Automotive guide to re:Invent 2020 announcements
At time of publish, there have been over 100 new product announcements made at this year’s re:Invent. In the following guide, we’ll review the major launches and preview announcements that will impact our Automotive customers in 2021 by providing innovative services to aid in the development of connected vehicles, autonomous driving and ADAS systems, digital customer engagement and manufacturing. For a list all re:Invent launches, see a full list here.
AWS Automotive hosted four breakout sessions, two on-air live sessions, and participated in many other automotive-related sessions in different product tracks. Please check out our automotive guide for a full list of content sessions with links to watch on-demand. Tune in starting January 12th 2021 for even more automotive content at re:Invent!
Partnerships and Announcements
BlackBerry and AWS join forces to develop an intelligent vehicle data platform named BlackBerry IVY. This new strategic alliance helps automakers and automotive suppliers more rapidly develop valuable customer experiences and unlock new revenue streams and business models.
The BMW Group and AWS announced a comprehensive strategic collaboration to further accelerate the automaker’s pace of innovation by placing data and analytics at the center of its decision-making. AWS and The BMW Group will jointly develop innovative cloud-enabled solutions and upskill up to 5,000 BMW Group-affiliated software engineers in cloud technologies.
AWS for Industrial –this is a new initiative that features new and existing services and solutions from AWS and AWS Partners to simplify the process for automotive industrial customers to build or deploy IoT, AIML, analytics and edge solutions to achieve improvements in operational efficiency, quality and agility.
AWS Product and Service Launches
Amazon EKS Distro and Amazon EKS Anywhere: Amazon Elastic Kubernetes Service (EKS) Distro is the same Kubernetes distribution used by Amazon EKS for customers who create Kubernetes clusters manually wherever their applications are deployed.
Amazon EKS Anywhere is a new deployment option for Amazon EKS that enables you to easily create and operate Kubernetes clusters on-premises, including on your own virtual machines (VMs) and bare metal servers. EKS Anywhere provides an installable software package for creating and operating Kubernetes clusters on-premises and automation tooling for cluster lifecycle support.
- Automotive Benefits in Autonomous Driving and Connected Mobility: For customers requiring deployments in regions where AWS does not have a presence, or where local installations are required due to data residency regulations. This is also useful for deployment consistency of connected mobility solutions or autonomous development.
AWS Wavelength New Zones: AWS Wavelength and Verizon 5G Edge bring the power of the world’s leading cloud closer to mobile and connected devices at the edge of the Verizon 5G Ultra Wideband network. AWS Wavelength embeds AWS compute and storage services at the edge of communications service providers’ 5G networks while providing seamless access to cloud services running in an AWS Region. By doing so, AWS Wavelength minimizes the latency and network hops required to connect from a 5G device to an application hosted on AWS. Among the many ultra-low latency use cases that AWS Wavelength enables are 5G applications for smart manufacturing, industrial automation, autonomous driving, and applications that deliver interactive and immersive experiences, like game streaming, virtual reality, and in-venue experiences for live events. We announced the availability of a new AWS Wavelength Zone on Verizon’s 5G Ultra Wideband network in Las Vegas. Wavelength Zones are now available in eight cities, including the seven previously announced cities of Boston, San Francisco Bay Area, New York City, Washington DC, Atlanta, Dallas, and Miami.
- Automotive Benefits in Autonomous Driving and Connected Mobility: Low latency cellular network edge applications like C-V2X for safety messaging to/from infrastructure/VRUs and ADS/ADAS snapshots for raw data bursting to edge locations at high bandwidths for offload. Additional use cases include off-loading HPC transactions, supporting autonomous depot maneuvering for fleet vehicles to and from parking spaces to EV charging stations and loading docks, as well as Autonomous Valet parking for vehicles without autonomous technology on-board.
New Features in Amazon Connect: Amazon Connect is an easy-to-use, omnichannel cloud contact center that helps provide superior customer service at a lower cost. Amazon Connect Wisdom provides contact center agents with the information they need to quickly solve customer issues using machine learning (ML) to drastically reduce the time agents spend searching for answers. Contact Lens for Amazon Connect provides a set of ML capabilities integrated into Amazon Connect that analyze call recordings or customer sentiment, trends, and compliance of conversations. Now, Contact Lens supports real-time call analytics capabilities, enabling you to detect customer issues during live calls and resolve them faster.
- Automotive Benefits in Digital Customer Engagement: Support for vehicle concierge services, leasing and finance support, to general customer support about vehicle features and the buying experience. Recently announced is Amazon Connect integration with Salesforce, furthering our capabilities to help Automotive CX.
AWS Audit Manager: AWS Audit Manager is a new service that helps you continuously audit your AWS usage to simplify how you assess risk and compliance with regulations and industry standards. Audit Manager automates evidence collection to make it easier to assess whether your policies, procedures, and activities, also known as controls, are operating effectively. When it is time for an audit, AWS Audit Manager helps you manage stakeholder reviews of your controls and enables you to build audit-ready reports with much less manual effort and in less time.
- Automotive Benefits for Connected Mobility, Autonomous Vehicle Development, and Digital Customer Engagement: Offers pre-built, customizable frameworks to map usage to controls like Center for Internet Security (CIS) and General Data Protection Regulation (GDPR).
AWS Tranium: AWS Trainium is high performance ML chip, custom designed by AWS to provide the best price performance for training machine learning models in the cloud. The Trainium chip is specifically optimized for deep learning training workloads for applications including image classification, semantic search, translation, voice recognition, natural language processing, and recommendation engines.
- Automotive Benefits in Autonomous Vehicles and Digital Customer Engagement: AWS Trainium is a very cost-effective chip designed to train ML models for image classification (labeling in AV), semantic searching (labeling in AV), voice recognition (digital personal assistants), NLP (digital personal assistants), and recommendation engines (for presenting content in B2C transactions).
Compute and Machine Learning Services for ADAS/ADS and ML Workloads
Amazon SageMaker Pipelines: Amazon SageMaker Pipelines is the first purpose-built, easy-to-use continuous integration and continuous delivery (CI/CD) service for machine learning. With SageMaker Pipelines, you can create, automate, and manage end-to-end ML workflows at scale.
Amazon SageMaker Clarify: Amazon SageMaker Clarify detects potential bias during data preparation, after training, and in your deployed model by examining attributes you specify. For instance, you can check for bias related to age in your initial dataset or in your trained model and receive a detailed report that quantifies different types of possible bias. SageMaker Clarify also includes feature importance graphs that help you explain model predictions and produces reports that can be shared to help answer questions about model predictions from business leaders, auditors, and customers.
- Automotive Benefits: SageMaker Clarify helps anywhere customers are developing machine learning models and seeking to understand why they make the predictions and inferences they make. It helps to understand what factors are influencing the model to perform the way it does. For example, it could help provide insight into why a path planning algorithm made a right turn vs. stopping to avoid a collision.
Amazon SageMaker Edge Manager: Amazon SageMaker Edge Manager optimizes models to run faster on target devices and provides model management for edge devices, so customers can prepare, run, monitor, and update deployed machine learning models across fleets of devices at the edge. Amazon SageMaker Edge Manager gives customers the ability to cryptographically sign their models, upload prediction data from their devices to Amazon SageMaker for monitoring and analysis, and view a dashboard that tracks and visually reports on the operation of the deployed models within the Amazon SageMaker console. SageMaker Edge Manager extends capabilities that were previously only available in the cloud by sampling models’ input and output data from edge devices and sending it to the cloud, so developers can continuously improve model quality by using Amazon SageMaker Model Monitor for drift detection, then relabel the data and retrain the models.
- Automotive Benefits: Optimizes the deployment of machine learning models to vehicle edge runtimes and provides a continuous loop of raw data feedback going into the model, compared to its output and uploading this information to the cloud for continuous improvement.
Amazon SageMaker Data Wrangler: Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for ML from weeks to minutes. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface. Using SageMaker Data Wrangler’s data selection tool, you can choose the data you want from various data sources and import it with a single click.
- Automotive Benefits: Improves the wrangling of data making is simpler to prepare for machine learning in the SageMaker integrated development environment shaving weeks of time to minutes. An example in AWS’s Predictive Maintenance solution is manipulating the data into balanced sets and formatting it for training the model.
Amazon Lookout for Metrics: Amazon Lookout for Metrics automatically connects to popular databases and SaaS applications to continuously monitor metrics that you care about, and sends you alerts as soon as anomalies are detected. When it finds anomalies, Amazon Lookout for Metrics immediately sends you alerts, groups anomalies that might be related to the same event, and helps you identify the root cause so that you can fix an issue or quickly react to opportunities. It also ranks anomalies in the order of severity, so that you can focus on what matters the most, and lets you to tune the results by providing feedback based on your knowledge about your business, and uses your feedback to improve the accuracy of results over time.
- Automotive Benefits: Discovering anomalies in your connected vehicle fleet data, electric vehicle charging stations, battery test fleets, and dips in fuel/power consumption linked to tire pressure.
Announcing: AWS for Industrial
AWS for Industrial: This is a new initiative that features new and existing services and solutions from AWS and our AWS Partners, which are built specifically for developers, engineers and operators at industrial companies, including Automotive. This initiative simplifies the process for customers to build or deploy innovative Internet of Things (IoT), Artificial Intelligence (AI), ML, analytics and edge solutions to achieve step change improvements in operational efficiency, quality, and agility. For more information about AWS for Industrial, here is a detailed blog post.
Use machine data to predict when equipment will require maintenance:
- Amazon Lookout for Equipment: Amazon Lookout for Equipment is an anomaly detection service for industrial machinery. It uses data from equipment tags and sensors, and historical maintenance events to detect abnormal equipment behavior.
- Amazon Monitron: Amazon Monitron is an end-to-end system that detects abnormal behavior in industrial machinery, such as motors, gearboxes, fans, and pumps, enabling customers to implement predictive maintenance and reduce unplanned downtime. It includes sensors to measure vibration and temperature, a gateway device, and a mobile app to set up devices and track and review potential failures in equipment.
Use computer vision to improve process, identify bottle necks, and detect anomalies:
- Amazon Lookout for Vision: Amazon Lookout for Vision enables customers to spot industrial product defects and anomalies using computer vision, accurately and at scale. Customers can automate real-time visual inspection for processes like quality control and defect assessment by analyzing images from cameras that monitor the process line. Amazon Lookout for Vision identifies missing components, damage to products, irregularities in production lines, and even minuscule defects in silicon wafers such as a missing capacitor on a printed circuit board.
- AWS Panorama: AWS Panorama is a machine learning appliance and SDK, which enable customers to add computer vision (CV) to existing on-premises cameras or to new Panorama enabled cameras. It gives customers the ability to make real-time decisions to improve operations, automate monitoring of visual inspection tasks, find bottlenecks in industrial processes, and assess worker safety within facilities.
- The AWS Panorama Appliance turns existing onsite cameras into powerful edge devices with the processing power to analyze video feeds from multiple cameras in parallel, and generate highly accurate predictions within milliseconds. With a dust resistant and waterproof appliance, customers can install devices in different environments without compromising functionality.
- Panorama SDK: The AWS Panorama SDK enables hardware partners to build new Panorama enabled devices that run more meaningful CV models at the edge, and offer a selection of edge devices to satisfy different use cases. New Panorama enabled devices, coming soon from AWS Partners including ADLINK Technology, Axis Communications, Basler AG, Lenovo, STANLEY Security, and Vivotek.
2020 Year in Review
In this :30 minute video, AWS’ Dean Phillips and Nicholas Walsh recap automotive highlights from 2020. You will learn about notable partnerships, announcements, how AWS addressed gaps in the automotive industry with end-to-end architecture, and hear Dean’s thoughts on what’s to come in 2021 for Automotive.