Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Vertex AI Reviews & Ratings
    783 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    10 Ratings
    Company Website
  • Chainguard Reviews & Ratings
    46 Ratings
    Company Website
  • RunPod Reviews & Ratings
    180 Ratings
    Company Website
  • Cloudflare Reviews & Ratings
    1,903 Ratings
    Company Website
  • Qloo Reviews & Ratings
    23 Ratings
    Company Website
  • Google Cloud Speech-to-Text Reviews & Ratings
    373 Ratings
    Company Website
  • JS7 JobScheduler Reviews & Ratings
    1 Rating
    Company Website
  • Paccurate Reviews & Ratings
    11 Ratings
    Company Website
  • Stonebranch Reviews & Ratings
    150 Ratings
    Company Website

What is IBM Distributed AI APIs?

Distributed AI is a computing methodology that allows for data analysis to occur right where the data resides, thereby avoiding the need for transferring extensive data sets. Originating from IBM Research, the Distributed AI APIs provide a collection of RESTful web services that include data and artificial intelligence algorithms specifically designed for use in hybrid cloud, edge computing, and distributed environments. Each API within this framework is crafted to address the specific challenges encountered while implementing AI technologies in these varied settings. Importantly, these APIs do not focus on the foundational elements of developing and executing AI workflows, such as the training or serving of models. Instead, developers have the flexibility to employ their preferred open-source libraries, like TensorFlow or PyTorch, for those functions. Once the application is developed, it can be encapsulated with the complete AI pipeline into containers, ready for deployment across different distributed locations. Furthermore, utilizing container orchestration platforms such as Kubernetes or OpenShift significantly enhances the automation of the deployment process, ensuring that distributed AI applications are managed with both efficiency and scalability. This cutting-edge methodology not only simplifies the integration of AI within various infrastructures but also promotes the development of more intelligent and responsive solutions across numerous industries. Ultimately, it paves the way for a future where AI is seamlessly embedded into the fabric of technology.

What is Azure Machine Learning?

Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.

Media

Media

Integrations Supported

APERIO DataWise
Azure AI Search
Azure Data Science Virtual Machines
Azure Kinect DK
Azure Marketplace
Azure Percept
BotCore
Cranium
Evvox
MLflow
Microsoft Azure
Microsoft Intelligent Data Platform
ModelOp
NVIDIA Triton Inference Server
New Relic
Omnisient
Red Hat OpenShift
Superwise
TensorFlow
Visual Studio Code

Integrations Supported

APERIO DataWise
Azure AI Search
Azure Data Science Virtual Machines
Azure Kinect DK
Azure Marketplace
Azure Percept
BotCore
Cranium
Evvox
MLflow
Microsoft Azure
Microsoft Intelligent Data Platform
ModelOp
NVIDIA Triton Inference Server
New Relic
Omnisient
Red Hat OpenShift
Superwise
TensorFlow
Visual Studio Code

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

IBM

Company Location

United States

Company Website

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

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/machine-learning/

Categories and Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

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

Popular Alternatives

Popular Alternatives

Vertex AI Reviews & Ratings

Vertex AI

Google
AWS Neuron Reviews & Ratings

AWS Neuron

Amazon Web Services
DeepSpeed Reviews & Ratings

DeepSpeed

Microsoft