- This post is cowritten by Paul Burchard and Igor Halperin from Artificial Genius. The proliferation of large language models (LLMs) presents a significant paradox for highly regulated industries like financial services and healthcare. The ability of these models to process complex, unstructured information offers transformative potential for analytics, compliance, and risk management. However, their inherent […]
- Integrating Amazon Bedrock AgentCore with Slack brings AI agents directly into your workspace. Your teams can interact with agents without jumping between applications, losing conversation history, or re-authenticating. The integration handles three technical requirements: validating Slack event requests for security, maintaining conversation context across threads, and managing responses that exceed Slack’s timeout limits. Developers typically […]
- This post is cowritten by Tal Shapira and Tamir Friedman from Reco. Reco helps organizations strengthen the security of their software as a service (SaaS) applications and accelerate business without compromise. Using Anthropic Claude in Amazon Bedrock, Reco tackles the challenge of machine-readable security alerts that SOC teams struggle to quickly interpret. This implementation helps […]
- Autonomous agents mark a new inflection point in AI. Systems are no longer limited to generating responses or reasoning through tasks. They can take action: Agents can read files, use tools, write and run code, and execute workflows across enterprise systems, all while expanding their own capabilities. Application-layer risk grows exponentially when agents continuously improve […]
- Running machine learning (ML) models in production requires more than just infrastructure resilience and scaling efficiency. You need nearly continuous visibility into performance and resource utilization. When latency increases, invocations fail, or resources become constrained, you need immediate insight to diagnose and resolve issues before they impact your customers. Until now, Amazon SageMaker AI provided […]
- A key development in generative AI is AI-powered video generation. Before AI, creating dynamic video content required extensive resources, technical expertise, and significant manual effort. Today, AI models can generate videos from simple inputs, but organizations still face challenges like unpredictable results. This post introduces Video Retrieval-Augmented Generation (V-RAG), an approach to help improve video […]
- Generating high-quality custom videos remains a significant challenge, because video generation models are limited to their pre-trained knowledge. This limitation affects industries such as advertising, media production, education, and gaming, where customization and control of video generation is essential. To address this, we developed a Video Retrieval Augmented Generation (VRAG) multimodal pipeline that transforms structured […]
- Nemotron 3 Super is now available as a fully managed and serverless model on Amazon Bedrock, joining the Nemotron Nano models that are already available within the Amazon Bedrock environment. With NVIDIA Nemotron open models on Amazon Bedrock, you can accelerate innovation and deliver tangible business value without managing infrastructure complexities. You can power your […]
- A look at what Google learned when it collaborated with Stanford researchers to find out why some people adopt AI, and some don’t.
- Our new study shows what happens when contrail avoidance is built directly into the tools airlines already use.
- Organizations with users in multiple geographies face data residency requirements such as General Data Protection Regulation (GDPR) in Europe, country-specific data sovereignty laws, and internal compliance policies. Amazon Quick with Microsoft 365 extensions supports Regional routing to meet these requirements. Amazon Quick supports multi-Region deployments so you can route users to AWS Region-specific Amazon Quick […]
- Universal Commerce Protocol (UCP) releases new capabilities, and Google shares a new onboarding experience to simplify UCP integration.
- It’s a double feature on GFN Thursday. This week, GeForce NOW offers smoother sights in virtual reality (VR) and a sprawling new land to conquer. Streaming at 90 frames per second (fps) comes to supported VR headsets. And Crimson Desert, which recently surpassed 3 million wishlist additions on Steam, debuts in the cloud with GeForce […]
- Reinforcement learning has emerged as a powerful paradigm for unlocking reasoning capabilities in large language models. However, relying on sparse rewards makes this process highly sample-inefficient, as models must navigate vast search spaces with minimal feedback. While classic curriculum learning aims to mitigate this by ordering data based on complexity, the right ordering for a […]
- With a wide array of Nova customization offerings, the journey to customization and transitioning between platforms has traditionally been intricate, necessitating technical expertise, infrastructure setup, and considerable time investment. This disconnect between potential and practical applications is precisely what we aimed to address. Nova Forge SDK makes large language model (LLM) customization accessible, empowering teams […]
- This post is cowritten with Hammad Mian and Joonas Kukkonen from Bark.com. When scaling video content creation, many companies face the challenge of maintaining quality while reducing production time. This post demonstrates how Bark.com and AWS collaborated to solve this problem, showing you a replicable approach for AI-powered content generation. Bark.com used Amazon SageMaker and […]
- Organizations commonly rely on A/B testing to optimize user experience, messaging, and conversion flows. However, traditional A/B testing assigns users randomly and requires weeks of traffic to reach statistical significance. While effective, this process can be slow and might not fully leverage early signals in user behavior. This post shows you how to build an […]
- Moving AI agents from prototypes to production surfaces a challenge that traditional testing is unable to address. Agents are flexible, adaptive, and context-aware by design, but the same qualities that make them powerful also make them difficult to evaluate systematically. Traditional software testing relies on deterministic outputs: same input, same expected output, every time. AI […]
- Large language models (LLMs) have transformed how we interact with AI, but one size doesn’t fit at all. Out-of-the-box LLMs are trained with broad, general knowledge and improved for a wide range of use cases, but they often fall short when it comes to domain-specific tasks, proprietary workflows, or unique business requirements. Enterprise customers increasingly […]
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