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xAI’s Grok 4.7 is now available on Amazon Bedrock, adding a frontier model built for coding, long-running agents, and knowledge work to the Bedrock model catalog. It offers a 500K token context window and supports configurable reasoning effort at four levels: low, medium, high, and xhigh. Grok 4.7 is served on the bedrock-runtime endpoint through…

Today, we’re excited to announce the availability of Claude Sonnet 5.5 on Amazon Bedrock and Claude Platform on AWS. Claude Sonnet 5.5 is a smarter, more efficient Sonnet model suited for focused coding and knowledge work with lower cost per task for most work at faster speed. Amazon Bedrock gives you Sonnet 5.5 capabilities while…

Voice agents, interactive learning applications, accessibility tools, and customer service assistants need to respond without long silent pauses. In this tutorial, you deploy a text-to-speech (TTS) model on Amazon SageMaker AI that can start playing speech before it finishes generating the full response. You use the AWS vLLM-Omni Deep Learning Container (DLC) to deploy Qwen3-TTS,…

In this post, you turn a text prompt into an image, then animate that image into a short video on Amazon SageMaker AI. You deploy two endpoints from the same AWS vLLM-Omni Deep Learning Container (DLC): a real-time endpoint for FLUX.2-klein-4B image generation and an asynchronous endpoint for Wan2.1-VACE-1.3B video generation. The workflow sends a…

Synthetic monitoring emulates real user journeys through automated transactions. Rather than waiting for customers to encounter problems, teams continuously validate critical workflows (logins, purchases, form submissions) on a scheduled basis. With this approach, you detect problems faster when performance degrades or UI interactions break. For customer-facing businesses, especially in ecommerce, synthetic monitoring safeguards interactions that…

When you post-train a Mixture-of-Experts (MoE) model with Reinforcement Learning from Human Feedback (RLHF) or Group Relative Policy Optimization (GRPO) at scale, three simultaneous challenges emerge. The first requires coordinating heterogeneous compute for rollout generation and policy training. Second, sustaining high-throughput communication across hundreds of accelerators. And third, dynamically orchestrating every subsystem to keep them…

Reinforcement learning (RL) post-training is becoming a standard step in building capable language model agents. Models learn to reason and act across sequences of steps by generating trajectories, receiving rewards, and updating their policy based on outcomes. Running this at scale, across multiple nodes with hundreds of GPU-hours of rollouts per training run, requires persistent…

Executives need to make data-driven decisions during live business reviews, where accuracy and speed matter. A conversational agentic AI assistant can meet this need by answering data questions instantly. But the stakes are high: a wrong number or a slow response in front of leadership carries immediate professional consequences, and a capable large language model…

With voice cloning, you can generate new speech in a target speaker’s voice from a short reference recording, without retraining a model. You can now deploy the publicly available Qwen3-TTS-12Hz-1.7B-Base text-to-speech model from Amazon SageMaker JumpStart to a fully managed, real-time inference endpoint. Voice cloning reproduces the vocal identity of a specific speaker. Start with…

This post was written with contributions from Datacor’s TrackAbout engineering and product teams. For gas and welding distributors, rental billing on assets such as cylinders and bulk tanks is a significant share of total revenue. Yet the data needed to manage those assets was often locked in disconnected systems, accessible only through IT. The resulting…