AWSML

Generative AI has created unprecedented opportunities for Canadian organizations to transform their operations and customer experiences. We are excited to announce that customers in Canada can now access advanced foundation models including Anthropic’s Claude Sonnet 4.5 and Claude Haiku 4.5 on Amazon Bedrock through cross-Region inference (CRIS). This post explores how Canadian organizations can use … Read more

Amazon SageMaker HyperPod clusters with Amazon Elastic Kubernetes Service (EKS) orchestration now support creating and managing interactive development environments such as JupyterLab and open source Visual Studio Code, streamlining the ML development lifecycle by providing managed environments for familiar tools to data scientists. This feature introduces a new add-on called Amazon SageMaker Spaces for AI developers to create and … Read more

Anthropic’s newest foundation model, Claude Opus 4.5, is now available in Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models from leading AI companies. Opus 4.5 is a meaningful step forward in what AI systems can do and sets a new standard across coding, agents, computer use, and office tasks. … Read more

Amazon Bedrock Custom Model Import now supports OpenAI models with open weights, including GPT-OSS variants with 20-billion and 120-billion parameters. GPT-OSS models offer reasoning capabilities and can be used with OpenAI Chat Completions API. By preserving full OpenAI API compatibility, organizations can migrate their existing applications to AWS, gaining enterprise-grade security, scaling, and cost control. … Read more

As organizations increasingly adopt AI capabilities across their applications, the need for centralized management, security, and cost control of AI model access is a required step in scaling AI solutions. The Generative AI Gateway on AWS guidance addresses these challenges by providing guidance for a unified gateway that supports multiple AI providers while offering comprehensive … Read more

Organizations have used geospatial machine learning (ML) for property risk assessment, disaster response, and infrastructure planning. These systems worked well but couldn’t scale beyond specialized use cases. Each question required multiple geospatial datasets, each with its own model and often its own workflow, limiting these capabilities to a handful of high-value use cases at the … Read more

This post is co-written with Rejin Surendran from Wipro Enterprises Limited and Bakrudeen K from ShellKode. In manufacturing environments, industrial automation engineers face a significant challenge: how to rapidly convert complex process requirements into Programmable Logic Controller (PLC) ladder text code. This traditional, manual process typically requires 3-4 days per query, creating bottlenecks in production … Read more

This post is co-written with Hossein Salami and Jwalant Vyas from MSD.  In the biopharmaceutical industry, deviations in the manufacturing process are rigorously addressed. Each deviation is thoroughly documented, and its various aspects and potential impacts are closely examined to help ensure drug product quality, patient safety, and compliance. For leading pharmaceutical companies, managing these … Read more

Genomic research stands at a transformative crossroads where the exponential growth of sequencing data demands equally sophisticated analytical capabilities. According to the 1000 Genomes Project, a typical human genome differs from the reference at 4.1–5.0 million sites, with most variants being SNPs and short indels. These variants, when aggregated across individuals, contribute to differences in … Read more

Our team at Amazon builds Rufus, an AI-powered shopping assistant which delivers intelligent, conversational experiences to delight our customers. More than 250 million customers have used Rufus this year. Monthly users are up 140% YoY and interactions are up 210% YoY. Additionally, customers that use Rufus during a shopping journey are 60% more likely to … Read more

This post is co-written with Michelle Tat, Christopher Penrose, Rasmus Buchmann, and Daniel Hansen from Care Access. Organizations operating in the healthcare industry face a critical challenge as they process large volumes of medical records and face a critical challenge: how to efficiently analyze thousands of medical records daily while maintaining strict security and compliance … Read more

Claude Code is an AI-powered coding assistant from Anthropic that helps developers write, review, and modify code through natural language interactions. Amazon Bedrock is a fully managed service that provides access to foundation models from leading AI companies through a single API. This post shows you how to deploy Claude Code with Amazon Bedrock. You’ll … Read more

Amazon Bedrock Guardrails now supports protection against undesirable content within code elements including user prompts, comments, variables, function names, and string literals. Amazon Bedrock Guardrails provides configurable safeguards for building generative AI applications at scale. These safety controls work seamlessly whether you’re using foundation models from Amazon Bedrock, or applying them at various intervention points … Read more

As AI applications grow more complex, many builders struggle to appropriately and responsibly balance AI benefits and risks. Few resources exist that help non-experts articulate and resolve the key design decisions they must make. However, it doesn’t have to be this way. Today, we’re announcing the AWS Well-Architected Responsible AI Lens—a set of thoughtful questions … Read more

At Amazon, we screen customers and transactions across our global business and its subsidiaries to comply with sanctions and other global laws. Failure to comply with these laws can result in severe financial penalties and reputational harm. Amazon’s Compliance team has developed an AI-driven screening and investigations system that has transformed Amazon’s compliance processes into … Read more

This post was written with Bharath Suresh and Mary Law from Snowflake. Agentic AI is a type of AI that functions autonomously, automating a broader range of tasks with minimal supervision. It combines traditional AI and generative AI capabilities to make decisions, perform tasks, and adapt to its environment without constant human intervention. These autonomous … Read more

Optimizing generative AI applications relies on tailoring foundation models (FMs) using techniques such as prompt engineering, RAG, continued pre-training, and fine-tuning. Efficient fine-tuning is achieved by strategically managing hardware, training time, data volume, and model quality to reduce resource demands and maximize value. Spectrum is a new approach designed to pinpoint the most informative layers … Read more

Large language models (LLMs) now support a wide range of use cases, from content summarization to the ability to reason about complex tasks. One exciting new topic is taking generative AI to the physical world by applying it to robotics and physical hardware. Inspired by this, we developed a game for the AWS re:Invent 2024 … Read more

Amazon SageMaker HyperPod is a purpose-built infrastructure for optimizing foundation model training and inference at scale. SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training foundation models (FMs). As AI moves towards deployment adopting to a multitude of domains and use cases, the need for security … Read more

Over the past two years, I’ve worked with many customers using generative AI to transform their organizations. Most stall at experimentation, because costs stack up and timelines extend before delivering demonstrable value. A 2023 AWS MIT Chief Data Officer (CDO) Symposium survey backs this up, reporting that while 71% of Chief Data Officers were experimenting … Read more