- The components of agent memory
For Claude to learn from experience, it has to decide what’s worth remembering before it knows what’s next. Here’s how “dreaming” helps it organize memory and correct mistakes.
- LifeVal: Measuring AI progress on the tasks that matter in everyday life.
For AGI to benefit all of humanity, it should help people with the everyday tasks that matter most to them. So we built LifeVal, a new benchmark shaped by feedback from thousands of ChatGPT users on where they most want help from a personal assistant—from finding childcare to …
- Teaching AI to build scientific models
AI for Science grantees Jakob Macke, Daniel Gedon, and Stefan Wahl on how AI is starting to change how scientific models are built and interpreted.
- How to predict the behavior of molecules from scant data
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
- Accelerating Reinforcement Learning Weight Refit with the Reshard Collective
During reinforcement learning (RL) post-training, training trajectories are generated on the fly by running inference with the current policy model. For... During reinforcement learning (RL) post-training, training trajectories are generated on the fly by running inference wit…
- SageMaker Inference now supports Multi-Instance GPU to maximize GPU utilization for model endpoints
Amazon SageMaker Inference now supports GPU partitioning with NVIDIA Multi-Instance GPU (MIG), which divides one GPU into hardware-isolated partitions so you can run a different model in each or take a right-sized fraction of a newer accelerator. This post shows how two option…
- Taxonomy of agentic primitives in Amazon Quick
As we built Amazon Quick, its agents grew from answering questions to taking actions, and the same primitives kept getting rebuilt under different names. This post shares the taxonomy we converged on — triggers, agents, capabilities, and learned context — found by decomposing …
- Serverless MCP server for AI agent data lake access on Amazon ECS Fargate
Learn how to build a serverless Model Context Protocol (MCP) server on Amazon ECS with AWS Fargate that gives AI agents secure, metadata-driven access to an enterprise data lake. Exposing a new dataset requires only a JSON file, with no per-dataset integration code.
- Project EVE: Claude plays MMORPGs
We put Claude in two EVE games to study how AI agents handle markets and teamwork, where they break down, and what safeguards they might need.
- Govern AI agent access with Okta Cross App Access and Amazon Bedrock AgentCore – Part 2
In Part 1 you built one governed agent. Part 2 scales the pattern to an enterprise: Amazon Bedrock AgentCore Gateway becomes the single front door and redeems Okta's grant, Cedar policies bind each tool to the agent, a second agent runs on Amazon EKS, and AgentCore Observabili…
- Govern AI agent access with Okta Cross App Access and Amazon Bedrock AgentCore – Part 1
An AI agent that acts for a user raises an identity question that per-app OAuth and service accounts leave open: which agent may act for which user, and how you stop it. In this first post of two, you build a task agent on Amazon Bedrock AgentCore that governs access through O…
- How Greenlight Financial built an autonomous SOC solution on Amazon Bedrock AgentCore
Greenlight Financial resolves more than 90% of up to 4,000 monthly security and risk cases without human intervention using Luna, a tiered multi-agent system on Amazon Bedrock AgentCore. This post covers the architecture, episodic memory for continuous learning, and the expans…
- Taxbit Assist: A grounded, role-aware AI agent on Amazon Bedrock AgentCore
Taxbit built Taxbit Assist, a cited, permission-aware AI assistant embedded in its enterprise dashboard, on Amazon Bedrock AgentCore. This post shows how they grounded answers in a curated knowledge base, enforced role-aware and region-compliant safety, and continuously measur…
- Extend Claude Code to remote sessions on Amazon Bedrock AgentCore with security controls
Run Claude Code as a remote agent on Amazon Bedrock AgentCore. Each coding task runs in its own isolated session in your AWS account, every model call goes through Amazon Bedrock, and the result comes back as a GitHub pull request you review and merge.
- Context Engineering for Images: MIT researchers build VISTA, an agent harness that keeps images in memory for faster retrieval
Managing an agent’s context by storing all the input text it receives and giving it tools to search the text boosts its performance.
- World Models Become Robot Playgrounds: Google Genie 4 combines with Gemini models to build better video game worlds, robotics training
Google says that Genie 4, its latest world model, will be used in tandem with Gemini models to create digital practice spaces for robots, giving them endless worlds to train in