Machine Learning

This post is cowritten with Dr. Mikkel Hansen from Qbtech. The assessment and diagnosis of attention deficit hyperactive disorder (ADHD) has traditionally relied on clinical observations and behavioral evaluations. While these methods are valuable, the process can be complex and time-intensive. Qbtech, founded in 2002 in Stockholm, Sweden, enhances ADHD diagnosis by integrating objective measurements … Read more

Marketing teams face increasing pressure to create engaging campaigns quickly while maintaining brand consistency and creative quality. Traditional marketing campaign creation processes often involve multiple iterations between creative teams, stakeholders, and external agencies, leading to extended timelines and increased costs. The advent and availability of generative models (especially image and video generation ones) has opened … Read more

This post is cowritten with Sangeetha Bharath and Seemal Zaman from Visa. Across every industry, agentic AI is redefining how work gets done by shifting digital experiences from manual, user-driven interactions to autonomous, outcome-driven workflows. Unlike traditional AI systems that merely answer questions or provide suggestions, agentic AI introduces intelligent agents capable of reasoning, acting, … Read more

As organizations scale their generative AI implementations, the critical challenge of balancing quality, cost, and latency becomes increasingly complex. With inference costs dominating 70–90% of large language model (LLM) operational expenses, and verbose prompting strategies inflating token volume by 3–5x, organizations are actively seeking more efficient approaches to model interaction. Traditional prompting methods, while effective, … Read more

Mistral AI’s Voxtral models combine text and audio processing capabilities in a single framework. The Voxtral family includes two distinct variants designed for different use cases and resource requirements. The Voxtral-Mini-3B-2507 is a compact 3-billion-parameter model optimized for efficient audio transcription and basic multimodal understanding, making it ideal for applications where speed and resource efficiency … Read more

Extracting structured information from unstructured data is a critical first step to unlocking business value. Our Generative AI Intelligent Document Processing (GenAI IDP) Accelerator has been at the forefront of this transformation, already having processed tens of millions of documents for hundreds of customers. Although organizations can use intelligent document processing (IDP) solutions to digitize … Read more

Predictive maintenance is a strategy that uses data from equipment sensors and advanced analytics to predict when a machine is likely to fail, ensuring maintenance can be performed proactively to prevent breakdowns. This enables industries to reduce unexpected failures, improve operational efficiency, and extend the lifespan of critical equipment. It is applicable across a wide range of components, … Read more

Today, we are excited to introduce a new feature for SageMaker Studio: SOCI (Seekable Open Container Initiative) indexing. SOCI supports lazy loading of container images, where only the necessary parts of an image are downloaded initially rather than the entire container. SageMaker Studio serves as a web Integrated Development Environment (IDE) for end-to-end machine learning (ML) development, … Read more

This post is co-written with Ranjit Rajan, Abdullahi Olaoye, and Abhishek Sawarkar from NVIDIA. AI’s next frontier isn’t merely smarter chat-based assistants, it’s autonomous agents that reason, plan, and execute across entire systems. But to accomplish this, enterprise developers need to move from prototypes to production-ready AI agents that scale securely. This challenge grows as … Read more

Building natural voice conversations with AI agents requires complex infrastructure and lots of code from engineering teams. Text-based agent interactions follow a turn-based pattern: a user sends a complete request, waits for the agent to process it, and receives a full response before continuing. Bi-directional streaming removes this constraint by establishing a persistent connection that … Read more

Building custom foundation models requires coordinating multiple assets across the development lifecycle such as data assets, compute infrastructure, model architecture and frameworks, lineage, and production deployments. Data scientists create and refine training datasets, develop custom evaluators to assess model quality and safety, and iterate through fine-tuning configurations to optimize performance. As these workflows scale across … Read more

A user can conduct machine learning (ML) data experiments in data environments, such as Snowflake, using the Snowpark library. However, tracking these experiments across diverse environments can be challenging due to the difficulty in maintaining a central repository to monitor experiment metadata, parameters, hyperparameters, models, results, and other pertinent information. In this post, we demonstrate … Read more

Picture this: Your enterprise has just deployed its first generative AI application. The initial results are promising, but as you plan to scale across departments, critical questions emerge. How will you enforce consistent security, prevent model bias, and maintain control as AI applications multiply? It turns out you’re not alone. A McKinsey survey spanning 750+ … Read more

This post is co-written with Vikram Bansal from Tata Power, and Gaurav Kankaria, Omkar Dhavalikar from Oneture. The global adoption of solar energy is rapidly increasing as organizations and individuals transition to renewable energy sources. India is on the brink of a solar energy revolution, with a national goal to empower 10 million households with … Read more

Media and entertainment, advertising, education, and enterprise training content combines visual, audio, and motion elements to tell stories and convey information, making it far more complex than text where individual words have clear meanings. This creates unique challenges for AI systems that need to understand video content. Video content is multidimensional, combining visual elements (scenes, … Read more

Foundation model training has reached an inflection point where traditional checkpoint-based recovery methods are becoming a bottleneck to efficiency and cost-effectiveness. As models grow to trillions of parameters and training clusters expand to thousands of AI accelerators, even minor disruptions can result in significant costs and delays. In this post, we introduce checkpointless training on … Read more

Modern AI infrastructure serves multiple concurrent workloads on the same cluster, from foundation model (FM) pre-training and fine-tuning to production inference and evaluation. In this shared environment, the demands for AI accelerators fluctuates continuously as inference workloads scale with traffic patterns, and experiments complete and release resources. Despite this dynamic availability of AI accelerators, traditional … Read more

Large Language Model (LLM) agents have revolutionized how we approach complex, multi-step tasks by combining the reasoning capabilities of foundation models with specialized tools and domain expertise. While single-agent systems using frameworks like ReAct work well for straightforward tasks, real-world challenges often require multiple specialized agents working in coordination. Think about planning a business trip: … Read more

Enterprise organizations are rapidly moving beyond generative AI experiments to production deployments and complex agentic AI solutions, facing new challenges in scaling, security, governance, and operational efficiency. This blog post series introduces generative AI operations (GenAIOps), the application of DevOps principles to generative AI solutions, and demonstrates how to implement it for applications powered by … Read more

Amazon Simple Storage Service (Amazon S3) is a highly elastic service that automatically scales with application demand, offering the high throughput performance required for modern ML workloads. High-performance client connectors such as the Amazon S3 Connector for PyTorch and Mountpoint for Amazon S3 provide native S3 integration in training pipelines without dealing directly with the … Read more

As cloud infrastructure becomes increasingly complex, the need for intuitive and efficient management interfaces has never been greater. Traditional command-line interfaces (CLI) and web consoles, while powerful, can create barriers to quick decision-making and operational efficiency. What if you could speak to your AWS infrastructure and get immediate, intelligent responses? In this post, we explore … Read more

This post was written with Bryan Woolgar-O’Neil, Jamie Cockrill and Adrian Cunliffe from Harmonic Security Organizations face increasing challenges protecting sensitive data while supporting third-party generative AI tools. Harmonic Security, a cybersecurity company, developed an AI governance and control layer that spots sensitive data in line as employees use AI, giving security teams the power … Read more

This post was written with Arun Sittampalam and Maxime Darcot from Swisscom. As we navigate the constantly shifting AI ecosystem, enterprises face challenges in translating AI’s potential into scalable, production-ready solutions. Swisscom, Switzerland’s leading telecommunications provider with an estimated $19B revenue (2025) and over $37B Market capitalization as of June 2025 exemplifies how organizations can … Read more

Today we’re announcing Amazon SageMaker AI with MLflow, now including a serverless capability that dynamically manages infrastructure provisioning, scaling, and operations for artificial intelligence and machine learning (AI/ML) development tasks. It scales resources up during intensive experimentation and down to zero when not in use, reducing operational overhead. It introduces enterprise-scale features including seamless access … Read more

The rise of artificial intelligence (AI) agents marks a change in software development and how applications make decisions and interact with users. While traditional systems follow predictable paths, AI agents engage in complex reasoning that remains hidden from view. This invisibility creates a challenge for organizations: how can they trust what they can’t see?  This … Read more

Automated smoke testing using Amazon Nova Act headless mode helps development teams validate core functionality in continuous integration and continuous delivery (CI/CD) pipelines. Development teams often deploy code several times daily, so fast testing helps maintain application quality. Traditional end-to-end testing can take hours to complete, creating delays in your CI/CD pipeline. Smoke testing is … Read more

Artificial intelligence (AI) reasoning capabilities determine whether models can handle complex, real-world tasks beyond simple pattern matching. With strong reasoning, models can identify problems from ambiguous descriptions, apply policies under competing constraints, adapt tone to sensitive situations, and provide complete solutions that address root causes. Without robust reasoning, AI systems fail when faced with nuanced … Read more

Teams need instant access to enterprise data and intelligent guidance on how to use it. Instead, they get scattered information across multiple systems. This results in employees spending valuable time searching for answers instead of making decisions. In this post, we show how to build chat agents in Amazon Quick Suite to address this problem. … Read more

When critical services depend on quick action, from the safety of vulnerable children to environmental protection, you need working AI solutions in weeks, not years. Amazon recently announced an investment of up to $50 billion in expanded AI and supercomputing infrastructure for US government agencies, demonstrating both the urgency and commitment from Amazon Web Services … Read more

Today, we are pleased to announce a new integration between Amazon Quick Research and S&P Global. This integration brings both S&P Global Energy news, research, and insights and S&P Global Market Intelligence data to Quick Research customers in one deep research agent. The S&P Global integration extends the capabilities of Quick Research so that business … Read more