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This post is co-written with Samit Verma, Eusha Rizvi, Manmeet Singh, Troy Smith, and Corey Finley from Verisk. Verisk Rating Insights as a feature of ISO Electronic Rating Content (ERC) is a powerful tool designed to provide summaries of ISO Rating changes between two releases. Traditionally, extracting specific filing information or identifying differences across multiple …
High-quality text embeddings are the engine for modern AI applications like semantic search, classification, and retrieval-augmented generation (RAG). But when it comes to picking a model to generate these embeddings, we know one size doesn’t fit all. Some use cases demand state-of-the-art quality, while others prioritize cost, speed, or compatibility with the open-source ecosystem. To …
Read more “Gemini and OSS text embeddings are now in BigQuery ML”
Today, we are excited to announce a new capability of Amazon SageMaker HyperPod task governance to help you optimize training efficiency and network latency of your AI workloads. SageMaker HyperPod task governance streamlines resource allocation and facilitates efficient compute resource utilization across teams and projects on Amazon Elastic Kubernetes Service (Amazon EKS) clusters. Administrators can …
Read more “Schedule topology-aware workloads using Amazon SageMaker HyperPod task governance”
Welcome to the first Cloud CISO Perspectives for September 2025. Today, Daryl Pereira and Hui Meng Foo, from our Office of the CISO’s Asia-Pacific office, share insights on AI from security leaders who attended our recent Google Cloud CISO Community event in Singapore. As with all Cloud CISO Perspectives, the contents of this newsletter are …
Read more “Cloud CISO Perspectives: APAC security leaders speak out on AI and key topics”
As generative AI becomes more widespread, it’s important for developers and ML engineers to be able to easily configure infrastructure that supports efficient AI inference, i.e., using a trained AI model to make predictions or decisions based on new, unseen data. While great at training models, traditional GPU-based serving architectures struggle with the “multi-turn” nature …
Read more “Fast and efficient AI inference with new NVIDIA Dynamo recipe on AI Hypercomputer”
Celtic languages — including Cornish, Irish, Scottish Gaelic and Welsh — are the U.K.’s oldest living languages. To empower their speakers, the UK-LLM sovereign AI initiative is building an AI model based on NVIDIA Nemotron that can reason in both English and Welsh, a language spoken by about 850,000 people in Wales today. Enabling high-quality …
Read more “Reaching Across the Isles: UK-LLM Brings AI to UK Languages With NVIDIA Nemotron”
Retrieval Augmented Generation (RAG) is a fundamental approach for building advanced generative AI applications that connect large language models (LLMs) to enterprise knowledge. However, crafting a reliable RAG pipeline is rarely a one-shot process. Teams often need to test dozens of configurations (varying chunking strategies, embedding models, retrieval techniques, and prompt designs) before arriving at …
Read more “Automate advanced agentic RAG pipeline with Amazon SageMaker AI”
In real-world video and image analysis, businesses often face the challenge of detecting objects that weren’t part of a model’s original training set. This becomes especially difficult in dynamic environments where new, unknown, or user-defined objects frequently appear. For example, media publishers might want to track emerging brands or products in user-generated content; advertisers need …
This post was co-authored with Jingwei Zuo from TII. We are excited to announce the availability of the Technology Innovation Institute (TII)’s Falcon-H1 models on Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, developers and data scientists can now use six instruction-tuned Falcon-H1 models (0.5B, 1.5B, 1.5B-Deep, 3B, 7B, and 34B) on AWS, and have access …
At Google Cloud Next 2025, we announced new inference capabilities with GKE Inference Gateway, including support for vLLM on TPUs, Ironwood TPUs, and Anywhere Cache. Our inference solution is based on AI Hypercomputer, a system built on our experience running models like Gemini and Veo 3, which serve over 980 trillion tokens a month to …
Read more “Scaling high-performance inference cost-effectively”