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About

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Sagemaker instances or Amazon ECS tasks, to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, PyTorch and ONNX models. Inference is the process of making predictions using a trained model. In deep learning applications, inference accounts for up to 90% of total operational costs for two reasons. Firstly, standalone GPU instances are typically designed for model training - not for inference. While training jobs batch process hundreds of data samples in parallel, inference jobs usually process a single input in real time, and thus consume a small amount of GPU compute. This makes standalone GPU inference cost-inefficient. On the other hand, standalone CPU instances are not specialized for matrix operations, and thus are often too slow for deep learning inference.

About

Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

IT teams that need an advanced Infrastructure as a Service solution

Audience

Machine learning practitioners and researchers in search of a tool to implement privacy-preserving, decentralized model training across diverse devices and platforms

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 2006
United States
aws.amazon.com/machine-learning/elastic-inference/

Company Information

Flower
Founded: 2023
Germany
flower.ai/

Alternatives

Alternatives

Keepsake

Keepsake

Replicate
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Amazon Web Services (AWS)
MXNet
PyTorch
TensorFlow
Amazon EC2
Amazon EC2 G4 Instances
Android
Apple iOS
Docker
Google Cloud Platform
Hardskills
Hugging Face
JAX
Keras
Microsoft Azure
NVIDIA Jetson
NumPy
Python
Raspberry Pi OS
pandas

Integrations

Amazon Web Services (AWS)
MXNet
PyTorch
TensorFlow
Amazon EC2
Amazon EC2 G4 Instances
Android
Apple iOS
Docker
Google Cloud Platform
Hardskills
Hugging Face
JAX
Keras
Microsoft Azure
NVIDIA Jetson
NumPy
Python
Raspberry Pi OS
pandas
Claim Amazon Elastic Inference and update features and information
Claim Amazon Elastic Inference and update features and information
Claim Flower and update features and information
Claim Flower and update features and information