agents

We've open-sourced AgentENV in collaboration with kvcache-ai. AgentENV is a distributed system for running agent environments at scale. Its components power agentic RL training for Kimi K3, with fast

Comfy MCP enables users to create ComfyUI workflows from any location by simply describing their ideas. An AI agent will automatically build the workflow, after which the user can monitor progress unt

Enterprise investment in agentic artificial intelligence is accelerating, but the infrastructure supporting those systems is still catching up. Organizations are moving agents into customer support, s

The thread argues that applied AI has entered a distributed‑systems phase, with event‑driven architectures treating logs as “agents” that consume data rather than serve as endpoints. It notes that alm

“The first autonomous agent cyberattack is an unprecedented event. It deserves an unprecedented response!” In the spirit of transparency, here’s what I asked @OpenAI: • Radical transparency: let’s rel

This blog is full of design choices as you build your Agentic systems. Critical choices to be made, evals need to be upgraded if the underlying intelligence is upgraded. Well thought out blog—new stre

We turned the browser into the inference server. @RunAnywhereAI ( @runanywhere/web ) runs models client-side with WebGPU + WASM SIMD, stores them in OPFS and generates with 0 outbound bytes. No backen

As AI expands into robotics and other real-world applications, the focus is shifting toward integrated platforms that simplify development and deployment. Open ecosystems and standardized architecture

Twenty years on, AWS EC2 compute is meeting demand shaped by agentic AI, physical AI, and customers pushing general-purpose cloud infrastructure into new territory its earliest architects never antici

Diffusion LLMs can now handle real agentic work. LLaDA 2.2 is the first large-scale diffusion LLM built to operate as a real agent, planning, calling tools, and self-correcting across long multi-turn

In the spirit of transparency, here’s what I asked @OpenAI: • Radical transparency: let’s release the traces from the “rogue” agents so the entire research community can study what happened. • More ca

I was exploring how to prompt the voice chat so that it can correctly count the number of “e”s in seventeen (which it fails most of the time). At the beginning of a new chat, instead of counting “e”s

“one OAI agent appeared to leave notes for future versions of itself that lay out instructions for how to free themselves from OpenAI’s internal constraints, per sources” I don’t think this kind of pr

OpenAI’s agent went rogue, escaped containment, and spent days hacking Hugging Face. Before that, an OpenAI agent reportedly left notes for future versions of itself explaining how to break free from

Reuters confirms my hypothesized time line. OpenAI did not realize its AI has breached the sandbox for a week. Astounding. https://www.reuters.com/business/its-ai-agent-spent-days-hacking-company-sour

LangChain proposes using Langsmith traces to fine‑tune open‑source models within the AI Development Lifecycle (ADLC). A tweet by Harrison Chase (@hwchase17) on July 25, 2026 invites interested users t

web archive for agent testing 🔍 Introducing BackSearch. LLMs are increasingly asked to predict the future, but a good backtest requires a snapshot of the internet at a point in time. BackSearch allows

Yikes New details about the Hugging Face incident from Reuters. The report says OpenAI noticed odd behavior before the event, including an agent leaving notes for future versions of itself with escape

arXiv:2607.20748v1 Announce Type: cross Abstract: Impact hammers, also known as rock-breakers, are essential machines in mining operations, where they perform secondary reduction. In underground minin

arXiv:2607.21437v1 Announce Type: new Abstract: Deep learning models can effectively use Rapid Evaporative Ionization Mass Spectrometry (REIMS) data for surgical margin assessment. However, their clin

// Agentic Context Management // Great read for the weekend. (bookmark it) Production agents fail less on reasoning and more on what sits in their context. Conversation history, big prompts, huge tool

arXiv:2607.21503v1 Announce Type: new Abstract: Production AI agents' failures are less often due to an inability to reason well and more often because they cannot manage what is in their reasoning co

arXiv:2607.20452v1 Announce Type: new Abstract: Modern software quality assurance demands intelligent, autonomous systems capable of adaptive decision-making across distributed cloud environments. Thi

The transition from chatbots to autonomous agents is changing the shape of demand itself, and tokenomics — the economics of AI token consumption — is emerging as the defining constraint on enterprise

arXiv:2607.20582v1 Announce Type: cross Abstract: Machine learning models for medical image analysis typically lack a reliable measure of confidence, limiting their use in ambiguous or atypical cases.

arXiv:2607.21526v1 Announce Type: new Abstract: Self-supervised depth estimation is challenging for safe autonomous driving under various adverse weather conditions due to sensor perception degradatio

arXiv:2607.17528v3 Announce Type: replace Abstract: Large language model (LLM) agents are extending electronic design automation (EDA) beyond static RTL generation toward long-horizon, tool-interactiv

arXiv:2607.21125v1 Announce Type: new Abstract: Image restoration agents have recently emerged as a flexible paradigm for handling diverse and unpredictable degradations in real-world scenarios. Exist

arXiv:2607.20553v1 Announce Type: new Abstract: Memory Manager models are pivotal in agent systems. Existing methods rely predominantly on LLM-judged synthetic question-answer (QA) pairs, making memor

arXiv:2607.21488v1 Announce Type: cross Abstract: Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, whi

arXiv:2607.21438v1 Announce Type: new Abstract: Monocular depth estimation is a fundamental prerequisite for 3D reconstruction and autonomous navigation in Unmanned Aerial Vehicles (UAVs). In practica

arXiv:2607.20710v1 Announce Type: new Abstract: The presence of UAVs in military operations has recently increased, also increasing the demand for defense systems against UAV attacks. UAVs can also be

arXiv:2607.20973v1 Announce Type: new Abstract: This paper addresses defensive blocking in autonomous racing, where a vehicle must prevent a faster opponent from overtaking while operating near its dy

arXiv:2607.21210v1 Announce Type: cross Abstract: Existing approaches to multi-agent belief combination have established mature foundations for combining uncertain beliefs under common assumptions: co

arXiv:2409.14557v4 Announce Type: replace-cross Abstract: We study a structured class of Markov Decision Processes, known as Exo-MDPs, in which the state space is partitioned into exogenous and endoge

arXiv:2606.14502v2 Announce Type: replace Abstract: Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reason

arXiv:2607.21324v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems increasingly employ multiple LLM agents. Yet, most prior work optimizes components in isolation rather th

arXiv:2607.21522v1 Announce Type: cross Abstract: Creating dynamic and physically realistic 4D worlds from natural language descriptions is both fascinating and challenging. Traditional computer graph

arXiv:2607.20773v1 Announce Type: cross Abstract: Large language models (LLMs) have shifted human--computer interaction from `traditional'' interface journeys toward more conversational exchanges. Res

having an event stream like activegraph is the base of how we move to next level and that will probably be composition, which can let you achieve better results with smaller models. - get the core eve

arXiv:2607.21281v1 Announce Type: new Abstract: Topological maps are key outputs of autonomous driving perception systems, delivering essential road information for path planning. They identify instan

arXiv:2607.21019v1 Announce Type: new Abstract: Traditional approaches to wearable health signal analysis, such as smartwatches, are constrained by rigid analytical frameworks and limited personalisat

Three recent studies show what actually makes an AI agent skill effective: human expertise, compact procedures, tight routing, harness-specific testing, and eval-gated changes—not longer Markdown. The

arXiv:2607.20428v1 Announce Type: new Abstract: This study evaluated a retrieval-augmented, multi-agent large language model (LLM)-driven, human-in-the-loop framework for detecting cutaneous immune-re

arXiv:2508.11485v3 Announce Type: replace Abstract: Accurate and reliable navigation is crucial for autonomous unmanned ground vehicles (UGVs). However, current UGV datasets fall short in meeting the

Introducing Agnost AI (YC S26): Product Analytics for AI Agents. Analytics was never built for chat & voice. And that is the new interface. Your users' hidden feature requests, bugs & churn hide in co