A recap of the latest Amazon Bedrock, Amazon Bedrock AgentCore, and Strands updates from September 2026 At AWS, we believe the fastest path to enterprise AI is giving builders real choice at every layer: model, runtime, and tooling. That belief shapes how we invest across Amazon Bedrock, AgentCore, and Strands. Amazon Bedrock continues expanding access …
Read more “ICYMI: What landed for AI builders in September 2026”
Editor’s note: This article is adapted from Thomas Kurian’s keynote address at Gemini at Work 2026. It includes a number of announcements: Gemini, a single, universal agent for work that answers your questions, handles your knowledge work, creates your images and media, and writes and runs code. Inline in Workspace, Gemini works directly inside Gmail, …
Read more “Welcome to Gemini at Work 2026: Introducing the Gemini agent”
Diffusion-based models decompose sampling into many small Gaussian denoising steps, an assumption that breaks down when generation is compressed to a few coarse transitions. Existing few-step methods address this through distillation, consistency training, or adversarial objectives, but sacrifice the likelihood framework in the process. We introduce Normalizing Trajectory Models (NTM), which models each reverse step …
When an AI agent runs, it often needs to buy something to finish a task: a model inference, an API response, access web content, or a call to another agent. These purchases are small and frequent, sometimes a fraction of a cent each, and they happen inside the agent’s loop with no person available to …
In recent decades, Ireland has grown into a vibrant hub for global technology. As modernization accelerates, Irish organizations — spanning government agencies, established enterprise brands, and growing startups in AI and other areas — are all advancing their technical foundations. Today, leaders across the country are injecting agentic AI into every layer of their business …
Read more “Innovation in Ireland: How Irish brands scale with Gemini Enterprise”
Today, we’re excited to announce the availability of Claude Haiku 5.5 on Amazon Bedrock and Claude Platform on AWS. According to Anthropic, Claude Haiku 5.5 is the fastest and most efficient model in the Claude 5.5 family, built for subagents and high-volume, cost-sensitive work. It also costs around 75 percent less than Claude Haiku 4.5 …
Training a single LLM agent jointly across diverse interactive environments has attracted increasing attention as a route to generalist agents. Existing curriculum and data-selection strategies often allocate training at the environment level or prioritize local reward-based signals, without explicitly considering relationships between current rollouts across environments for prompt-group selection. Meanwhile, as environments are learned at …
Read more “RISED: Rubrics for Agentic Multi-Environment Selection and Self-Distillation”
Off-the-shelf AI assistants answer individual questions well, but they fall short on a different axis: continuity. Ask a stateless assistant about your garden today and it has no idea that you mentioned your fast-draining raised beds three weeks ago, that you only use organic fertilizer, or that your petunias were struggling through a heat wave. …
Read more “Building a context-aware AI assistant on AgentCore and OpenClaw”
Designed artifacts are ontological, shaping, and at times limiting, what becomes possible or imaginable. One path toward mitigating such foreclosures is giving people power over how systems are designed and built. Despite decades of scholarship around systems that enable such authorship, these systems are often evaluated on whether or not they are usable, useful, or …
Read more “Negotiating Ontological Boundaries in User-Authored Personal Sensing Systems”
Coding and agentic workloads are asking more of AI models than ever: refactor a repository spanning hundreds of files, sustain a multi-hour agentic workflow without losing context, and reason through complex systems problems with tool use at every step. Meeting those demands with open-weight models has historically meant provisioning and operating your own inference infrastructure. …