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What is Fabric for Deep Learning (FfDL)?

Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have greatly improved the ease with which deep learning models can be designed, trained, and utilized. Fabric for Deep Learning (FfDL, pronounced "fiddle") provides a unified approach for deploying these deep-learning frameworks as a service on Kubernetes, facilitating seamless functionality. The FfDL architecture is constructed using microservices, which reduces the reliance between components, enhances simplicity, and ensures that each component operates in a stateless manner. This architectural choice is advantageous as it allows failures to be contained and promotes independent development, testing, deployment, scaling, and updating of each service. By leveraging Kubernetes' capabilities, FfDL creates an environment that is highly scalable, resilient, and capable of withstanding faults during deep learning operations. Furthermore, the platform includes a robust distribution and orchestration layer that enables efficient processing of extensive datasets across several compute nodes within a reasonable time frame. Consequently, this thorough strategy guarantees that deep learning initiatives can be carried out with both effectiveness and dependability, paving the way for innovative advancements in the field.

What is Fabnami?

Conduct a comprehensive assessment of 3D meshes to identify any topological or geometric defects that may hinder effective 3D printing. Fabnami is designed to be customizable, accommodating the requirements of different professional 3D printers and materials. Pricing can be determined by various criteria, including model volume, support material volume, bounding box dimensions, model convexity (which facilitates nesting), and printing duration. Prior to deployment, Fabnami is integrated with your existing tools and tailored to suit your 3D printers, pricing models, and operational workflows, allowing you to streamline processes without disrupting current operations. Utilizing a range of Amazon Web Services such as Lambda, Fabnami guarantees dependable, scalable, and high-performance data processing, capable of managing virtually any workload effectively. You can easily establish business processes that adapt depending on factors like order size, material selection, or customer identification. For example, automated quotations can be provided for smaller orders, while larger ones may necessitate a manual inspection to ensure precision and thoroughness. This adaptability empowers businesses to efficiently navigate their workflows while accommodating a variety of order types and complexities. Ultimately, Fabnami enhances productivity while providing tailored solutions to meet diverse needs.

Media

Media

Integrations Supported

Caffe
Kubernetes
PyTorch
TensorFlow
Torch

Integrations Supported

Caffe
Kubernetes
PyTorch
TensorFlow
Torch

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

Date Founded

1911

Company Location

United States

Company Website

developer.ibm.com/open/projects/fabric-for-deep-learning-ffdl/

Company Facts

Organization Name

In Numero

Company Location

Switzerland

Company Website

fabnami.com

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

eCommerce

CRM
Catalog Management
Channel Management
Customer Accounts
Data Security
Email Marketing
Inventory Management
Kitting
Loyalty Program
Mobile Access
Multi-Store Management
Order Management
Product Configurator
Promotions Management
Returns Management
Reviews Management
SEO Management
Shopping Cart
Templates

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