Amazon Web Services (AWS) has launched a fully autonomous 1/18th scale race car driven by reinforced learning. Making the announcement on Wednesday at re:Invent, CEO Andy Jassy explained that AWS DeepRacer is a fully autonomous race car designed to get customers going with reinforcement learning. Reinforcement Learning is one of the technologies used to make self-driving cars a reality and Jassy touted DeepRacer as the best way to go "hands-on" to learn about it. On the hardware and software side, the DeepRacer boasts an Intel Atom processor, a 4 megapixel camera with 1080p resolution, fast WiFi, multiple USB ports, and about two hours of battery life. In a statement, AWS explained the Atom processor runs Ubuntu 16.04 LTS, Robot Operating System, and the Intel OpenVino computer vision toolkit.
Two years ago, Alphabet researchers made computing history when their artificial intelligence software AlphaGo defeated a world champion at the complex board game Go. Amazon now hopes to democratize the AI technique behind that milestone--with a pint-size self-driving car. The 1/18th-scale vehicle is called DeepRacer, and it can be preordered for $249; it will later cost $399. It's designed to make it easier for programmers to get started with reinforcement learning, the technique that powered AlphaGo's victory and is loosely inspired by how animals learn from feedback on their behavior. Although the approach has produced notable research stunts, such as bots that can play Go, chess, and complicated multiplayer electronic games, it isn't as widely used as the pattern-matching learning techniques used in speech recognition and image analysis.
Amazon is set to open up the machine-learning algorithms that power its recommendations and forecasts to Amazon Web Services customers in a bid to make it easier to adopt the new technology. The AWS annual Re:Invent conference in Las Vegas also saw the introduction of new tools to help companies manage their data, improve their security and introduce blockchain services. In a keynote speech that referenced Fortnite, the Beatles, Elvis Presley, the Clash and Queen, chief executive Andy Jassy announced a total of 20 new products and services that it would allow its customers to use the company's smart technology to get started in machine learning, making it easier for its customers to get started and customise the new technology to meet their needs. "We're entering this golden age of what's going to be possible," he said. "The problem with machine learning today is it's still pretty early for most companies in terms of knowing what they want to do with machine learning and having the people to build and tune the models.That's why you see us spending so much time, energy and investment and so many releases in machine learning and AI in the past couple of years."
This week in Las Vegas, Amazon rolled out dozens of new features, upgrades, and new products at AWS re:Invent. Here's a quick roundup of news out of the annual conference that may matter to members of the AI community. A disproportionate amount of money is spent on inference versus training when it comes to AI models, AWS CEO Andy Jassy said, and GPUs can be terribly inefficient. To address these issues, Amazon custom-designed a chip named Inferentia due out next year and created Elastic Inference, a service that identifies parts of a neural network that can benefit from acceleration. To speed up training of AI models, Amazon introduced AWS-Optimized TensorFlow, which can train a model with the ResNet-50 benchmark in 14 minutes.
It already has quite a few smart code confections: Rekognition, Lex, Polly, Transcribe, Comprehend, Translate, Sagemaker, and Greengrass, among others. At its re:Invent gathering in Las Vegas today, AWS threw a handful of new flavors into the mix, among them: Elastic Inference, SageMaker GroundTruth, SageMaker RL, Amazon SageMaker Neo, Personalize, Forecast, Textract, and Comprehend Medical. It also teased a machine-learning inference chip called Inferentia, and a small radio-controlled car called DeepRacer for executing autonomous driving models in the real-world and terrifying pets. It's a 1/18th scale race car that's ostensibly intended to help people understand and implement reinforcement learning. It may also help with customer acquisition, retention, and spending.