AWS Machine Learning Blog

AWS Deep Learning AMIs Now Available in 4 New Regions: Beijing, Frankfurt, Singapore, and Mumbai

The AWS Deep Learning AMIs are now available in four new AWS Regions: China (Beijing) operated by Sinnet, Europe (Frankfurt), Asia Pacific (Singapore), and Asia Pacific (Mumbai).

The Amazon Machine Images (AMIs) provide provide machine learning practitioners with the infrastructure and tools to accelerate deep to quickly start experimenting with deep learning models. The AMIs come with pre-built packages of popular deep learning frameworks including Apache MXNet and Gluon, TensorFlow, Microsoft Cognitive Toolkit, Caffe, Caffe2, Theano, Torch, PyTorch, and Keras. In addition, to expedite development and model training, the AMIs are pre-configured with NVIDIA CUDA and cuDNN drivers, and are optimized for GPU acceleration on Amazon EC2 P2 and P3 instances.

Driving business value with deep learning

Companies are turning to deep learning to tackle a broad range of challenges. For example, media giant Condé Nast uses computer vision and natural language processing to monitor online content in order to better understand its customers. TuSimple, a leader in self-driving technology, uses deep learning algorithms to run driving simulations and train its autonomous systems. Instacart, an Internet-based grocery delivery service, uses deep learning to help their thousands of personal shoppers be more efficient through a scoring generator that helps customers shop based on prior purchases.

And many companies have accelerated their success with deep learning using the AWS Deep Learning AMIs:

Zendesk, which provides an online customer-support platform used by more than 87,000 customers worldwide, uses deep learning to improve the customer service experience. Using the AMIs and TensorFlow, Zendesk developed algorithms that power its Answer Bot product, allowing help desk agents to match customer queries with information to quickly find solutions to problems.

Matrix Analytics, a health care startup, was created with the goal of applying software algorithms to fight life-threatening diseases. Using the AMIs, the company has already made great strides in using machine learning to boost early cancer detection, predict malignancy risk from CT scans, and automate follow-up care for patients.

Zocdoc, another startup, uses deep learning to help patients find appropriate and timely medical care. With 100% of their systems on AWS, Zocdoc uses the AMIs for computer vision to extract information from member ID cards. Zocdoc also helps patients understand their health plan coverage and connects them to doctors who are available.

Germany-based SCDM Financial provides advanced analytics and AI capabilities to the world’s largest financial companies. Using the AMIs and TensorFlow, SCDM built a deep learning solution that extracts with high-value, actionable investment insights from vast quantities of market and financial data.

Now, with the availability of the AMIs in the newly-announced Regions, developers in these geographic locations can spin up a pre-built machine image to kick start or speed up deep learning projects.

The AMIs are also already available in the following Regions:

  • US East (Ohio)
  • US East (N. Virginia)
  • US West (Oregon)
  • Asia Pacific (Seoul)
  • Asia Pacific (Sydney)
  • Asia Pacific (Tokyo)
  • Europe (Ireland)

Get started with deep learning on AWS

Getting started with the AMIs is simple. We have three types of AWS Deep Learning AMIs available to support the various needs of machine learning practitioners. Visit our AMI selection guide, simple tutorials, and more deep learning resources to get started today.

Conda-based AMI Base AMI AMIs with source code
For developers who want pre-installed pip packages of deep learning frameworks in separate virtual environments For developers who want a clean slate to set up private deep learning engine repositories or custom builds of deep learning engines For developers who want pre-installed deep learning frameworks and their source code in a shared Python environment

Deep Learning AMI (Ubuntu)

Deep Learning AMI (Amazon Linux)

Deep Learning Base AMI (Ubuntu)

Deep Learning Base AMI (Amazon Linux)

For P3 instances:

Deep Learning AMI with Source Code (CUDA 9, Ubuntu)

Deep Learning AMI with Source Code (CUDA 9, Amazon Linux)

For P2 instances:

Deep Learning AMI with Source Code (CUDA 8, Ubuntu)

Deep Learning AMI with Source Code (CUDA 8, Amazon Linux)

For users in the Beijing Region, you can find the Deep Learning AMI of your choice in the Quick Start section of the Step 1: Choose an Amazon Machine Image (AMI) in the EC2 instance launch wizard.



About the Author

Cynthya Peranandam is a Principal Marketing Manager for AWS artificial intelligence solutions, helping customers use deep learning to provide business value. In her spare time she likes to run and listen to music.