Compelling AI-generated images start with well-crafted prompts. In this follow-up to our Amazon Nova Canvas Prompt Engineering Guide, we showcase a curated gallery of visuals generated by Nova Canvas—categorized by real-world use cases—from marketing and product visualization to concept art and design exploration. Each image is paired with the prompt and parameters that generated it, … Read more
Based on original post by Dr. Hemant Joshi, CTO, FloTorch.ai A recent evaluation conducted by FloTorch compared the performance of Amazon Nova models with OpenAI’s GPT-4o. Amazon Nova is a new generation of state-of-the-art foundation models (FMs) that deliver frontier intelligence and industry-leading price-performance. The Amazon Nova family of models includes Amazon Nova Micro, Amazon … Read more
DeepSeek-R1 is a large language model (LLM) developed by DeepSeek AI that uses reinforcement learning to enhance reasoning capabilities through a multi-stage training process from a DeepSeek-V3-Base foundation. A key distinguishing feature is its reinforcement learning step, which was used to refine the model’s responses beyond the standard pre-training and fine-tuning process. By incorporating RL, … Read more
In today’s fast-paced world, time is of the essence and even basic tasks like grocery shopping can feel rushed and challenging. Despite our best intentions to plan meals and shop accordingly, we often end up ordering takeout; leaving unused perishable items to spoil in the refrigerator. This seemingly small issue of wasted groceries, paired with … Read more
Investment professionals face the mounting challenge of processing vast amounts of data to make timely, informed decisions. The traditional approach of manually sifting through countless research documents, industry reports, and financial statements is not only time-consuming but can also lead to missed opportunities and incomplete analysis. This challenge is particularly acute in credit markets, where … Read more
DeepSeek-R1 models, now available on Amazon Bedrock Marketplace, Amazon SageMaker JumpStart, as well as a serverless model on Amazon Bedrock, were recently popularized by their long and elaborate thinking style, which, according to DeepSeek’s published results, lead to impressive performance on highly challenging math benchmarks like AIME-2024 and MATH-500, as well as competitive performance compared … Read more
Today, we’re announcing the general availability (GA) of multi-agent collaboration on Amazon Bedrock. This capability allows developers to build, deploy, and manage networks of AI agents that work together to execute complex, multi-step workflows efficiently. Since its preview launch at re:Invent 2024, organizations across industries—including financial services, healthcare, supply chain and logistics, manufacturing, and customer … Read more
This post is co-authored with Sundeep Sardana, Malolan Raman, Joseph Lam, Maitri Shah and Vaibhav Singh from Verisk. Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks. … Read more
Today, Amazon Web Services (AWS) announced the general availability of Amazon Bedrock Knowledge Bases GraphRAG (GraphRAG), a capability in Amazon Bedrock Knowledge Bases that enhances Retrieval-Augmented Generation (RAG) with graph data in Amazon Neptune Analytics. This capability enhances responses from generative AI applications by automatically creating embeddings for semantic search and generating a graph of … Read more
Agents are revolutionizing the landscape of generative AI, serving as the bridge between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to become the cornerstone of AI adoption across industries, heralding a new era of human-AI collaboration and problem-solving. By using the power of LLMs and combining them with specialized … Read more
In the rapidly evolving landscape of artificial intelligence, Retrieval Augmented Generation (RAG) has emerged as a game-changer, revolutionizing how Foundation Models (FMs) interact with organization-specific data. As businesses increasingly rely on AI-powered solutions, the need for accurate, context-aware, and tailored responses has never been more critical. Enter the powerful trio of Amazon Bedrock, LlamaIndex, and … Read more
This post was co-authored with Johann Wildgruber, Dr. Jens Kohl, Thilo Bindel, and Luisa-Sophie Gloger from BMW Group. The BMW Group—headquartered in Munich, Germany—is a vehicle manufacturer with more than 154,000 employees, and 30 production and assembly facilities worldwide as well as research and development locations across 17 countries. Today, the BMW Group (BMW) is the … Read more
Time series forecasting is critical for decision-making across industries. From predicting traffic flow to sales forecasting, accurate predictions enable organizations to make informed decisions, mitigate risks, and allocate resources efficiently. However, traditional machine learning approaches often require extensive data-specific tuning and model customization, resulting in lengthy and resource-heavy development. Enter Chronos, a cutting-edge family of … Read more
Generative AI question-answering applications are pushing the boundaries of enterprise productivity. These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques. However, building and deploying trustworthy AI assistants requires a robust ground truth and evaluation framework. Ground truth … Read more
Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize … Read more
Amazon Bedrock Knowledge Bases offers a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) to internal data sources. It’s a cost-effective approach to improving LLM output so it remains relevant, accurate, and useful in various contexts. It also provides developers with greater control over the LLM’s outputs, including the ability … Read more
Increasingly, organizations across industries are turning to generative AI foundation models (FMs) to enhance their applications. To achieve optimal performance for specific use cases, customers are adopting and adapting these FMs to their unique domain requirements. This need for customization has become even more pronounced with the emergence of new models, such as those released … Read more
Recent advances in generative AI have led to the proliferation of new generation of conversational AI assistants powered by foundation models (FMs). These latency-sensitive applications enable real-time text and voice interactions, responding naturally to human conversations. Their applications span a variety of sectors, including customer service, healthcare, education, personal and business productivity, and many others. … Read more
Today, we are excited to announce that Pixtral 12B (pixtral-12b-2409), a state-of-the-art 12 billion parameter vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a new capability in Amazon Bedrock that enables developers to discover, test, and … Read more
Amazon Q Business is a fully managed, generative AI–powered assistant that empowers enterprises to unlock the full potential of their data and organizational knowledge. With Amazon Q Business, you can quickly access answers to questions, generate summaries and content, and complete tasks by using the expertise and information stored across various data sources and enterprise … Read more
Organizations across many industries are harnessing the power of foundation models (FMs) and large language models (LLMs) to build generative AI applications to deliver new customer experiences, boost employee productivity, and drive innovation. Amazon Bedrock, a fully managed service that offers a choice of high-performing FMs from leading AI companies, provides the easiest way to … Read more
This post was written by Claudiu Bota, Oleg Yurchenko, and Vladyslav Melnyk of AWS Partner Automat-it. As organizations adopt AI and machine learning (ML), they’re using these technologies to improve processes and enhance products. AI use cases include video analytics, market predictions, fraud detection, and natural language processing, all relying on models that analyze data … Read more
AWS DeepRacer League 2024 Championship finalists at re:Invent 2024 The AWS DeepRacer League is the world’s first global autonomous racing league powered by machine learning (ML). Over the past 6 years, a diverse community of over 560,000 builders from more than 150 countries worldwide have participated in the League to learn ML fundamentals hands-on through … Read more
In our previous blog posts, we explored various techniques such as fine-tuning large language models (LLMs), prompt engineering, and Retrieval Augmented Generation (RAG) using Amazon Bedrock to generate impressions from the findings section in radiology reports using generative AI. Part 1 focused on model fine-tuning. Part 2 introduced RAG, which combines LLMs with external knowledge … Read more
Having spent the last years studying the art of AWS DeepRacer in the physical world, the author went to AWS re:Invent 2024. How did it go? In AWS DeepRacer: How to master physical racing?, I wrote in detail about some aspects relevant to racing AWS DeepRacer in the physical world. We looked at the differences … Read more
Brands today are juggling a million things, and keeping product content up-to-date is at the top of the list. Between decoding the endless requirements of different marketplaces, wrangling inventory across channels, adjusting product listings to catch a customer’s eye, and trying to outpace shifting trends and fierce competition, it’s a lot. And let’s face it—staying … Read more
In enterprise environments, organizations often divide their AI operations into two specialized teams: an AI research team and a model hosting team. The research team is dedicated to developing and enhancing AI models using model training and fine-tuning techniques. Meanwhile, a separate hosting team is responsible for deploying these models across their own development, staging, … Read more
This is a guest post authored by the team at ByteDance. ByteDance is a technology company that operates a range of content platforms to inform, educate, entertain, and inspire people across languages, cultures, and geographies. Users trust and enjoy our content platforms because of the rich, intuitive, and safe experiences they provide. These experiences are … Read more
This post is co-written with Xavier Vizcaino, Diego Martín Montoro, and Jordi Sánchez Ferrer from Applus+ Idiada. In 2021, Applus+ IDIADA, a global partner to the automotive industry with over 30 years of experience supporting customers in product development activities through design, engineering, testing, and homologation services, established the Digital Solutions department. This strategic move … Read more
Troubleshooting infrastructure as code (IaC) errors often consumes valuable time and resources. Developers can spend multiple cycles searching for solutions across forums, troubleshooting repetitive issues, or trying to identify the root cause. These delays can lead to missed security errors or compliance violations, especially in complex, multi-account environments. This post demonstrates how you can use … Read more