AWS announced a raft of machine learning services at this week's re:Invent 2018 conference in Las Vegas, including new algorithms for SageMaker.
Amazon SageMaker was first announced last year and has since become one of the fastest growing services in AWS' growing arsenal, according to a blog by AWS' Shaun Ray, senior manager of developer relations.
The new SageMaker updates include SageMaker RL, which was designed to make it easier for developers to build, train and deploy machine learning tools, including low cost, automatic data labeling and reinforcement learning (RL). SageMaker RL is now generally available.
"Customers using Amazon SageMaker can use optimized algorithms offered in Amazon SageMaker, to run fully-managed MXNet, TensorFlow, PyTorch, and Chainer algorithms, or bring their own algorithms and models," Ray said. "When it comes to building their own machine learning model, many customers spend significant time developing algorithms and models that are solutions to problems that have already been solved."
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Labeling data is a labor-intensive job because it has largely been done by hand. Amazon SageMaker Ground Truth, which is now generally available, uses machine learning to pick up the work humans are doing in real time when they are creating labels. Once SageMaker Ground Truth has a subset of those data, it can automatically apply the labels. Building highly accurate data sets can reduce labeling costs by up to 70%, according to a blog by AWS Technical Evangelist Julien Simon.
AWS also announced its AWS Marketplace for Machine Learning, which is stocked with more than 150 algorithms and models that can be deployed directly to SageMaker. Developers can also sell their designs directly through AWS Marketplace.
“We want to help all of our customers embrace machine learning, no matter their size, budget, experience, or skill level,” said Swami Sivasubramanian, vice president, Amazon Machine Learning, in a prepared statement. “Today’s announcements remove significant barriers to the successful adoption of machine learning, by reducing the cost of machine learning training and inference, introducing new SageMaker capabilities that make it easier for developers to build, train, and deploy machine learning models in the cloud and at the edge, and delivering new AI services based on our years of experience at Amazon.”
On the somewhat lighter side, AWS also announced the AWS DeepRacer, which is currently under pre-order. AWS DeepRacer is a 1/18th scale all-wheel drive race car that comes with an HD video camera, monster truck tiers and on-board compute. The fully autonomous race car uses reinforcement learning models from SageMaker and allows the developers to race against each other for prizes in their own DeepRacer League.
All told, AWS announced 13 new machine learning capabilities and services that run across all layers of the machine learning stack, which will no doubt give developers plenty of space to work and play in.