This post was written with Dominic Catalano from Anyscale.
Organizations building and deploying large-scale AI models often face critical infrastructure challenges that can directly impact their bottom line: unstable training clusters that fail mid-job, inefficient resource utilization driving up costs, and complex distributed computing frameworks...
This post was co-written with Cyril Ovely from Vxceed.
Consumer packaged goods (CPG) companies face a critical challenge in emerging economies: how to effectively retain revenue and grow customer loyalty at scale. Although these companies invest 15–20% of their revenue in trade promotions and retailer...
Machine learning operations (MLOps) is the combination of people, processes, and technology to productionize ML use cases efficiently. To achieve this, enterprise customers must develop MLOps platforms to support reproducibility, robustness, and end-to-end observability of the ML use case’s lifecycle. Those platforms are based...
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies through a single API, along with capabilities to build generative AI applications with security, privacy, and responsible AI.
Batch inference in Amazon Bedrock is for...
Amazon QuickSight data stories support global customers by transforming complex data into interactive narratives for faster decisions. However, manual creation of multiple daily data stories consumes significant time and resources, delaying critical decisions and preventing teams from focusing on valuable analysis.
Each organization has multiple...
This post is cowritten with Gayathri Rengarajan and Harshit Kumar Nyati from PowerSchool.
PowerSchool is a leading provider of cloud-based software for K-12 education, serving over 60 million students in more than 90 countries and over 18,000 customers, including more than 90 of the top...
