Category: Artificial Intelligence

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 […]

Domino Data Lab is an AWS Partner Network (APN) partner that provides a central system of record for data science activity across an organization. The Domino solution delivers orchestration for all data science artifacts, including AWS infrastructure, data and services. As part of the solution, Domino’s platform leverages the scale, security, reliability, and cost-effectiveness of […]

Companies from different industries use data to help their Artificial Intelligence (AI) and Machine Learning (ML) systems make intelligent decisions. For ML systems to work well, it is crucial to make sure that the massive datasets used for training ML models are of the highest quality, minimizing noise that can contribute to less-than-optimal performance. Processing […]

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 […]

Training Machine Learning models involves multiple steps, it gets more complex and time consuming when the size of the data set for training is in the range of 100s of GBs. Data Scientists run through large number of experiments and research which includes testing and training large number of models. Kubeflow provides various ML capabilities […]

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 […]

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 […]

As AWS Solutions Architects, we help customers understand and plan AWS architectures that meet their business goals while remaining scalable, cost effective, secure, and reliable. One common pattern that comes up frequently is the desire to move from manual or polling-based strategies to reliable events processing, also known as event-driven architecture (EDA). This approach dovetails […]

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. Amazon FSx […]

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 […]