Favorite Using Amazon SageMaker Pipelines, organizations can automate their machine learning (ML) workloads and distribute them over many AWS accounts and AWS Regions as part of their Machine Learning Operations (MLOps) strategy. However, monitoring SageMaker Pipelines can become complex when they are distributed across many AWS environments. Developers and operations
Read More
Shared by AWS Machine Learning July 16, 2026
Favorite The integration of AI into real-world applications has long been hindered by a fundamental challenge: the disconnect between systems that can see, systems that can think, and systems that can act. Developers have struggled with complex integrations, managing multiple APIs, and creating custom solutions to bridge these gaps, resulting
Read More
Shared by AWS Machine Learning July 16, 2026
Favorite Document processing in real estate is complex and highly manual, impacting critical business decisions at scale, making it ripe for automation. Built Technologies, a real estate finance software provider, processes over $500B in real estate projects. The company deployed an AI-powered document processing engine on Amazon Bedrock and the
Read More
Shared by AWS Machine Learning July 16, 2026
Favorite Healthcare organizations need efficient scheduling solutions, and ScienceSoft’s AI voice assistant, powered by Amazon Nova Sonic and Amazon Bedrock Guardrails, shows how responsible AI can deliver that. The AI patient scheduling software market is one of healthcare’s fastest-growing technology segments. According to Grand View Research, this market is growing
Read More
Shared by AWS Machine Learning July 15, 2026
Favorite This post was written by Konstantin Lekh, Sasha Zinchuk, and Eugene Sergueev from Flo Health, and Liza (Elizaveta) Zinovyeva from AWS. In this post, we share how Flo Health’s engineering team turned a proof of concept (PoC) from the AWS Generative AI Innovation Center into a production-grade, AI-powered medical
Read More
Shared by AWS Machine Learning July 15, 2026
Favorite User experience (UX) testing faces multiple challenges that limit an organization’s ability to improve how users interact with their platforms. UX testing evaluates how easily and effectively users can navigate digital interfaces to complete intended tasks, such as finding products, creating accounts, or completing purchases. Unlike traditional Quality Assurance
Read More
Shared by AWS Machine Learning July 15, 2026
Favorite Production quality assurance (QA) workflows require more than individual test execution. You must organize tests into regression suites that run as a batch, and integrate them into continuous integration and continuous delivery (CI/CD) pipelines so that test results gate deployments automatically. In a previous post, we introduced QA Studio,
Read More
Shared by AWS Machine Learning July 15, 2026
Favorite Your prospects leave trails across multiple sources: a founder asks “What should I use for X?” in r/SaaS while their product launches on Hacker News. Stack Overflow questions spike. A GitHub repo crosses 2,400 stars. Each signal alone is noise, but correlated across sources, they reveal a prospect ready
Read More
Shared by AWS Machine Learning July 15, 2026
Favorite Google Images is turning 25. Here’s a look back at some major milestones — and new ways to explore and create visual content. View Original Source (blog.google/technology/ai/) Here.
Favorite Deploying generative AI models to production requires finding the right combination of instance type, serving container with settings, and optimization strategy. This process typically requires a long iteration cycle of optimization and manual benchmarking. In April 2026, Amazon SageMaker AI launched this inference recommendations, so customers can programmatically get
Read More
Shared by AWS Machine Learning July 14, 2026
Shared by AWS Machine Learning July 16, 2026
