AWS AI Blog

Tag: Deep Learning AMI

Building an Autonomous Vehicle, Part 4:  Using Behavioral Cloning with Apache MXNet for Your Self-Driving Car

In the first blog post of our autonomous vehicle series, you built your Donkey vehicle and deployed your pilot server onto an Amazon EC2 instance. In the second blog post, you learned to drive the Donkey car, and the Donkey car learned to self-drive. In the third blog post, you learned about the process of streaming telemetry […]

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New AWS Deep Learning AMIs for Machine Learning Practitioners

We’re excited to announce the availability of two new versions of the AWS Deep Learning AMI. The first is a Conda-based AMI with separate Python environments for deep learning frameworks created using Conda—a popular open source package and environment management tool. The second is a Base AMI with GPU drivers and libraries to deploy your own […]

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Getting Started with the AWS Deep Learning Conda and Base AMIs

Today AWS announced the availability of two new versions of the AWS Deep Learning AMI: a Conda-based AMI and a Base AMI. This post will walk you through the instructions and additional resources for making the most of your new AMIs. New Deep Learning AMI with Conda-managed environments The new Deep Learning AMIs for Amazon […]

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Announcing New AWS Deep Learning AMI for Amazon EC2 P3 Instances

We’re pleased to announce a new set of AWS Deep Learning AMIs, which come pre-installed with deep learning frameworks optimized for the NVIDIA Volta V100 GPUs in the new Amazon EC2 P3 instance family. The new P3 instances are perfect for deep learning, with eight NVIDIA Volta GPUs available in a single p3.16xlarge instance, which […]

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Build an Autonomous Vehicle Part 2: Driving Your Vehicle

This is the second blog post in our series that teaches you how to build a 1/16th scale autonomous car. You can also tune in to our Twitch streams to review concepts discussed in these blogs. After following along with us, you can bring your own car to race at the re:Invent Robocar Rally 2017, […]

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AWS Deep Learning AMI Now Supports PyTorch, Keras 2 and Latest Deep Learning Frameworks

Today, we’re pleased to announce an update to the AWS Deep Learning AMI. The AWS Deep Learning AMI, which lets you spin up a complete deep learning environment on AWS in a single click, now includes PyTorch, Keras 1.2 and 2.0 support, along with popular machine learning frameworks such as TensorFlow, Caffe2 and Apache MXNet. […]

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Build an Autonomous Vehicle on AWS and Race It at the re:Invent Robocar Rally

Autonomous vehicles are poised to take to our roads in massive numbers in the coming years. This has been made possible due to advances in deep learning and its application to autonomous driving. In this post, we take you through a tutorial that shows you how to build a remote control (RC) vehicle that uses […]

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Get Started with Deep Learning Using the AWS Deep Learning AMI

Whether you’re new to deep learning or want to build advanced deep learning projects in the cloud, it’s easy to get started by using AWS. The AWS Deep Learning AMIs, available in both Ubuntu and Amazon Linux versions, let you run deep learning applications in the cloud at any scale. The Amazon Machine Images (AMIs) […]

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The AWS Deep Learning AMI for Ubuntu is Now Available with CUDA 8, Ubuntu 16, and the Latest Versions of Deep Learning Frameworks

by Cynthya Peranandam | on | Permalink | Comments |  Share

The AWS Deep Learning AMI lets you build and scale deep learning applications in the cloud, at any scale. The AMI comes pre-installed with popular deep learning frameworks, to let you to train sophisticated, custom AI models, experiment with new algorithms, or to learn new skills and techniques. The latest release of the AWS Deep […]

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AWS and NVIDIA Expand Deep Learning Partnership at GTC 2017

by Joseph Spisak | on | Permalink | Comments |  Share

This year at NVIDIA’s GPU Technology Conference, AWS and NVIDIA partnered on multiple initiatives. The first is an exciting new Volta-based GPU instance that we think will completely change the face of the AI developer world through a 3x speedup on LSTM training. Second, we are announcing plans to train 100,000+ developers through the Deep […]

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