AI News — Archive

Efficiently serve dozens of fine-tuned models with vLLM on Amazon SageMaker AI and Amazon…

In this post, we explain how we implemented multi-LoRA inference for Mixture of Experts (MoE) models in vLLM, describe the kernel-level optimizations we performed, and show you how you can benefit from this work. We use GPT-OSS 20B as our primary example throughout this post.

Ask a Techspert: What’s a world model?

Learn more about Google’s Project Genie, as well as what makes a world model and what it can do.

Train CodeFu-7B with veRL and Ray on Amazon SageMaker Training jobs

In this post, we demonstrate how to train CodeFu-7B, a specialized 7-billion parameter model for competitive programming, using Group Relative Policy Optimization (GRPO) with veRL, a flexible and efficient training library for large language models (LLMs) that enables straightforward extension of diverse RL algorithms and seamless integration with existing LLM infrastructure, within a distributed Ray cluster managed by SageMaker training jobs. We walk through the complete implementation, covering data preparation, distributed training setup, and comprehensive observability, showcasing how this unified approach delivers both computational scale and developer experience for sophisticated RL training workloads.

Introducing Amazon Bedrock global cross-Region inference for Anthropic’s Claude models in…

We’re excited to announce the availability of Anthropic’s Claude Opus 4.6, Claude Sonnet 4.6, Claude Opus 4.5, Claude Sonnet 4.5, and Claude Haiku 4.5 through Amazon Bedrock global cross-Region inference for customers operating in the Middle East. In this post, we guide you through the capabilities of each Anthropic Claude model variant, the key advantages of global cross-Region inference including improved resilience, real-world use cases you can implement, and a code example to help you start building generative AI applications immediately.

Deploying Open Source Vision Language Models (VLM) on Jetson

Scaling data annotation using vision-language models to power physical AI systems

In this post, we examine how Bedrock Robotics tackles this challenge. By joining the AWS Physical AI Fellowship, the startup partnered with the AWS Generative AI Innovation Center to apply vision-language models that analyze construction video footage, extract operational details, and generate labeled training datasets at scale, to improve data preparation for autonomous construction equipment.

Train AI models with Unsloth and Hugging Face Jobs for FREE

Leading Inference Providers Cut AI Costs by up to 10x With Open Source Models on NVIDIA B…

A diagnostic insight in healthcare. A character’s dialogue in an interactive game. An autonomous resolution from a customer service agent. Each of these AI-powered interactions is built on the same unit of intelligence: a token. Scaling these AI interactions requires businesses to consider whether they can afford more tokens. The answer lies in better tokenomics Read Article

H Company's new Holo2 model takes the lead in UI Localization

Training Design for Text-to-Image Models: Lessons from Ablations