Category: Uncategorized

This week, Amazon presented an academic paper at KDD 2017, the prestigious machine learning and big data conference. The paper shows Amazon’s research into tools that help us measure customers’ satisfaction and better learn how we can implement ideas that delight them. Specifically, we show an efficient bandit algorithm for multivariate testing, where one seeks […]

This is a guest post by Jaeyoung Choi of the International Computer Science Institute and Kevin Li of the University of California, Berkeley. This project demonstrates how academic researchers can leverage our AWS Cloud Credits for Research Program to support their scientific breakthroughs. Modern mobile devices can automatically assign geo-coordinates to images when you take pictures of […]

Apache MXNet (incubating) is a full-featured, highly scalable deep learning framework that supports creating and training state-of-the-art deep learning models. With it, you can create convolutional neural networks (CNNs), long short-term memory networks (LSTMs), and others. It supports a variety of languages, including, but not limited to, Python, Scala, R, and Julia. In this post, we showcase […]

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 […]

Have you ever wondered how you can use machine learning (ML) for translation? With our new framework, Sockeye, you can model machine translation (MT) and other sequence-to-sequence tasks. Sockeye, which is built on Apache MXNet, does most of the heavy lifting for building, training, and running state-of-the-art sequence-to-sequence models. In natural language processing (NLP), many […]

As AWS continues to support the Artificial Intelligence (AI) community with contributions to Apache MXNet and the release of Amazon Lex, Amazon Polly, and Amazon Rekognition managed services, we are also expanding our team of AI experts, who have one primary mission: To lower the barrier to AI for all AWS developers, making AI more accessible […]

In the past five years, deep neural networks have solved many computationally difficult problems, particularly in the field of computer vision. Because deep networks require a lot of computational power to train, often using tens of GPUs, many people assume that you can run them only on powerful cloud servers. In fact, after a deep […]

As AWS continues to support the Artificial Intelligence (AI) community with contributions to Apache MXNet and the release of Amazon Lex, Amazon Polly, and Amazon Rekognition managed services, we are also expanding our team of AI experts, who have one primary mission: To lower the barrier to AI for all AWS developers, making AI more accessible […]

You can now use Apache MXNet v0.10 and TensorFlow v1.1 with the AWS Deep Learning AMIs for Amazon Linux and Ubuntu. Apache MXNet announced version 0.10, available at http://mxnet.io, with significant improvements to documentation and tutorials including updated installation guides for running MXNet on various operating systems and environments, such as NVIDIA’s Jetson TX2. In […]

This is a guest post by Dana Van Aken, Andy Pavlo, and Geoff Gordon of Carnegie Mellon University. This project demonstrates how academic researchers can leverage our AWS Cloud Credits for Research Program to support their scientific breakthroughs. Database management systems (DBMSs) are the most important component of any data-intensive application. They can handle large […]