Generative Data Intelligence

Tag: Amazon FSx

Integrate HyperPod clusters with Active Directory for seamless multi-user login | Amazon Web Services

Amazon SageMaker HyperPod is purpose-built to accelerate foundation model (FM) training, removing the undifferentiated heavy lifting involved in managing and optimizing a large training...

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NetApp and AWS Deliver a Nine Times Performance Increase for Amazon FSx for NetApp ONTAP

New FSx for ONTAP scale-out file systems help organizations migrate or extend high-performance data-intensive workloads to the cloud SAN JOSE, Calif.–(BUSINESS WIRE)–NetApp® (NASDAQ: NTAP), the...

Introducing three new NVIDIA GPU-based Amazon EC2 instances | Amazon Web Services

Amazon Elastic Compute Cloud (Amazon EC2) accelerated computing portfolio offers the broadest choice of accelerators to power your artificial intelligence (AI), machine learning (ML),...

NetApp Reports First Quarter of Fiscal Year 2024 Results

Net revenues of $1.43 billion for the first quarter Introduced significant innovations, including NetAppâ„¢ ASA A-Series, a new line of all-flash SAN storage systems Announced the...

Build protein folding workflows to accelerate drug discovery on Amazon SageMaker | Amazon Web Services

Drug development is a complex and long process that involves screening thousands of drug candidates and using computational or experimental methods to evaluate leads....

Technology Innovation Institute trains the state-of-the-art Falcon LLM 40B foundation model on Amazon SageMaker | Amazon Web Services

This blog post is co-written with Dr. Ebtesam Almazrouei, Executive Director–Acting Chief AI Researcher of the AI-Cross Center Unit and Project Lead for LLM...

Analyze Amazon SageMaker spend and determine cost optimization opportunities based on usage, Part 4: Training jobs | Amazon Web Services

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. Since its introduction, we’ve helped hundreds of customers...

Use Snowflake as a data source to train ML models with Amazon SageMaker

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML...

Training large language models on Amazon SageMaker: Best practices

Language models are statistical methods predicting the succession of tokens in sequences, using natural text. Large language models (LLMs) are neural network-based language models...

Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic

Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to...

Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. At the server level, such training workloads demand faster compute...

Best practices for Amazon SageMaker Training Managed Warm Pools

Amazon SageMaker Training Managed Warm Pools gives you the flexibility to opt in to reuse and hold on to the underlying infrastructure for a...

Cloud-based medical imaging reconstruction using deep neural networks

Medical imaging techniques like computed tomography (CT), magnetic resonance imaging (MRI), medical x-ray imaging, ultrasound imaging, and others are commonly used by doctors for...

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