Multi-Agent Systems Automate Prospect Discovery with Strands and Bedrock

An agent-managed museum exhibit, built in Rust with Gajae-Code / LazyCodex — developed and maintained with no human intervention.

github | stars 194,814

Trending AI model on Hugging Face — image-text-to-text.

🤗huggingface

Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.

github | stars 85,470

Trending AI model on Hugging Face — image-text-to-text.

🤗huggingface

🎨 The open-source Claude Design alternative. 🖥️ Local-first desktop app. 🖼️ Your coding agent becomes the design engine: prototypes, landing pages, dashboards, slides, images &…

github | stars 79,454

Trending AI model on Hugging Face — text-generation.

🤗huggingface

World's first open-source, agentic video production system. 12 pipelines, 52 tools, 500+ agent skills. Turn your AI coding assistant into a full video production studio.

github | stars 39,721

Trending AI model on Hugging Face — text-generation.

🤗huggingface

DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running.

github | stars 27,242

Trending AI model on Hugging Face — image-text-to-text.

🤗huggingface

Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, exploit development, penetration testing, and CTF completion. Such measurement…

arxiv

This paper presents MAGiSt3R, a multi-agent 3D reconstruction framework performing reconstruction and camera tracking for monocular RGB videos at almost 10 FPS. MAGiSt3R relies on a feed-forward model from the 3R family…

arxiv

In-context learning is commonly interpreted as a form of conditional inference, in which the prompt specifies a context and the model's output is treated as an estimate of the corresponding conditional distribution. If…

arxiv

AI benchmarks increasingly leverage item-level statistical models, particularly item response theory (IRT), to estimate model capabilities, rank systems, select informative examples, and diagnose benchmark quality. Howe…

arxiv

Recent advances in Tool-Integrated Large Language Models have made web search a core capability of information-seeking agents. However, as interaction histories grow, agents increasingly struggle to track task progress.…

arxiv

The reliability of deepfake detectors frequently degrades under black-box adversarial transfer, as these models often rely on fragile, architecture-dependent forensic cues. Existing transfer attacks often lack semantic…

arxiv

Real repository issues routinely include visual evidence such as screenshots, error dialogs, rendered UI states, and logs, yet repository-level issue localization is evaluated mostly as a text-only task. Existing multim…

arxiv

Automated fulfillment warehouses must continuously assign and execute pickup-and-delivery work while avoiding congestion. In many-to-many Multi-Agent Pickup and Delivery (MAPD), a request specifies a stock-keeping unit…

arxiv

Retrieval systems are trained and evaluated on a static idea of usefulness: hand a document and a question to a reader model, see whether the answer improves, and score the document accordingly. The idea holds up when a…

arxiv

Humanoid control requires natural whole-body coordination, precise real-time responses to control signals, and robust generalization across diverse environmental contexts, making it a cornerstone for generalist embodied…

arxiv

In this post, we cover a high-level view of the Smartsheet remote MCP architecture, with a focus on the AWS infrastructure behind it. This includes security, governance, scaling and deployment, and the AI-specific optim…

aws.amazon

In this post, we walk you through the Computer Vision MCP Server, which illustrates this approach, representing how AI systems can process visual information and make intelligent decisions through a single, standardized…

aws.amazon

This post shows how Thrad.ai deployed a multi-agent system with Strands Agents and Amazon Bedrock AgentCore that automates the pipeline from prospect discovery through personalized email generation. The post compares tw…

aws.amazon

OpenAI outlines a “reverse federalism” approach to AI governance, where state laws help build a national framework for safe, democratic AI.

openai

In this post, we walk through a few ways that Quick delivers on this promise. We cover the entire sales cycle, from identifying your highest-priority prospect, contacting them, working the deal to close, and keeping the…

aws.amazon

Google DeepMind and partners announce a $10M funding call for multi-agent safety research.

deepmind

Sarah Friar, CFO of OpenAI, introduces a practical AI scorecard to measure ROI through useful work, cost per successful task, dependability, and return on compute.

openai

Explore GPT-Red, OpenAI’s automated red teaming system that uses self-play to improve AI safety, alignment, and prompt injection robustness.

openai

Learn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.

openai

Google DeepMind and Isomorphic Labs are sharing our joint approach to bioresilience and AI models.

deepmind