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H2O.ai is a visionary leader in democratizing artificial intelligence (AI) by rapidly provisioning AI platforms that help businesses make better decisions. Our company’s SaaS platform, built on AWS, H2O AI Managed Cloud, enables businesses to build productive models and gain insights from their data quickly and easily. H2O.ai’s platform uses data and technology to improve: Speed: Our platform helps businesses to quickly develop and deploy AI/ML models, which leads to faster time to market and improved decision-making. Accuracy: Our platform uses a variety of techniques to improve the accuracy of AI/ML models, including automatic feature engineering and model selection. Scalability: Our platform can be scaled to handle large datasets and complex problems. Explainability: Our platform provides insights into how AI/ML models make decisions, which can help businesses to trust and adopt these models. This post demonstrates how we used Karpenter, an AWS open-sourced just-in-time Kubernetes autoscaler, and Bottlerocket, a secure, lightweight, purpose-built Linux-based operating system to run containers in the Amazon Elastic Kubernetes Service (Amazon EKS) clusters. This combined functionality, along with prefetching container images, helped us improve the compute provisioning and configuration time for our ML workloads by 100-fold... View the full article

Today, we are announcing availability of a Bottlerocket variant that supports NVIDIA GPU-based Amazon EC2 instance types on Amazon Elastic Container Services (Amazon ECS). Bottlerocket is a Linux-based operating system that is purpose-built to run container workloads. Customers can now benefit from using the same container-focused host operating system for both their non-GPU and GPU workloads while using ECS, including machine learning, video encoding, and streaming workloads. This helps customers standardize on a single operating system that utilizes the underlying specialized compute hardware. View the full article