Category: Amazon Machine Learning

Large language models (LLMs) and AI agents have revolutionized the orchestration of complex workflows by using their ability to interact with their environment and reason through actions. Agentic AI solutions bring a new level of flexibility and intelligence, unlike traditional machine learning (ML) methods, which often need complete retraining for new tasks and struggle to […]

The current state of telco operations: challenges and complexity Global telco operators today find themselves squeezed between surging network demand and stagnating revenue growth. According to PwC, global telecom service revenue rose by just 4.3% in 2023 and is projected to grow at a Compound Annual Growth Rate (CAGR) of only 2.9% through 2028—below inflation. […]

Water utilities worldwide are facing challenges in managing infrastructure, reducing water waste, and making sure of reliable service delivery. The traditional approaches of manual monitoring and reactive maintenance are no longer sufficient due to increasing water demand, need for uninterrupted service, regulatory requirements, and customer satisfaction. In this post, we explore how Amazon Web Services (AWS) AI […]

Every day, radiologists around the world face a growing challenge: dealing with an increasing number of medical images while racing to deliver faster results. Adhering to the latest American College of Radiology (ACR) Appropriateness Criteria can be difficult, especially when patient care is on the line. At Amazon Web Services (AWS), we’ve been thinking a […]

Lotte Homeshopping is a major South Korean retailer that was faced with an increasingly complex quality assurance (QA) process. Their fast-paced fashion division struggled with product approvals that required manual coordination across multiple channels. Partner questions went unanswered for too long, while QA agents struggled to keep up with repetitive inquiries. These mounting challenges created […]

Healthcare providers face a significant challenge today: the overwhelming volume of patient data spread across electronic health records. Before each patient visit, clinicians must review extensive medical histories, lab results, medications, and previous diagnoses—often under severe time constraints. This data overload can lead to missed insights, reduced face-to-face time with patients, and clinician burnout. We […]

Accessing workflow run logs and metrics through individual Amazon Web Services (AWS) HealthOmics APIs can make it difficult to have a birds-eye view over all your workflows and runs. Automating the ingestion of relevant HealthOmics workflow and run information can help you to be operationally efficient. Introduction Omics data has the potential to transform how […]

Introduction In today’s rapidly evolving telecommunications landscape, the management and optimization of Radio Access Networks (RANs) has become extraordinarily complex. As networks roll out 5G, traditional approaches to network management are proving increasingly inadequate. The sheer volume of data, the intricate interdependencies between network elements, and the demanding requirements for real-time optimization demand an innovative […]

Manufacturing companies face significant challenges with unplanned equipment downtime, which leads to lost revenue and production delays. Maintenance teams often struggle to detect early warning signs of equipment failure due to resource constraints and a lack of advanced analytics expertise. To address these challenges, we are excited to announce the general availability of native anomaly […]

Introduction The automotive industry continues to face challenges from the mounting complexity of software systems, with requirements encompassing functional needs such as electrification and autonomous driving alongside non-functional criteria such as performance and security. In our previous blog post, we explored how the framework of the Virtual Engineering Workbench (VEW), powered by AWS services and […]