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Introducing cross-Region inference for OpenAI GPT-5.6 models on Amazon Bedrock

This post is co-written with Chris Dickens from OpenAI. Amazon Bedrock now offers OpenAI GPT-5.6 models on Amazon Bedrock in more than 25 AWS Regions, with cross-Region inference. Three GPT-5.6 variants support cross-Region inference, Sol, Terra, and Luna, each tuned for a different balance of capability and cost. Cross-Region inference (CRIS) in Amazon Bedrock works …

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Expanding Google Antigravity for enterprise customers

Since announcing Google Antigravity in Gemini Enterprise Agent Platform at I/O in May, we’ve heard helpful feedback from our customers. Your developers want easy access to coding agents across surfaces. Your enterprise governance team wants security controls and license management. And your finance team wants pooled usage so that no prepaid token ever goes unused. …

Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts

Large language models (LLMs) exhibit a wide range of human-like behaviors, from expressing thoughts and emotions, to engaging in relationship-building with users, to refusing requests and maintaining boundaries. Despite their prevalence, researchers and practitioners lack methods and empirical insights to make informed decisions about when and what types of human-like behaviors LLMs should exhibit. To …

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Domain and publish date filters for Web Search on AgentCore

When an AI agent uses Web Search to ground its answers on behalf of a customer, the organization behind that agent needs domain and date filters to control which sources the agent consults and how fresh those sources must be. A financial-services agent shouldn’t ground its answers in an unvetted blog. A product-information agent shouldn’t …

GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings

Reinforcement Learning with Verifiable Rewards (RLVR), often optimized with Group Relative Policy Optimization (GRPO), has become a central recipe for improving the reasoning capabilities of pretrained language models but current studies remain heavily English-centric. We conduct a large-scale empirical study of multilingual and non-English GRPO across a wide range of base models, training languages, and …

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Amazon Bedrock AgentCore payments is now generally available: Enabling agents to transact safely and autonomously at scale

Agents have evolved from simple chat applications to autonomous, long-running systems that dynamically discover and compose dozens of tools per task without human oversight. On the other side, service and content providers are moving from human-centric subscription-based, one-size-fits-all pricing to pay-per-use, per-execution models where costs are often a few cents. Today, agents are doing a …

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Building cost-effective, high-throughput gen AI workflows in Google Dataflow

Real-time streaming pipelines are the operational backbone of modern enterprises, continuously processing everything from customer support interactions to transaction logs. Traditionally, streaming DAGs are static; once deployed, their processing logic and execution paths are fixed. However, by integrating generative AI agents, we can move beyond static logic to adaptive execution. This allows streaming workflows to …

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NVIDIA Nemotron 3.5 Lightning now available in Amazon SageMaker JumpStart

NVIDIA Nemotron 3.5 Lightning is designed for the fast, specialized model execution required by high-volume agentic workloads. With NVIDIA Nemotron 3.5 Lightning on Amazon SageMaker JumpStart, you can access an open model designed for high-volume agentic workloads. With this launch, you can deploy Nemotron 3.5 Lightning from Amazon SageMaker JumpStart without configuring the serving infrastructure …

When Unlearning Is Free: Leveraging Low Influence Points to Reduce Computational Costs

As concerns around data privacy in machine learning grow, the ability to unlearn, or remove, specific data points from trained models becomes increasingly important. While state of the art unlearning methods have emerged in response, they typically treat all points in the forget set equally. In this work, we challenge this approach by asking whether …

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Custom reward functions for multi-turn reinforcement learning with Amazon Nova Forge

In multi-turn reinforcement learning (RL), your custom reward function decides what the model actually learns. A subtly wrong reward can quietly teach the wrong thing while every training curve looks healthy. Designing a reward that holds up over multi-turn, agentic tasks is one of the hardest parts of customizing Amazon Nova models. For multi-turn training, …