Like every other event this year, one of the most awaited cloud computing events, AWS re:Invent 2020 is also being held virtually. The three-week virtual event took place from November 30th with live keynotes from Andy Jassy, CEO of AWS and Werner Vogels, VP and CTO of Amazon.com.
From the very first day, the event has started to announce the major launch and preview announcements including machine learning tools, containers and more. Below here, we have listed the latest announcements on AI and machine learning, in no particular order, made at AWS re:Invent 2020.
Sign up for your weekly dose of what's up in emerging technology.
After Inferentia, AWS launched its second custom machine learning (ML) chip known as Trainium. According to a blog post, Trainium is meant to provide the best price-performance for training ML models in the cloud. The chip shares the same AWS Neuron SDK as AWS Inferentia.
According to its developers, besides delivering the most cost-effective ML training, the chip will offer the greatest performance with the most teraflops of computing power for machine learning in the cloud. Also, the chip is optimised for various deep learning training workloads for applications, such as image classification, translation, voice recognition, natural language processing, among others.
SageMaker Data Wrangler
SageMaker Data Wrangler is a new AWS service that is designed to speed up data preparation for machine learning and AI applications. According to its developers, it reduces the time it takes to aggregate and prepares data for machine learning (ML) from weeks to minutes. The service contains over 300 built-in data transformations so that one can quickly normalise, transform, as well as combine features without having to write any code.
Amazon QuickSight Q
Amazon QuickSight is a generally available, scalable, serverless, embeddable, machine learning-powered business intelligence (BI) service built for the cloud. This year at re:invent, Amazon announced Amazon QuickSight Q, which is a Natural Language Query (NLQ) feature powered by machine learning.
Q uses ML algorithms to understand the relationships across the data and build indexes to provide accurate answers. With this new feature, users can now utilise Amazon QuickSight to ask questions about data using natural language and obtain specific answers within seconds.
Amazon Devops Guru
re:Invent 2020 announced Amazon DevOps Guru, which is a fully managed operations service. The service makes it effortless for the developers as well as operators to improve application availability by detecting operational issues and recommending fixes in an automated manner. It applies ML to collect as well as analyse data such as application metrics, events to identify the behaviour, etc.
There are several benefits to this service, such as:
- It alerts developers and operators to the details of the problem so they can quickly understand the scope of the problem.
- This service provides intelligent recommendations for fixing various problems.
- With this service, there is no particular hardware or software to deploy, and one only pays for the data analysed.
Amazon Lookout for Equipment
Amazon announced Lookout for Equipment, which is an API-based machine learning service that detects abnormal equipment behaviour. According to a blog post, Lookout for Equipment automatically tests the possible combinations and builds an optimal ML model to learn the normal behaviour of the equipment.
With this automated machine learning tool, customers can bring in historical time series data and past maintenance events data generated from industrial equipment that can have up to 300 data tags from components such as sensors and actuators per model.
Amazon Lookout for Vision
Along with Lookout for Equipment, the e-commerce giant also announced Amazon Lookout for Vision, which is a machine learning service that spots visual defects and anomalies in visual representations using computer vision (CV).
Amazon Lookout for Vision uses ML to see and understand images from any camera as a person would and allows customers to eliminate the need for costly and inconsistent manual inspection, while improving quality control, defect and damage assessment, and compliance.
During the event, Amazon previewed AWS Panorama, which is a machine learning appliance and software development kit (SDK) that allows organisations to bring computer vision to on-premises cameras to make predictions locally with high accuracy and low latency. One can now develop a CV model using Amazon SageMaker and then deploy it to a Panorama Appliance that can then run the model on video feeds from multiple networks and IP cameras.
The AWS Panorama Appliance is a hardware device that allows you to add CV to your internet protocol (IP) cameras that weren’t built to accommodate computer vision. Also, AWS Panorama Device SDK is a software kit that enables third-party manufacturers to build new cameras that run more meaningful CV models at the edge for tasks like object detection or activity recognition.
re:Invent 2020 announced Amazon Monitron, which is an end-to-end system that uses machine learning (ML) to detect abnormal behaviour in industrial machinery. The system enables a user to implement predictive maintenance and reduce unplanned downtime.
Monitron includes sensors to capture vibration and temperature data from equipment. The Monitron service is a gateway device to securely transfer data to AWS that analyses the data for abnormal patterns using machine learning, and comes with a companion mobile app to set up the devices and receive reports on operating behaviour and alerts to potential failures in your machinery.