Category: Artificial Intelligence

Nathan Stone (NS) and Peter McLean (PM) are a team both professionally at Haven Power, a business energy supplier in Ipswich, UK, and also off the clock when they recently collaborated to create SafeHaven, the third place winner in the AWS DeepLens Challenge. SafeHaven was designed to protect vulnerable people, by enabling them to identify […]

Our customer had a problem: The manual classification of warranty claims was causing a bottleneck. These claims were based on a text field that explained the event in short detail. An example of that text looked something like this: “The plutonium-fueled nuclear reactor overheated on a hot day in Arizona’s recent inclement weather. Burn damage […]

Today Amazon SageMaker is launching several additional features to the built-in linear learner algorithm. Amazon SageMaker algorithms are designed to scale effortlessly to massive datasets and take advantage of the latest hardware optimizations for unparalleled speed. The Amazon SageMaker linear learner algorithm encompasses both linear regression and binary classification algorithms. These algorithms are used extensively in […]

The AWS Deep Learning AMIs come with latest pip packages of popular deep learning frameworks pre-installed in separate virtual environments so that developers can quickly get started with training deep learning models. The new version of the Deep Learning AMIs for Ubuntu and Amazon Linux now come with TensorFlow 1.6, built with advanced optimizations for […]

Matthew Clark is a software developer turned architect. He lives in Manchester in the north of England, and he’s soon to be the proud owner of a new kitchen. He’s also the creator of Dee – the DeepLens Educating Entertainer, which won second place in the AWS DeepLens Challenge. Dee is an example of how […]

What an opening round of March Madness basketball tournament games! We had a buzzer beater, some historic upsets, and exciting games throughout. The model built in our first blog post (Part 1) pointed out a few likely upset candidates (Loyola IL, Butler), but did not see some coming (Marshall, UMBC). I’m sure there will be […]

Natural human speech frequently includes audible breathing sounds as a speaker inhales or exhales during normal speaking. For example, when we speak, we generally take a breath at major pauses. Narrations without breathing sounds produced by Text-to-Speech (TTS) engines often the lack naturalness of a human narrator. Most TTS systems don’t include respiratory sounds in […]

Amazon SageMaker seq2seq offers you a very simple way to make use of the state-of-the-art encoder-decoder architecture (including the attention mechanism) for your sequence to sequence tasks. You just need to prepare your sequence data in recordio-protobuf format and your vocabulary mapping files in JSON format. Then you need to upload them to Amazon Simple […]

In this blog post, we’ll show you how you can mount an Amazon Elastic File System (EFS) to your Amazon SageMaker notebook instance. This is an easy way to store and access large datasets, and to share machine learning scripts from your SageMaker notebook instance. Amazon SageMaker notebooks provide fast access to your own instance running […]

When Alex Schultz first heard about the AWS DeepLens workshop in Dr. Matt Wood’s keynote address at re:Invent 2017, little did he know that a few months later he would be the first place winner of the AWS DeepLens Challenge Hackathon, owe his kids $400, and be the star of a blog post on the […]