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What is SynapseAI?

Our accelerator hardware is meticulously designed to boost the performance and efficiency of deep learning while emphasizing developer usability. SynapseAI seeks to simplify the development journey by offering support for popular frameworks and models, enabling developers to utilize the tools they are already comfortable with and prefer. In essence, SynapseAI, along with its comprehensive suite of tools, is customized to assist deep learning developers in their specific workflows, empowering them to create projects that meet their individual preferences and needs. Furthermore, Habana-based deep learning processors not only protect existing software investments but also make it easier to develop innovative models, addressing the training and deployment requirements of a continuously evolving range of models influencing the fields of deep learning, generative AI, and large language models. This focus on flexibility and support guarantees that developers can excel in an ever-changing technological landscape, fostering innovation and creativity in their projects. Ultimately, SynapseAI's commitment to enhancing developer experience is vital in driving the future of AI advancements.

What is AWS Deep Learning Containers?

Deep Learning Containers are specialized Docker images that come pre-loaded and validated with the latest versions of popular deep learning frameworks. These containers enable the swift establishment of customized machine learning environments, thus removing the necessity to build and refine environments from scratch. By leveraging these pre-configured and rigorously tested Docker images, users can set up deep learning environments in a matter of minutes. In addition, they allow for the seamless development of tailored machine learning workflows for various tasks such as training, validation, and deployment, integrating effortlessly with platforms like Amazon SageMaker, Amazon EKS, and Amazon ECS. This simplification of the process significantly boosts both productivity and efficiency for data scientists and developers, ultimately fostering a more innovative atmosphere in the field of machine learning. As a result, teams can focus more on research and development instead of getting bogged down by environment setup.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
AWS Marketplace
AWS Neuron
Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EKS
Amazon Elastic Container Registry (ECR)
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
PyTorch
TensorFlow

Integrations Supported

Amazon Web Services (AWS)
AWS Marketplace
AWS Neuron
Amazon EC2 G5 Instances
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EKS
Amazon Elastic Container Registry (ECR)
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Habana Labs

Date Founded

2016

Company Location

Israel

Company Website

habana.ai/training-software/

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/machine-learning/containers/

Categories and Features

Deep Learning

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

Categories and Features

Container Management

Access Control
Application Development
Automatic Scaling
Build Automation
Container Health Management
Container Storage
Deployment Automation
File Isolation
Hybrid Deployments
Network Isolation
Orchestration
Shared File Systems
Version Control
Virtualization

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