Category: Amazon SageMaker

Learn how to architect an end-to-end pipeline that processes surgical video at the edge for de-identification, instrument detection, and surgical phase recognition—while using the cloud for model training and fleet management.

Learn how at the 2026 AWS Life Sciences Symposium, we brought together some of the most innovative companies in MedTech to share what it takes to build in this environment, and what becomes possible when you have the right data foundation and AI backbone.

In this post, we show how BridgeWise was able to overcome these challenges when developing their wealth AI platform with responsible AI in mind. BridgeWise is a global leader in AI for wealth.

In this blog post, learn how at the 2026 AWS Life Sciences Symposium earlier this month, leaders from Sanofi, Genentech, Noetik, Apheris, Bristol Myers Squibb, Memorial Sloan Kettering, and more demonstrated how they’re using agentic AI today to accelerate scientific discovery and improve patient outcomes.

This blog post will detail how Genmab, a leading biotech company, built an automated pipeline on AWS that handles whole-slide images from start to finish, cutting analysis time from hours to under 30 minutes per batch and reducing manual work by 80 percent. We will walk through how Genmab achieved this using AWS services and share the key lessons they learned along the way.

Learn how to transform collections operations for banks and fintechs with AI and ML on AWS The Business Challenge Financial institutions face mounting pressure in collections operations. Traditional debt collection operates on a simple playbook: aggressive phone calls, generic messaging, and rule-based workflows. Yet customers have unique capacity to pay (income, assets, competing obligations), willingness […]

Autonomous Vehicles (AV) development has been maturing and is advancing through clear architectural changes: AV 1.0: classical modular stacks (perception → prediction → planning → control) with hand-engineered interfaces AV 2.0: multi-modal LLM end-to-end (E2E) learned stacks that reduce modularity and improve scaling with data AV 3.0: end-to-end reasoning VLA (Vision–Language–Action) systems that perceive, reason, […]

Machine learning (ML) models operate directly in the critical path of ad delivery, influencing bidding, pricing, and campaign optimization under strict latency, reliability, and correctness requirements. These models are trained frequently on large volumes of historical auction data and produce deterministic artifacts that downstream serving systems rely on for consistent behavior in production. Historically, Kargo, […]

Ericsson rApp as a Service – Redefining Network Optimization with Agentic AI The future of telecom networks is autonomous, intelligent, and cloud driven. Ericsson and AWS are taking a significant leap forward by introducing Ericsson rApp as a Service (rApp aaS), a pioneering solution designed to accelerate the journey towards autonomous networks for Communication Service […]

Cloud technology enables sustainable energy pioneers to accelerate their transition to sustainable fuels, while maintaining operational excellence and their competitive advantage in an evolving energy landscape. We will explore how energy companies are leveraging Amazon Web Services (AWS) to revolutionize their supply chain for sustainable fuel and in particular hydrotreated vegetable oil (HVO). Energy companies […]