Tag: Channy Yun

In March 2023, AWS and NVIDIA announced a multipart collaboration focused on building the most scalable, on-demand artificial intelligence (AI) infrastructure optimized for training increasingly complex large language models (LLMs) and developing generative AI applications. We preannounced Amazon Elastic Compute Cloud (Amazon EC2) P5 instances powered by NVIDIA H100 Tensor Core GPUs and AWS’s latest networking and scalability that will deliver up to 20 exaflops of compute performance for building and training the largest machine learning (ML) models. This announcement is the product of more than a decade of collaboration between AWS and NVIDIA, delivering the visual computing, AI, and high performance computing (HPC) clusters across the Cluster GPU (cg1) instances (2010), G2 (2013), P2 (2016), P3 (2017), G3 (2017),…

The Data Centered: Eastern Oregon, a five-part mini-documentary series looking at the real-life impact of the more than $15 billion investment AWS has made in the local community, and how the company supports jobs, generates economic growth, provides skills training and education, and unlocks opportunities for local businesses suppliers. Last week, I watched a new episode introducing the Data Center Technician training program offered by AWS to train people with little or no previous technical experience in the skills they need to work in data centers and other information technology (IT) roles. This video reminded me of my first days of cabling and transporting servers in data centers. Remember, there are still people behind cloud computing. Last Week’s Launches Here…

At AWS re:Invent 2022, Adam Selipsky, CEO of AWS, explained high performance computing (HPC) workloads typically can either be compute-intensive, compute- and networking-intensive, or data- and memory-intensive in his keynote. Compute workloads include weather forecasting, computational fluid dynamics, and financial options pricing. To help with this, you have Amazon EC2 Hpc6a instances, which deliver up to 65 percent better price performance over comparable compute optimized x86-based instances. Other HPC workloads require modeling the performance of complex structures—things like wind turbines, concrete buildings, and industrial equipment. Without enough data and memory, these models can take days or weeks to run in a cost-effective way. The Amazon EC2 Hpc6id instance is designed to deliver leading price performance for data and memory-intensive HPC…

At AWS re:Invent 2022, we previewed Amazon SageMaker geospatial capabilities, allowing data scientists and machine learning (ML) engineers to build, train, and deploy ML models using geospatial data. Geospatial ML with Amazon SageMaker supports access to readily available geospatial data, purpose-built processing operations and open source libraries, pre-trained ML models, and built-in visualization tools with Amazon SageMaker’s geospatial capabilities. During the preview, we had lots of interest and great feedback from customers. Today, Amazon SageMaker geospatial capabilities are generally available with new security updates and additional sample use cases. Introducing Geospatial ML features with SageMaker Studio To get started, use the quick setup to launch Amazon SageMaker Studio in the US West (Oregon) Region. Make sure to use the default…