Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Amazon EC2 G4 instances are specifically designed to enhance the performance of machine learning inference and applications that require high graphics capabilities. Users can select between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad) according to their requirements. The G4dn instances combine NVIDIA T4 GPUs with bespoke Intel Cascade Lake CPUs, ensuring an optimal mix of computational power, memory, and networking bandwidth. These instances are well-suited for tasks such as deploying machine learning models, video transcoding, game streaming, and rendering graphics. On the other hand, G4ad instances, equipped with AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, offer a budget-friendly option for handling graphics-intensive workloads. Both instance types utilize Amazon Elastic Inference, which permits users to add economical GPU-powered inference acceleration to Amazon EC2, thereby lowering costs associated with deep learning inference. They come in a range of sizes tailored to meet diverse performance demands and seamlessly integrate with various AWS services, including Amazon SageMaker, Amazon ECS, and Amazon EKS. Additionally, this versatility makes G4 instances an attractive choice for organizations looking to leverage cloud-based machine learning and graphics processing capabilities.

Description

Fortanix Confidential AI presents a comprehensive platform that allows data teams to handle sensitive datasets and deploy AI/ML models exclusively within secure computing environments, integrating managed infrastructure, software, and workflow orchestration to uphold privacy compliance across organizations. This service features on-demand infrastructure driven by the high-performance Intel Ice Lake third-generation scalable Xeon processors, enabling the execution of AI frameworks within Intel SGX and other enclave technologies while ensuring no external visibility. Moreover, it offers hardware-backed execution proofs and comprehensive audit logs to meet rigorous regulatory standards, safeguarding every aspect of the MLOps pipeline, from data ingestion through Amazon S3 connectors or local uploads to model training, inference, and fine-tuning, while also ensuring compatibility across a wide range of models. By leveraging this platform, organizations can significantly enhance their ability to manage sensitive information responsibly while advancing their AI initiatives.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AMD Radeon ProRender
Amazon EC2
Amazon EKS
Amazon Elastic Inference
Amazon S3
Amazon SageMaker
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
CUDA
Microsoft Azure
OpenGL

Integrations

AMD Radeon ProRender
Amazon EC2
Amazon EKS
Amazon Elastic Inference
Amazon S3
Amazon SageMaker
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
CUDA
Microsoft Azure
OpenGL

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/ec2/instance-types/g4/

Vendor Details

Company Name

Fortanix

Founded

2016

Country

United States

Website

www.fortanix.com/platform/confidential-ai

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

HPC

Product Features

Alternatives

Alternatives