AWS Storage Blog

Tag: HAQM Sagemaker

HAQM S3 Tables

Streamlining access to tabular datasets stored in HAQM S3 Tables with DuckDB

As businesses continue to rely on data-driven decision-making, there’s an increasing demand for tools that streamline and accelerate the process of data analysis. Efficiency and simplicity in application architecture can serve as a competitive edge when driving high-stakes decisions. Developers are seeking lightweight, flexible tools that seamlessly integrate with their existing application stack, specifically solutions […]

HAQM S3 Tables

Seamless streaming to HAQM S3 Tables with StreamNative Ursa Engine

Organizations are modernizing data platforms to use generative AI by centralizing data from various sources and streaming real-time data into data lakes. A strong data foundation, such as scalable storage, reliable ingestion pipelines, and interoperable formats, is critical for businesses to discover, explore, and consume data. As organizations modernize their platforms, they often turn to […]

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How Fetch reduced latency on image uploads using HAQM S3 Express One Zone

Fetch provides a convenient and rewarding platform for consumers to earn points and redeem them for various goods and services, making it an attractive option for those looking to maximize the value of their everyday purchases. Fetch’s users use a simple interface to upload their receipts for scanning and earn points for every receipt they […]

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Siemens builds Datalake2Go on AWS to analyze disparate data globally

Siemens is a technology company focused on industry, infrastructure, transport, and healthcare. From resource-efficient factories, resilient supply chains, and smart buildings and grids, to cleaner and more comfortable transportation and advanced healthcare, the company creates technology with purpose, adding real value for its customers. Siemens technology is everywhere, supporting the critical infrastructure and vital industries […]

Accelerating GPT large language model training with AWS services

GPT, or Generative Pre-trained Transformer, is a language model that has shown remarkable progress in various vertical industries. This technology has been used to generate human-like text in fields such as finance, healthcare, legal, marketing, and many others. In finance, GPT is being used to analyze financial data, generate reports, and assist with decision-making. In […]

High-performance cloud storage comes of age with HAQM FSx for Lustre

The rapid maturation of cloud tools for high-performance workloads in the past several years has made it possible for household names like T-Mobile, Toyota, and Rivian to move their high-performance analytics and AI/ML environments to the cloud. These are hugely data-intensive workflows that many companies five years ago believed would never be able to be […]

A gene-editing prediction engine with iterative learning cycles built on AWS

NRGene develops cutting-edge genomic analytics products that are reshaping agriculture worldwide. Among our customers are some of the biggest and most sophisticated companies in seed-development, food and beverages, paper, rubber, cannabis, and more. In the middle of 2020, NRGene joined a consortium of companies and academic institutions to build the best-in-class gene-editing prediction platform to […]

Using high-performance storage for machine learning workloads on Kubernetes

Organizations are modernizing their applications by adopting containers and microservices-based architectures. Many customers are deploying high-performance workloads on containers to power microservices architecture, and require access to low latency and high throughput shared storage from these containers. Because containers are transient in nature, these long-running applications require data to be stored in durable storage. HAQM FSx […]

New on the Machine Learning blog: Speed up training on HAQM SageMaker using HAQM FSx for Lustre and HAQM EFS file systems

Deploying analytics applications and machine learning models requires storage that can scale in capacity and performance to handle workload demands with high throughput and low-latency file operations. A common use case we’re seeing centers around data science teams doing some form of analytics (e.g machine learning, genomics). AWS offers two scalable, durable, highly available file […]