At re:Invent 2018, AWS announced Amazon Elastic Inference (EI), a new service that lets you attach just the right amount of GPU-powered inference acceleration to any Amazon EC2 instance. This is also available for Amazon SageMaker notebook instances and endpoints, bringing acceleration to built-in algorithms and to deep learning environments. In this blog post, I show how to use the models in the ONNX Model Zoo on GitHub to perform inference by using MXNet with Elastic Inference Accelerator (EIA) as a backend. Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75 percent. Amazon Elastic Inference provides support for Apache MXNet, TensorFlow, and ONNX models.
Have you ever wanted to work on machine learning challenges that will make a lasting impact on society and solve key problems that impact the experience of millions of Amazon customers? Amazon are looking for brilliant Machine Learning Scientists who have the passion to tackle tough problems to help inform a new product from the very early stages in the online grocery shopping space. Together with a multi-disciplinary team of scientists, engineers, economists, product managers, and subject domain experts you will help define our customer experience with machine learning at its core. You will define the research and experiment strategy with an iterative approach to create machine learning models and progressively improve the results over time. We are looking for candidates who thrive in a fast paced environments and want to invent the future.
You know when you're watching a movie or TV show set in the future and the world of tomorrow features video displays for phone calls in kitchens and living rooms? Well, the future is now with the Echo Show and it's on sale for $179.99 on Amazon. That's a $50 savings and the lowest price the online retailer has ever offered for this item. SEE ALSO: Amazon's Echo Auto is finally here Normally retailing for $229.99, the all-new Echo Show is the second generation of Amazon's best-selling smart video display. It's more than just your average smart display because it's powered with the Alexa voice assistant.
Amazon SageMaker makes it easier for any developer or data scientist to build, train, and deploy machine learning (ML) models. While it's designed to alleviate the undifferentiated heavy lifting from the full life cycle of ML models, Amazon SageMaker's capabilities can also be used independently of one another; that is, models trained in Amazon SageMaker can be optimized and deployed outside of Amazon SageMaker (or even out of the cloud on mobile or IoT devices at the edge). Conversely, Amazon SageMaker can deploy and host pre-trained models from model zoos, or other members of your team. In this blog post, we'll demonstrate how to deploy a trained Keras (TensorFlow or MXNet backend) or TensorFlow model using Amazon SageMaker, taking advantage of Amazon SageMaker deployment capabilities, such as selecting the type and number of instances, performing A/B testing, and Auto Scaling. Auto Scaling clusters are spread across multiple Availability Zones to deliver high performance and high availability.
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Did you catch (no pun intended) that Amazon commercial during the Super Bowl featuring Harrison Ford? You have to give Amazon credit for being able to make fun of themselves and joking about the sheer amount of devices and gadgets that feature the Alexa voice assistant. No, Amazon didn't create an Alexa-enabled dog collar for dogs or an Alexa-enabled electric toothbrush that can play your favorite podcasts, but the online retailer did make a microwave built with the voice assistant. Did you notice it in the ad? It's "hidden" at the very beginning of the TV spot.
With the introduction of its latest delivery drone iteration, the Scout, Amazon is once again reassuring the shopping public that automated package delivery services are just just around the corner. Just as they've been promising since 2013, when founder Jeff Bezos went on 60 Minutes and claimed that the technology would be commonplace within 5 years. But unfortunately for his predictions, the march of progress rarely sticks to a set schedule. Over the past half decade, a litany of companies worldwide have sought to build and deploy dozens of drone-based delivery services, with varying degrees of success. Last May, Ele.me, Alibaba's online meal ordering service, began using drones in Jinshan Industrial Park to get meals to mouths in just 20 minutes, a fraction of the time it'd take a human courier to drive through Shanghai traffic.
The maker of Equal sweeteners and the nutrition brand GNC are among the first to launch products through a program Amazon started last year to outsource the work. Mattress maker Tuft & Needle also recently created a brand called Nod exclusively for Amazon. Amazon's initiative is the latest example of the e-commerce giant flexing its muscles in order to offer the lowest prices and widest selection, as it seeks to cut into the market share of big-brand manufacturers. Also, they risk cannibalizing higher-margin sales of their main brands by offering comparable products under different labels. In exchange for creating exclusive products, the brands get help launching their products on Amazon.com,
A research paper and associated article published yesterday made claims about the accuracy of Amazon Rekognition. We welcome feedback, and indeed get feedback from folks all the time, but this research paper and article are misleading and draw false conclusions. This blog post shares details which we hope will help clarify several misperceptions and inaccuracies. People often think of accuracy as an absolute measure, such as a percentage score on a math exam, where each answer is either right or wrong. To understand, interpret, and compare the accuracy of machine learning systems, it's important to understand what is being predicted, the confidence of the prediction, and how the prediction is to be used, which is impossible to glean from a single absolute number or score.
Amazon's drone delivery service may be missing in action but the company has not given up on its dream of robots delivering parcels. It is launching Amazon Scout, a service employing six squat six-wheeled delivery robots, across Snohomish County, Washington, just north of its Seattle HQ. "These devices were created by Amazon, are the size of a small cooler and roll along sidewalks at a walking pace," the head of the Scout project, Sean Scott, wrote in a blogpost. "The devices will autonomously follow their delivery route but will initially be accompanied by an Amazon employee. "We developed Amazon Scout at our research and development lab in Seattle, ensuring the devices can safely and efficiently navigate around pets, pedestrians and anything else in their path." In 2013 Amazon's boss, Jeff Bezos, launched Amazon Prime Air and announced an intention to begin offering flying deliveries direct to the home within five years.