[
  {
    "id": "b88ea9c8-0d8c-40d1-acc5-fba4d0dfe517",
    "slug": "amazon-20260424-building-workforce-ai-agents-with-visier-and-amazon-quick",
    "title": "Building Workforce AI Agents with Visier and Amazon Quick",
    "summary": "In this post, we show how connecting the Visier Workforce AI platform with Amazon Quick through Model Context Protocol (MCP) gives every knowledge worker a unified agentic workspace to ask questions in. Visier helps ground the workspace in live workforce data and the organizational context that surrounds it while letting your users act on the conversational results without switching tools.",
    "author": "Vishnu Elangovan",
    "category": "News",
    "tags": [
      "Amazon Quick Suite",
      "Artificial Intelligence",
      "Customer Solutions"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/building-workforce-ai-agents-with-visier-and-amazon-quick/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-24T18:04:20+00:00",
    "updatedAt": "2026-04-24T18:36:47.419605+00:00"
  },
  {
    "id": "d5473a02-6b13-4f14-82b5-9a913e349ef7",
    "slug": "amazon-20260423-amazon-quick-for-marketing-from-scattered-data-to-strategic-action",
    "title": "Amazon Quick for marketing: From scattered data to strategic action",
    "summary": "Amazon Quick changes how you work. You can set it up in minutes and by the end of the day, you will wonder how you ever worked without it. Quick connects with your applications, tools, and data, creating a personal knowledge graph that learns your priorities, preferences, and network.",
    "author": "Zach Conley",
    "category": "News",
    "tags": [
      "Amazon Quick Suite",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/amazon-quick-for-marketing-from-scattered-data-to-strategic-action/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-23T17:05:17+00:00",
    "updatedAt": "2026-04-23T17:34:33.573534+00:00"
  },
  {
    "id": "699f5859-a27f-429b-856c-c3301b5add35",
    "slug": "amazon-20260423-applying-multimodal-biological-foundation-models-across-therapeutics-and-patient",
    "title": "Applying multimodal biological foundation models across therapeutics and patient care",
    "summary": "In this post, we\u0027ll explore how multimodal BioFMs work, showcase real-world applications in drug discovery and clinical development, and contextualize how AWS enables organizations to build and deploy multimodal BioFMs.",
    "author": "Kristin Ambrosini",
    "category": "News",
    "tags": [
      "Foundation models",
      "Generative AI",
      "Healthcare",
      "Life Sciences"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/applying-multimodal-biological-foundation-models-across-therapeutics-and-patient-care/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-23T16:17:29+00:00",
    "updatedAt": "2026-04-23T16:34:27.391381+00:00"
  },
  {
    "id": "a8cc780d-7ee5-48c5-b16a-7bd41dd8f434",
    "slug": "amazon-20260422-cost-effective-multilingual-audio-transcription-at-scale-with-parakeet-tdt-and-a",
    "title": "Cost-effective multilingual audio transcription at scale with Parakeet-TDT and AWS Batch",
    "summary": "In this post, we walk through building a scalable, event-driven transcription pipeline that automatically processes audio files uploaded to Amazon Simple Storage Service (Amazon S3), and show you how to use Amazon EC2 Spot Instances and buffered streaming inference to further reduce costs.",
    "author": "Gleb Geinke",
    "category": "News",
    "tags": [
      "AWS Batch",
      "Compute",
      "High Performance Computing",
      "Technical How-to"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/cost-effective-multilingual-audio-transcription-at-scale-with-parakeet-tdt-and-aws-batch/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-22T21:05:01+00:00",
    "updatedAt": "2026-04-22T21:32:47.806319+00:00"
  },
  {
    "id": "f6d9b60f-68a0-4e3c-a3cb-4627f4aa976d",
    "slug": "amazon-20260422-amazon-sagemaker-ai-now-supports-optimized-generative-ai-inference-recommendatio",
    "title": "Amazon SageMaker AI now supports optimized generative AI inference recommendations",
    "summary": "Today, Amazon SageMaker AI supports optimized generative AI inference recommendations. By delivering validated, optimal deployment configurations with performance metrics, Amazon SageMaker AI keeps your model developers focused on building accurate models, not managing infrastructure.",
    "author": "Mona Mona",
    "category": "News",
    "tags": [
      "Amazon SageMaker",
      "Amazon SageMaker AI",
      "Generative AI"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-ai-now-supports-optimized-generative-ai-inference-recommendations/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-22T19:15:08+00:00",
    "updatedAt": "2026-04-22T19:32:34.829134+00:00"
  },
  {
    "id": "62949a78-04a0-4eaa-a40f-9f4545c6cdaa",
    "slug": "amazon-20260422-get-to-your-first-working-agent-in-minutes-announcing-new-features-in-amazon-bed",
    "title": "Get to your first working agent in minutes: Announcing new features in Amazon Bedrock AgentCore",
    "summary": "Today, we\u0027re introducing new capabilities that further streamline the agent building experience, removing the infrastructure barriers that slow teams down at every stage of agent development from the first prototype through production deployment.",
    "author": "Madhu Parthasarathy",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Bedrock AgentCore",
      "Announcements",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/get-to-your-first-working-agent-in-minutes-announcing-new-features-in-amazon-bedrock-agentcore/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-22T19:13:56+00:00",
    "updatedAt": "2026-04-22T19:32:34.829223+00:00"
  },
  {
    "id": "d73b8fd0-b479-4fb5-8679-87d4def99fc4",
    "slug": "amazon-20260422-company-wise-memory-in-amazon-bedrock-with-amazon-neptune-and-mem0",
    "title": "Company-wise memory in Amazon Bedrock with Amazon Neptune and Mem0",
    "summary": "Company-wise memory in Amazon Bedrock, powered by Amazon Neptune and Mem0, provides AI agents with persistent, company-specific context\u2014enabling them to learn, adapt, and respond intelligently across multiple interactions. TrendMicro, one of the largest antivirus software companies in the world, developed the Trend\u2019s Companion chatbot, so their customers can explore information through natural, conversational interactions",
    "author": "Shawn Tsai",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Neptune",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/company-wise-memory-in-amazon-bedrock-with-amazon-neptune-and-mem0/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-22T15:56:24+00:00",
    "updatedAt": "2026-04-22T16:32:15.94309+00:00"
  },
  {
    "id": "66c2b912-8355-42ed-af52-977eb76a7990",
    "slug": "amazon-20260421-from-developer-desks-to-the-whole-organization-running-claude-cowork-in-amazon-b",
    "title": "From developer desks to the whole organization: Running Claude Cowork in Amazon Bedrock",
    "summary": "Today, we\u0027re excited to announce Claude Cowork in Amazon Bedrock. You can now run Cowork and Claude Code Desktop through Amazon Bedrock, directly or using an LLM gateway. In this post, we walk through how Claude Cowork integrates with Amazon Bedrock and show an example of how knowledge workers use it in practice.",
    "author": "Sofian Hamiti",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Announcements",
      "Generative AI"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/from-developer-desks-to-the-whole-organization-running-claude-cowork-in-amazon-bedrock/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-21T19:13:49+00:00",
    "updatedAt": "2026-04-21T19:29:55.354948+00:00"
  },
  {
    "id": "14dbfbf0-4388-43d7-94c3-dd6310f39c25",
    "slug": "amazon-20260421-end-to-end-lineage-with-dvc-and-amazon-sagemaker-ai-mlflow-apps",
    "title": "End-to-end lineage with DVC and Amazon SageMaker AI MLflow apps",
    "summary": "In this post, we show how to combine DVC (Data Version Control), Amazon SageMaker AI, and Amazon SageMaker AI MLflow Apps to build end-to-end ML model lineage. We walk through two deployable patterns \u2014 dataset-level lineage and record-level lineage \u2014 that you can run in your own AWS account using the companion notebooks.",
    "author": "Manuwai Korber",
    "category": "News",
    "tags": [
      "Amazon SageMaker AI",
      "Technical How-to"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/end-to-end-lineage-with-dvc-and-amazon-sagemaker-ai-mlflow-apps/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-21T16:43:03+00:00",
    "updatedAt": "2026-04-21T19:29:55.355016+00:00"
  },
  {
    "id": "76d4a7d3-2183-4602-93e9-cd5a1ceff720",
    "slug": "amazon-20260420-accelerate-generative-ai-inference-on-amazon-sagemaker-ai-with-g7e-instances",
    "title": "Accelerate Generative AI Inference on Amazon SageMaker AI with G7e Instances",
    "summary": "Today, we are thrilled to announce the availability of G7e instances powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs on Amazon SageMaker AI. You can provision nodes with 1, 2, 4, and 8 RTX PRO 6000 GPU instances, with each GPU providing 96 GB of GDDR7 memory. This launch provides the capability to use a single-node GPU, G7e.2xlarge instance to host powerful open source foundation models (FMs) like GPT-OSS-120B, Nemotron-3-Super-120B-A12B (NVFP4 variant), and Qwen3.5-35B-A3B, offering organizations a cost-effective and high-performing option.",
    "author": "Hazim Qudah",
    "category": "News",
    "tags": [
      "Amazon SageMaker",
      "Amazon SageMaker AI",
      "Artificial Intelligence",
      "Technical How-to",
      "AI/ML"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/accelerate-generative-ai-inference-on-amazon-sagemaker-ai-with-g7e-instances/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-20T19:38:10+00:00",
    "updatedAt": "2026-04-21T13:29:30.989691+00:00"
  },
  {
    "id": "14e18813-16d1-454a-868b-9b14310e2df3",
    "slug": "amazon-20260420-toolsimulator-scalable-tool-testing-for-ai-agents",
    "title": "ToolSimulator: scalable tool testing for AI agents",
    "summary": "You can use ToolSimulator, an LLM-powered tool simulation framework within Strands Evals, to thoroughly and safely test AI agents that rely on external tools, at scale. Instead of risking live API calls that expose personally identifiable information (PII), trigger unintended actions, or settling for static mocks that break with multi-turn workflows, you can use ToolSimulator\u0027s large language model (LLM)-powered simulations to validate your agents. Available today as part of the Strands Evals Software Development Kit (SDK), ToolSimulator helps you catch integration bugs early, test edge cases comprehensively, and ship production-ready agents with confidence.",
    "author": "Darren Wang",
    "category": "News",
    "tags": [
      "Artificial Intelligence",
      "Strands Agents"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/toolsimulator-scalable-tool-testing-for-ai-agents/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-20T17:06:26+00:00",
    "updatedAt": "2026-04-21T13:29:30.989773+00:00"
  },
  {
    "id": "8958bd35-c201-438b-a8e9-c64519496c7d",
    "slug": "amazon-20260420-omnichannel-ordering-with-amazon-bedrock-agentcore-and-amazon-nova-2-sonic",
    "title": "Omnichannel ordering with Amazon Bedrock AgentCore and Amazon Nova 2 Sonic",
    "summary": "In this post, we\u0027ll show you how to build a complete omnichannel ordering system using Amazon Bedrock AgentCore, an agentic platform, to build, deploy, and operate highly effective AI agents securely at scale using any framework and foundation model and Amazon Nova 2 Sonic.",
    "author": "Sergio Barraza",
    "category": "News",
    "tags": [
      "Amazon API Gateway",
      "Amazon Bedrock",
      "Amazon Bedrock AgentCore",
      "Amazon Cognito",
      "Amazon DynamoDB"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/omnichannel-ordering-with-amazon-bedrock-agentcore-and-amazon-nova-2-sonic/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-20T15:03:28+00:00",
    "updatedAt": "2026-04-21T13:29:30.989784+00:00"
  },
  {
    "id": "e3897bb6-4ee1-4f80-be91-0f6bfd5e015f",
    "slug": "amazon-20260417-introducing-granular-cost-attribution-for-amazon-bedrock",
    "title": "Introducing granular cost attribution for Amazon Bedrock",
    "summary": "In this post, we share how Amazon Bedrock\u0027s granular cost attribution works and walk through example cost tracking scenarios.",
    "author": "Ba\u0027Carri Johnson",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Announcements",
      "Artificial Intelligence",
      "AWS Cost and Usage Report",
      "AWS Cost Explorer"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/introducing-granular-cost-attribution-for-amazon-bedrock/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-17T22:04:15+00:00",
    "updatedAt": "2026-04-18T00:51:45.774017+00:00"
  },
  {
    "id": "e01e5a34-541f-46f3-a5f9-cc3b463f1053",
    "slug": "amazon-20260417-optimize-video-semantic-search-intent-with-amazon-nova-model-distillation-on-ama",
    "title": "Optimize video semantic search intent with Amazon Nova Model Distillation on Amazon Bedrock",
    "summary": "In this post, we show you how to use Model Distillation, a model customization technique on Amazon Bedrock, to transfer routing intelligence from a large teacher model (Amazon Nova Premier) into a much smaller student model (Amazon Nova Micro). This approach cuts inference cost by over 95% and reduces latency by 50% while maintaining the nuanced routing quality that the task demands.",
    "author": "Amit Kalawat",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Nova",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/optimize-video-semantic-search-intent-with-amazon-nova-model-distillation-on-amazon-bedrock/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-17T19:43:38+00:00",
    "updatedAt": "2026-04-18T00:51:45.774171+00:00"
  },
  {
    "id": "b88d3960-e478-40e7-8969-db48c8f97484",
    "slug": "amazon-20260417-power-video-semantic-search-with-amazon-nova-multimodal-embeddings",
    "title": "Power video semantic search with Amazon Nova Multimodal Embeddings",
    "summary": "In this post, we show you how to build a video semantic search solution on Amazon Bedrock using Nova Multimodal Embeddings that intelligently understands user intent and retrieves accurate video results across all signal types simultaneously. We also share a reference implementation you can deploy and explore with your own content.",
    "author": "Amit Kalawat",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Nova",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/power-video-semantic-search-with-amazon-nova-multimodal-embeddings/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-17T19:43:35+00:00",
    "updatedAt": "2026-04-18T00:51:45.774202+00:00"
  },
  {
    "id": "b072abca-e5ee-4f8f-a70d-03b7f1a8f499",
    "slug": "amazon-20260417-nova-forge-sdk-series-part-2-practical-guide-to-fine-tune-nova-models-using-data",
    "title": "Nova Forge SDK series part 2: Practical guide to fine-tune Nova models using data mixing capabilities",
    "summary": "This hands-on guide walks through every step of fine-tuning an Amazon Nova model with the Amazon Nova Forge SDK, from data preparation to training with data mixing to evaluation, giving you a repeatable playbook you can adapt to your own use case. This is the second part in our Nova Forge SDK series, building on the SDK introduction and first part, which covered kicking off customization experiments.",
    "author": "Gideon Teo",
    "category": "News",
    "tags": [
      "Amazon Machine Learning",
      "Amazon Nova",
      "Amazon SageMaker AI",
      "Artificial Intelligence",
      "Expert (400)"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/nova-forge-sdk-series-part-2-practical-guide-to-fine-tune-nova-models-using-data-mixing-capabilities/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-17T17:27:40+00:00",
    "updatedAt": "2026-04-18T00:51:45.774226+00:00"
  },
  {
    "id": "5ad9a858-fe85-498a-a1ff-d6eaa59e149a",
    "slug": "amazon-20260417-from-hours-to-minutes-how-agentic-ai-gave-marketers-time-back-for-what-matters",
    "title": "From hours to minutes: How Agentic AI gave marketers time back for what matters",
    "summary": "In this post, we share how AWS Marketing\u2019s Technology, AI, and Analytics (TAA) team worked with Gradial to build an agentic AI solution on Amazon Bedrock for accelerating content publishing workflows.",
    "author": "Ishara Premadasa",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/from-hours-to-minutes-how-agentic-ai-gave-marketers-time-back-for-what-matters/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-17T17:12:10+00:00",
    "updatedAt": "2026-04-18T00:51:45.774246+00:00"
  },
  {
    "id": "3464d350-579f-4fbf-b28d-274b9554ef06",
    "slug": "amazon-20260416-cost-efficient-custom-text-to-sql-using-amazon-nova-micro-and-amazon-bedrock-on",
    "title": "Cost-efficient custom text-to-SQL using Amazon Nova Micro and Amazon Bedrock on-demand inference",
    "summary": "In this post, we demonstrate two approaches to fine-tune Amazon Nova Micro for custom SQL dialect generation to deliver both cost efficiency and production ready performance.",
    "author": "Zeek Granston",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Nova",
      "Amazon SageMaker AI",
      "Artificial Intelligence",
      "Generative AI"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/cost-efficient-custom-text-to-sql-using-amazon-nova-micro-and-amazon-bedrock-on-demand-inference/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-16T17:43:03+00:00",
    "updatedAt": "2026-04-18T00:51:45.774272+00:00"
  },
  {
    "id": "e64da628-c177-496f-acb6-764baadbc2c1",
    "slug": "amazon-20260416-transform-retail-with-aws-generative-ai-services",
    "title": "Transform retail with AWS generative AI services",
    "summary": "Online retailers face a persistent challenge: shoppers struggle to determine the fit and look when ordering online, leading to increased returns and decreased purchase confidence. The cost? Lost revenue, operational overhead, and customer frustration. Meanwhile, consumers increasingly expect immersive, interactive shopping experiences that bridge the gap between online and in-store retail. Retailers implementing virtual try-on [\u2026]",
    "author": "Bhavya Chugh",
    "category": "News",
    "tags": [
      "Advanced (300)",
      "Amazon Bedrock",
      "Amazon Nova",
      "Amazon OpenSearch Service",
      "Amazon Rekognition"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/transform-retail-with-aws-generative-ai-services/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-16T17:39:56+00:00",
    "updatedAt": "2026-04-18T00:51:45.774289+00:00"
  },
  {
    "id": "6ef89746-0cb9-4dce-87a5-1e07b45e4bb4",
    "slug": "amazon-20260416-how-automated-reasoning-checks-in-amazon-bedrock-transform-generative-ai-complia",
    "title": "How Automated Reasoning checks in Amazon Bedrock transform generative AI compliance",
    "summary": "In this post, you\u0027ll learn why probabilistic AI validation falls short in regulated industries and how Automated Reasoning checks use formal verification to deliver mathematically proven results. You\u0027ll also see how customers across six industries use this technology to produce formally verified, auditable AI outputs, and how to get started.",
    "author": "Nafi Diallo",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Artificial Intelligence",
      "Generative AI",
      "Responsible AI"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/how-automated-reasoning-checks-in-amazon-bedrock-transform-generative-ai-compliance/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-16T17:34:42+00:00",
    "updatedAt": "2026-04-18T00:51:45.774306+00:00"
  },
  {
    "id": "e031da79-c9a1-40c4-b022-e99f236c3097",
    "slug": "amazon-20260415-create-rich-custom-tooltips-in-amazon-quick-sight",
    "title": "Create rich, custom tooltips in Amazon Quick Sight",
    "summary": "Today, we\u0027re announcing sheet tooltips in Amazon Quick Sight. Dashboard authors can now design custom tooltip layouts using free-form layout sheets. These layouts combine charts, key performance indicator (KPI) metrics, text, and other visuals into a single tooltip that renders dynamically when readers hover over data points.",
    "author": "Meshan Khosla",
    "category": "News",
    "tags": [
      "Amazon Quick Sight",
      "Business Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/create-rich-custom-tooltips-in-amazon-quick-sight/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-15T15:22:53+00:00",
    "updatedAt": "2026-04-18T00:51:45.774324+00:00"
  },
  {
    "id": "7b30df2d-9fbd-4243-ac2e-5c40794c6957",
    "slug": "amazon-20260415-accelerating-decode-heavy-llm-inference-with-speculative-decoding-on-aws-trainiu",
    "title": "Accelerating decode-heavy LLM inference with speculative decoding on AWS Trainium and vLLM",
    "summary": "In this post, you will learn how speculative decoding works and why it helps reduce cost per generated token on AWS Trainium2.",
    "author": "Yahav Biran",
    "category": "News",
    "tags": [
      "Advanced (300)",
      "Amazon Elastic Kubernetes Service",
      "Artificial Intelligence",
      "AWS Trainium",
      "Compute"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/accelerating-decode-heavy-llm-inference-with-speculative-decoding-on-aws-trainium-and-vllm/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-15T15:20:58+00:00",
    "updatedAt": "2026-04-18T00:51:45.774343+00:00"
  },
  {
    "id": "e5bb7c9e-aa08-4a3b-a781-86779fe598ec",
    "slug": "amazon-20260415-rede-mater-dei-de-sa-de-monitoring-ai-agents-in-the-revenue-cycle-with-amazon-be",
    "title": "Rede Mater Dei de Sa\u00FAde: Monitoring AI agents in the revenue cycle with Amazon Bedrock AgentCore",
    "summary": "This post is cowritten by Renata Salvador Grande, Gabriel Bueno and Paulo Laurentys at Rede Mater Dei de Sa\u00FAde. The growing adoption of multi-agent AI systems is redefining critical operations in healthcare. In large hospital networks, where thousands of decisions directly impact cash flow, service delivery times, and the risk of claim denials, the ability [\u2026]",
    "author": "Renata Salvador Grande",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Bedrock AgentCore",
      "Customer Solutions",
      "Foundational (100)",
      "Healthcare"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/rede-mater-dei-de-saude-monitoring-ai-agents-in-the-revenue-cycle-with-amazon-bedrock-agentcore/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-15T15:15:23+00:00",
    "updatedAt": "2026-04-18T00:51:45.774452+00:00"
  },
  {
    "id": "102223a1-964e-4627-a2be-a8a948a08c95",
    "slug": "amazon-20260414-navigating-the-generative-ai-journey-the-path-to-value-framework-from-aws",
    "title": "Navigating the generative AI journey: The Path-to-Value framework from AWS",
    "summary": "In this post, we introduce the Generative AI Path-to-Value (P2V) framework, a structured approach to help you move generative AI initiatives from concept to production and sustained value creation.",
    "author": "Nitin Eusebius",
    "category": "News",
    "tags": [
      "Advanced (300)",
      "Best Practices",
      "Generative AI",
      "Intermediate (200)",
      "Technical How-to"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/navigating-the-generative-ai-journey-the-path-to-value-framework-from-aws/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-14T18:19:43+00:00",
    "updatedAt": "2026-04-18T00:51:45.774488+00:00"
  },
  {
    "id": "277238ac-66c8-4193-be84-4f8a346ecbb3",
    "slug": "amazon-20260414-use-case-based-deployments-on-sagemaker-jumpstart",
    "title": "Use-case based deployments on SageMaker JumpStart",
    "summary": "We\u0027re excited to announce the launch of Amazon SageMaker JumpStart optimized deployments. SageMaker JumpStart improved deployments address the need for rich and straightforward deployment customization on SageMaker JumpStart by offering pre-defined deployment configurations, designed for specific use cases. Customers maintain the same level of visibility into the details of their proposed deployments, but now deployments are optimized for their specific use case and performance constraint.",
    "author": "Dan Ferguson",
    "category": "News",
    "tags": [
      "Amazon SageMaker",
      "Amazon SageMaker JumpStart",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/use-case-based-deployments-on-sagemaker-jumpstart/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-14T18:14:54+00:00",
    "updatedAt": "2026-04-18T00:51:45.774512+00:00"
  },
  {
    "id": "d1f7e9a1-2d75-4127-868b-8800c299180b",
    "slug": "amazon-20260414-best-practices-to-run-inference-on-amazon-sagemaker-hyperpod",
    "title": "Best practices to run inference on Amazon SageMaker HyperPod",
    "summary": "This post explores how Amazon SageMaker HyperPod provides a comprehensive solution for inference workloads. We walk you through the platform\u2019s key capabilities for dynamic scaling, simplified deployment, and intelligent resource management. By the end of this post, you\u2019ll understand how to use the HyperPod automated infrastructure, cost optimization features, and performance enhancements to reduce your total cost of ownership by up to 40% while accelerating your generative AI deployments from concept to production.",
    "author": "Vinay Arora",
    "category": "News",
    "tags": [
      "Amazon SageMaker HyperPod",
      "Artificial Intelligence",
      "Best Practices"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/best-practices-to-run-inference-on-amazon-sagemaker-hyperpod/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-14T18:09:22+00:00",
    "updatedAt": "2026-04-18T00:51:45.774535+00:00"
  },
  {
    "id": "4e3fc04f-d35b-4824-bce4-18077827e3d6",
    "slug": "amazon-20260414-how-guidesly-built-ai-generated-trip-reports-for-outdoor-guides-on-aws",
    "title": "How Guidesly built AI-generated trip reports for outdoor guides on AWS",
    "summary": "In this post, we walk through how Guidesly built Jack AI on AWS using AWS Lambda, AWS Step Functions, Amazon Simple Storage Service (Amazon S3), Amazon Relational Database Service (Amazon RDS), Amazon SageMaker AI, and Amazon Bedrock to ingest trip media, enrich it with context, apply computer vision and generative AI, and publish marketing-ready content across multiple channels\u2014securely, reliably, and at scale.",
    "author": "David Lord, Taylor Lord, Shiva Prasad, Anup Banasavalli Hiriyanagowda, Nikhil Chandra",
    "category": "News",
    "tags": [
      "Amazon API Gateway",
      "Amazon Bedrock AgentCore",
      "Amazon RDS",
      "Amazon SageMaker Autopilot",
      "Amazon Simple Notification Service (SNS)"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/how-guidesly-built-ai-generated-trip-reports-for-outdoor-guides-on-aws/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-14T18:02:56+00:00",
    "updatedAt": "2026-04-18T00:51:45.774558+00:00"
  },
  {
    "id": "7dcc8d78-4dd1-4038-9ef2-401280570b54",
    "slug": "amazon-20260414-spring-ai-sdk-for-amazon-bedrock-agentcore-is-now-generally-available",
    "title": "Spring AI SDK for Amazon Bedrock AgentCore is now Generally Available",
    "summary": "With the new Spring AI AgentCore SDK, you can build production-ready AI agents and run them on the highly scalable AgentCore Runtime. The Spring AI AgentCore SDK is an open source library that brings Amazon Bedrock AgentCore capabilities into Spring AI. In this post, we build an AI agent starting with a chat endpoint, then adding streaming responses, conversation memory, and tools for web browsing and code execution.",
    "author": "Andrei Shakirin",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Bedrock AgentCore",
      "Announcements",
      "Java"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/spring-ai-sdk-for-amazon-bedrock-agentcore-is-now-generally-available/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-14T12:40:47+00:00",
    "updatedAt": "2026-04-18T00:51:45.774607+00:00"
  },
  {
    "id": "8ac356f0-1e77-475b-af08-9c60bef70b74",
    "slug": "amazon-20260413-how-to-build-effective-reward-functions-with-aws-lambda-for-amazon-nova-model-cu",
    "title": "How to build effective reward functions with AWS Lambda for Amazon Nova model customization",
    "summary": "This post demonstrates how Lambda enables scalable, cost-effective reward functions for Amazon Nova customization. You\u0027ll learn to choose between Reinforcement Learning via Verifiable Rewards (RLVR) for objectively verifiable tasks and Reinforcement Learning via AI Feedback (RLAIF) for subjective evaluation, design multi-dimensional reward systems that help you prevent reward hacking, optimize Lambda functions for training scale, and monitor reward distributions with Amazon CloudWatch. Working code examples and deployment guidance are included to help you start experimenting.",
    "author": "Manoj Gupta",
    "category": "News",
    "tags": [
      "Advanced (300)",
      "Amazon Nova",
      "AWS Lambda",
      "Best Practices",
      "Technical How-to"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/how-to-build-effective-reward-functions-with-aws-lambda-for-amazon-nova-model-customization/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-13T16:01:18+00:00",
    "updatedAt": "2026-04-18T00:51:45.774637+00:00"
  },
  {
    "id": "5b5f4557-7577-45b5-b46d-ce00fef65b04",
    "slug": "amazon-20260409-understanding-amazon-bedrock-model-lifecycle",
    "title": "Understanding Amazon Bedrock model lifecycle",
    "summary": "This post shows you how to manage FM transitions in Amazon Bedrock, so you can make sure your AI applications remain operational as models evolve. We discuss the three lifecycle states, how to plan migrations with the new extended access feature, and practical strategies to transition your applications to newer models without disruption.",
    "author": "Saurabh Trikande",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Machine Learning",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/understanding-amazon-bedrock-model-lifecycle/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-09T17:33:28+00:00",
    "updatedAt": "2026-04-18T00:51:45.774659+00:00"
  },
  {
    "id": "d778f76c-a952-46c6-b118-1ef0b9adcf4d",
    "slug": "amazon-20260409-the-future-of-managing-agents-at-scale-aws-agent-registry-now-in-preview",
    "title": "The future of managing agents at scale: AWS Agent Registry now in preview",
    "summary": "Today, we\u0027re announcing AWS Agent Registry (preview) in AgentCore, a single place to discover, share, and reuse AI agents, tools, and agent skills across your enterprise.",
    "author": "Preethi C N",
    "category": "News",
    "tags": [
      "Amazon Bedrock",
      "Amazon Bedrock AgentCore",
      "Announcements",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/the-future-of-managing-agents-at-scale-aws-agent-registry-now-in-preview/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-09T17:28:20+00:00",
    "updatedAt": "2026-04-18T00:51:45.77468+00:00"
  },
  {
    "id": "1e9ed0fa-e368-4c5e-9eca-98011c662fdc",
    "slug": "amazon-20260409-embed-a-live-ai-browser-agent-in-your-react-app-with-amazon-bedrock-agentcore",
    "title": "Embed a live AI browser agent in your React app with Amazon Bedrock AgentCore",
    "summary": "This post walks you through three steps: starting a session and generating the Live View URL, rendering the stream in your React application, and wiring up an AI agent that drives the browser while your users watch. At the end, you will have a working sample application you can clone and run.",
    "author": "Sundar Raghavan",
    "category": "News",
    "tags": [
      "Advanced (300)",
      "Amazon Bedrock",
      "Amazon Bedrock AgentCore",
      "Amazon Machine Learning",
      "Artificial Intelligence"
    ],
    "contentType": "News",
    "sourceUrl": "https://aws.amazon.com/blogs/machine-learning/embed-a-live-ai-browser-agent-in-your-react-app-with-amazon-bedrock-agentcore/",
    "coverImageUrl": null,
    "publishedAt": "2026-04-09T17:06:07+00:00",
    "updatedAt": "2026-04-18T00:51:45.774706+00:00"
  }
]