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Notion ships knowledge work AI agents via 5 rebuilds, 100+ tools, and MCP integration after internal infrastructure overhaul.
Import AI 453 examines agent vulnerabilities, MirrorCode tool, and disempowerment strategies for AI systems.
We cap out our World Models coverage with one of the most exciting new approaches - long running, multiplayer, interactive world models built with agents bootstrapped from game engines!
Gradient Labs deploys GPT-4.1 and GPT-5.4 mini/nano agents for automated banking support with low-latency agentic workflows.
Mistral releases Spaces, a CLI tool designed for both human developers and autonomous agents.
Mistral AI shares design philosophy for CLI tools supporting both human users and AI agents, emphasizing unified tooling that improves developer experience.
Agentic AI is an ecosystem where specialized models work together to handle planning, reasoning, retrieval, and safety guardrailing. As these systems scale,... Agentic AI is an ecosystem where specialized models work together to handle planning, reasoning, retrieval, and safety guardrailing. As these systems scale, developers need models that can understand real-world multimodal data, converse naturally with users globally, and operate safely across languages and modalities. At GTC 2026, NVIDIA introduced a new generation of NVIDIA Nemotron models… Source
Mistral open-sources Voxtral, a fast, adaptable TTS model for voice agents with real-time synthesis.
OpenAI uses chain-of-thought monitoring to detect misalignment risks in internal coding agents via real-world deployment analysis.
While consumer AI offers powerful capabilities, workplace tools often suffer from disjointed data and limited context. Built with LangChain, the NVIDIA AI-Q... While consumer AI offers powerful capabilities, workplace tools often suffer from disjointed data and limited context. Built with LangChain, the NVIDIA AI-Q blueprint is an open source template that bridges this gap. LangChain recently introduced an enterprise agent platform built with NVIDIA AI to support scalable, production-ready agent development. This tutorial, available as an NVIDIA… Source
AI-native services are exposing a new bottleneck in AI infrastructure: As millions of users, agents, and devices demand access to intelligence, the challenge is... AI-native services are exposing a new bottleneck in AI infrastructure: As millions of users, agents, and devices demand access to intelligence, the challenge is shifting from peak training throughput to delivering deterministic inference at scale—predictable latency, jitter, and sustainable token economics. NVIDIA announced at GTC 2026 that telcos and distributed cloud providers are… Source
AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward... AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward trillions of parameters. These systems rely on agentic long‑term memory for context that persists across turns, tools, and sessions so agents can build on prior reasoning instead of starting from scratch on every request. Source
Autonomous AI agents are driving the next wave of AI innovation. These agents must often manage long-running tasks that use multiple communication channels and... Autonomous AI agents are driving the next wave of AI innovation. These agents must often manage long-running tasks that use multiple communication channels and background subprocesses simultaneously to explore options, test solutions, and generate optimal results. This places extreme demands on local compute. NVIDIA DGX Spark provides the performance necessary for autonomous agents to execute… Source
AI has evolved from assistants following your directions to agents that act independently. Called claws, these agents can take a goal, figure out how to achieve... AI has evolved from assistants following your directions to agents that act independently. Called claws, these agents can take a goal, figure out how to achieve it, and execute indefinitely—while leaving you out of the loop. The more capable claws become, the harder they are to trust. And their self-evolving autonomy changes everything about the environment in which they operate. Source
ChatGPT agents defend against prompt injection via action constraints and sensitive data protection in agent workflows.
NVIDIA ACE is a suite of technologies for building AI agents for gaming. ACE provides ready-to-integrate cloud and on-device AI models for every part of in-game... NVIDIA ACE is a suite of technologies for building AI agents for gaming. ACE provides ready-to-integrate cloud and on-device AI models for every part of in-game characters, from speech to intelligence to animation. To run these models alongside the game engine efficiently, the NVIDIA In-Game Inferencing (NVIGI) SDK includes a set of performant libraries that developers can integrate into C++… Source
Alibaba has introduced the new open source Qwen3.5 series built for native multimodal agents. The first model in this series is a ~400B parameter native... Alibaba has introduced the new open source Qwen3.5 series built for native multimodal agents. The first model in this series is a ~400B parameter native vision-language model (VLM) with reasoning built with a hybrid architecture of mixture of experts (MoE) and Gated Delta Networks. Qwen3.5 can understand and navigate user interfaces, which improves on the previous generation of VLMs. Qwen3.5… Source
OpenAI and Amazon expand partnership: Frontier platform, custom models, and enterprise agents on AWS.
Amazon Bedrock adds stateful runtime for persistent orchestration and memory in multi-step AI agent workflows.
DraftNEPABench benchmark evaluates AI coding agents on federal permitting; shows 15% NEPA drafting time reduction potential.
OpenAI launches Frontier Alliance Partners program to help enterprises deploy AI agents from pilots to production with secure, scalable infrastructure.
As global AI adoption accelerates, developers face a growing challenge: delivering large language model (LLM) performance that meets real-world latency and cost... As global AI adoption accelerates, developers face a growing challenge: delivering large language model (LLM) performance that meets real-world latency and cost requirements. Running models with tens of billions of parameters in production, especially for conversational or voice-based AI agents, demands high throughput, low latency, and predictable service-level performance. Source
OpenAI and Paradigm introduce EVMbench, a benchmark for evaluating AI agents on smart contract vulnerability detection and exploitation.
Anthropic releases Claude Sonnet 4.6 with frontier performance in coding, agents, and professional applications.
Anthropic partners with Infosys to develop AI agents for telecommunications and regulated industries.
OpenAI Frontier is enterprise platform for building, deploying, and managing AI agents with governance and context management.
OpenAI and Snowflake announce $200M partnership embedding frontier models and agents directly in Snowflake's data platform.