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About

Distributed AI is a computing paradigm that bypasses the need to move vast amounts of data and provides the ability to analyze data at the source. Distributed AI APIs built by IBM Research is a set of RESTful web services with data and AI algorithms to support AI applications across hybrid cloud, distributed, and edge computing environments. Each Distributed AI API addresses the challenges in enabling AI in distributed and edge environments with APIs. The Distributed AI APIs do not focus on the basic requirements of creating and deploying AI pipelines, for example, model training and model serving. You would use your favorite open-source packages such as TensorFlow or PyTorch. Then, you can containerize your application, including the AI pipeline, and deploy these containers at the distributed locations. In many cases, it’s useful to use a container orchestrator such as Kubernetes or OpenShift operators to automate the deployment process.

About

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

About

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

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

Developers interested in a solution offering data and AI algorithms to support their AI applications

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

Audience

Organizations interested in a powerful open source machine learning platform

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

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

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Reviews/Ratings

Overall 5.0 / 5
ease 1.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 4.5 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

IBM
United States
developer.ibm.com/apis/catalog/edgeai--distributed-ai-apis/Introduction/

Company Information

PyTorch
Founded: 2016
pytorch.org

Company Information

TensorFlow
Founded: 2015
United States
www.tensorflow.org

Alternatives

Alternatives

Alternatives

Vertex AI

Vertex AI

Google
Core ML

Core ML

Apple
Tinker

Tinker

Thinking Machines Lab
Create ML

Create ML

Apple
AWS Neuron

AWS Neuron

Amazon Web Services
MXNet

MXNet

The Apache Software Foundation
DeepSpeed

DeepSpeed

Microsoft
DeepSpeed

DeepSpeed

Microsoft

Categories

Categories

Categories

Machine Learning Features

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Integrations

Activeeon ProActive
Botify.cloud
DagsHub
Fabric for Deep Learning (FfDL)
Feast
Flower
GPUEater
Google Cloud Deep Learning VM Image
Keras
LiteRT
MegaETH
NVIDIA Triton Inference Server
Sesterce
Snitch AI
Spark NLP
SuperDuperDB
Swimm
TruEra
VIKTOR
teX.ai

Integrations

Activeeon ProActive
Botify.cloud
DagsHub
Fabric for Deep Learning (FfDL)
Feast
Flower
GPUEater
Google Cloud Deep Learning VM Image
Keras
LiteRT
MegaETH
NVIDIA Triton Inference Server
Sesterce
Snitch AI
Spark NLP
SuperDuperDB
Swimm
TruEra
VIKTOR
teX.ai

Integrations

Activeeon ProActive
Botify.cloud
DagsHub
Fabric for Deep Learning (FfDL)
Feast
Flower
GPUEater
Google Cloud Deep Learning VM Image
Keras
LiteRT
MegaETH
NVIDIA Triton Inference Server
Sesterce
Snitch AI
Spark NLP
SuperDuperDB
Swimm
TruEra
VIKTOR
teX.ai
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