Abstract: Online latent state estimation constitutes a fundamental challenge within the artificial intelligence field, serving as a foundational tool for diverse applications, including sequential decision making, anomaly and change-point detection. In this pap...
Recursive Self-Evolving Agents via Held-Out Selection
arXiv:2606.28374v1 Announce Type: new
Abstract: LLM agents are increasingly improved without weight updates by evolving a natural-language artifact, such as reflections, workflows, playbooks, cheatsheets, or optimized prompts, that conditions a frozen policy. Such methods are typically reported as ...
Data and Evaluation Closed-Loop for Model Capability Enhancement
arXiv:2606.28471v1 Announce Type: new
Abstract: Model capability is the central variable in LLM pre-training, yet is never observed directly: data shapes it prospectively, while evaluation reveals it only retrospectively, compressing samples, prompts, decoding, and scoring rules into one noisy scor...
GPTNT: Benchmarking Real-Time Collaboration Between Multimodal Agents on Keep Talking And Nobody Explodes
arXiv:2606.28514v1 Announce Type: new
Abstract: Multimodal models are increasingly deployed to solve tasks collaboratively with humans or other artificial agents. Existing benchmarks show that these models possess many of the required component capabilities, but the conditions that coincide in coll...
IMCBench: A benchmark for multimodal LLMs in Image-grounded Medical Conversations
arXiv:2606.28556v1 Announce Type: new
Abstract: Recent advances in large language models and vision-language models have enabled reasoning over multimodal data, offering opportunities for clinical applications such as decision support and triaging. However, existing medical AI benchmarks are fragme...
Search for Truth from Reasoning: A Dynamic Representation Editing Framework for Steering LLM Trajectories
arXiv:2606.28589v1 Announce Type: new
Abstract: Current approaches to enhance Large Language Model (LLM) reasoning, such as Chain-of-Thought and "Wait" prompts, primarily encourage models to think more, yet often fail to guide them toward Truth. While Representation Editing (RepE) offers a intrinsi...
OpenAI engineers used large-scale core dump analysis to debug rare infrastructure crashes, uncovering both a hardware fault and a long-standing software bug.
OpenClaw Releases iOS and Android Companion Node Apps That Connect a Phone to a Self-Hosted AI Agent Gateway
OpenClaw's iOS and Android apps are companion nodes, not standalone chatbots. Each phone pairs to a self-hosted Gateway over WebSocket. This adds device hardware — camera, location, voice, and Canvas — to a local-first AI agent. Here is the architecture, the capabilities, and the trade-offs for buil...
Millions of exploding stars could soon reveal dark energy's secrets
A new AI-powered framework could transform how astronomers measure the expansion of the Universe. By analyzing images of Type Ia supernovae and modeling their environments in unprecedented detail, researchers can estimate cosmic distances with near-spectroscopic accuracy. The technique is designed f...