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Vercel Releases Eve: An Open-Source AI Agent Framework Where Each Agent is a Directory of Files Mapped to Capabilities

Vercel has released eve, an open-source framework for building, running, and scaling agents. The project is published as the npm package eve, licensed under Apache-2.0. Building an agent should mean defining what it does. It should not mean assembling all the plumbing that an agent needs to run in production. eve is the framework Vercel […]

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MiniMax Sparse Attention (MSA): a Two-Branch Block-Sparse Attention Trained on a 109B-Parameter MoE With a 3T-Token Budget

MiniMax released MSA (MiniMax Sparse Attention), a sparse attention method built directly on Grouped Query Attention (GQA). It targets one bottleneck: the quadratic cost of softmax attention at long context. The MiniMax research team tested it inside a 109B-parameter Mixture-of-Experts model trained with native multimodal data. They also open-sourced an inference kernel and shipped a

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OpenAI’s Deployment Simulation Extends Pre-Deployment Risk Assessment to Agentic Coding Through Simulated Tool Calls

OpenAI published a new pre-deployment safety method called Deployment Simulation. The idea is direct. Before a model ships, simulate its deployment first. Replay past conversations through the new candidate model. Then study how it behaves in realistic contexts. OpenAI already uses insights from the method during model development. It has informed mitigations and deployment decisions,

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How to Build Memory-Efficient Transformers with xFormers Using Packed Sequences, GQA, ALiBi, SwiGLU, and Causal Attention

In this tutorial, we implement xFormers: a practical toolkit for building fast, memory-efficient Transformer models on GPUs. We begin by validating memory-efficient attention against a standard attention implementation, then compare their speed and memory consumption across different sequence lengths. We then examine causal masking, packed variable-length sequences, grouped-query attention, and custom ALiBi positional biases. Finally,

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Meet Qwen-RobotSuite: Three Embodied AI Models for VLA Manipulation, Video World Modeling, and Navigation

The Qwen team has released three embodied AI models, grouped as Qwen-Robot-Suite. The three are Qwen-RobotManip, Qwen-RobotWorld, and Qwen-RobotNav. Each is built on a Qwen vision-language backbone and targets a different robotics problem. Qwen-RobotManip is a Vision-Language-Action model for manipulation, built on Qwen3.5-4B. Qwen-RobotWorld is a language-conditioned video world model with a 60-layer MMDiT and

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Hermes Agent Adds Asynchronous Subagents, So Delegated Work No Longer Blocks the Parent Chat

Nous Research has shipped a change to Hermes Agent. Its delegate tool can now run subagents asynchronously. Per the announcement, delegated work no longer blocks the parent chat. Hermes Agent is an open-source personal agent from Nous Research. A parent agent can spawn child agents, called subagents, to fan out work. Until now, that delegation

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Meet Atoms: A Vibe Coding Tool That Uses AI Agents to Build, Deploy, and Market Your App (No Code)

The concept of vibe coding is interesting; you don’t need to be a developer or software engineer to build your own applications. You can describe your idea to an AI in plain language, and it will build, edit, and refine your applications so you don’t have to write code line by line. It sounds simple

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Google Cloud Introduces Open Knowledge Format (OKF): A Vendor-Neutral Markdown Spec for Giving AI Agents Curated Context

Foundation models keep getting stronger, yet they still stall on the same thing: context. A model can write code or analyze a dataset, but only with the right internal knowledge. That knowledge includes table schemas, metric definitions, runbooks, join paths and it lives scattered across catalogs, wikis, and a few senior engineers’ heads. Google Cloud

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How to Build a Parsing Pipeline with Docling Parse for Layout-Aware Document Intelligence

In this tutorial, we build a workflow for using Docling Parse to analyze PDF documents at a detailed structural level. We start by preparing a stable Python environment, handling common Colab dependency issues, and generating a custom multi-page PDF with text, columns, table-like content, vector shapes, and an embedded image. We then use Docling Parse

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Sakana AI Commercializes AB-MCTS in Sakana Marlin, an Enterprise Agent Generating Up to 100-Page Research Reports With Slides

Tokyo-based Sakana AI shipped its first commercial product ‘Sakana Marlin’ this week. Sakana team positions it as a Virtual CSO (Chief Strategy Officer). It is a B2B autonomous research agent built for enterprises. Marlin does not answer in seconds like a chatbot. You give it one research topic. It then runs autonomously for up to

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