Reading time 7 min

Stijn Van den Enden

In my previous blog post, I emphasized the importance of gathering data. However, in some cases you might not have any suitable data available. You might have raw data, but perhaps it’s unlabeled and unfit for machine learning. If you don’t have the financial resources to label this data, or you don’t have a product like reCAPTCHA to do it for free, there’s another option. Since Amazon launched its Amazon Web Services cloud platform as a side-business over a decade ago, it has grown at a tremendous pace. AWS offers now more than 165 services, giving anyone, from startups to multinational corporations, access to a dependable and scalable technical infrastructure. Some of these services offer what we call pre-trained machine learning models. Amazon’s pre-trained machine learning models can recognize images or objects, process text, give recommendations and more. The best part of it all is that you are able to use services based on Deep Learning without having to know anything about machine learning at all. These services are trained by Amazon, using data from its websites, its massive product catalog and its warehouses. The information on the AWS websites might be a bit overwhelming at first. That’s why in this blog post I would like to give an overview of a few services using Amazon’s machine learning models, which I think can easily be introduced into your applications. Computer vision with Rekognition Amazon Rekognition is a service that analyzes images and videos. You can use this service to identify people’s faces, everyday objects or even different celebrities. Practical uses are adding labels to videos, for instance following the ball during a football match, or picking out celebrities in an audience. Since Rekognition also has an API to compare similarities between persons in multiple images, you can use it to verify someone’s identity or automatically tag friends on social media. Speaking of social media: depending on the context of a platform, some user contributions might not be deemed acceptable. Through Rekognition, a social media platform can semi-automatically control suggestive or explicit content, giving the opportunity to blur or deny uploaded media when certain labels are associated with it. Digitalize archives with Textract Amazon Textract allows you to extract text from a scanned document. It uses Optical Character Recognition (OCR) and goes a step further by taking context into account. If your company receives a lot of printed forms instead of their digital counterpart, you might have a few thousand papers you need to digitalize manually. With regular OCR, it’s challenging to detect where a form label ends and a form field begins. Likewise it would be difficult for OCR to read newspapers, when text is placed in two or more columns. Textract is able to identify which group of words belong together, whether it’s a paragraph, a form field or a data table, helping you to reduce the time and effort you need to digitalize those archives. Analyze text with Comprehend Amazon Comprehend is a Natural Language Processing (NLP) service. It helps you discover the subject of a document, key phrases, important locations, people mentioned and more. One of its features is to analyze sentiment in a text. This can give you a quick insight in interactions with customers: are they happy, angry, satisfied? Amazon Comprehend can even highlight similar frustrations around a certain topic. If reviews around a certain product are automatically found to be mostly positive, you could easily incorporate this in a promotional campaign. Similarly if reviews are mostly negative, that might be something to forward to the manufacturer. A subservice of Comprehend called Comprehend Medical, is used to mine patient records and extract patient data and treatment information. Its goal is to help health care providers to quickly get an overview of previous interactions with a patient. By identifying key information from medical notes and adding some structure to it, Comprehend Medical assists medical customers to process a ton of documents in a short period of time. Take notes with Transcribe Amazon Transcribe is a general-purpose service to convert speech to text, with support for 14 languages. It automatically adds punctuation and formatting, making the text easier to read and search through. A great application for this is creating a transcript from an audio file and sending it to Comprehend for further analysis. A call center could use real-time streaming transcription to detect the name of a customer and present their information to the operator. Alternatively, the call center could label conversations with keywords to analyze which issues arise frequently. One of Transcribe’s features is to identify multiple speakers. This is useful for transcribing interviews or creating meeting minutes without having one of the meeting participants spend extra time jotting everything down. Multilingual with Translate When you’re getting reactions from customers on your products, you can translate them into your preferred language, so you can grasp subtle implications of certain words. Or you can extend your reach by translating your social media posts. You can even combine Transcribe and Translate to automatically generate subtitles for live events in multiple languages. Express yourself with Polly The Polly service can be considered the inverse of Transcribe. With Polly, you can convert text to speech, making the voice sound as close to natural speech as possible. With support for over 30 languages and many more lifelike voices, nothing is stopping you from making your applications talk back to you. Polly has some support for Speech Synthesis Markup Language (SSML), which gives you more control on how certain parts of the text are pronounced. Besides adding pauses, you can put emphasis on words, exchange acronyms with their unabbreviated form and even add breathing sounds. This amount of customization makes it possible to synthesize voice samples that sound very natural. Generating realistic speech has been a key factor to the success of apps like Duolingo , where pronunciation is of great significance. You can read about this particular use case in this blogpost . Bonus: if you don’t feel like reading, you can have it read to you by Polly! Make suggestions with Personalize When you look for any product on Amazon’s website , you immediately get suggestions for similar products or products that other customers have bought in combination. It’s mind blowing that out of the millions of items offered by Amazon, you get an accurate list of related products at the same moment the page loads. This powerful tool is available to you through Amazon Personalize . You need to provide an item inventory (products, documents, video’s, …), some demographic information about your users, and Personalize will combine this with an activity stream from your application to generate recommendations either in real-time or in bulk. This can easily be applied to a multitude of applications. You can present a list of similar items to customers of a webshop. A course provider would be able to suggest courses similar to a topic of interest. Found a restaurant you liked? Here’s a list of similar restaurants in your area. If you can provide the data, Personalize can provide the recommendations. Create conversations with Lex Amazon Lex is a service that provides conversational AI. It uses the same Natural Language Understanding technology as Amazon’s virtual assistant Alexa. Users can chat to your application instead of clicking through it. Everything starts with an intent . This defines the intention of the user, the goal we want to achieve for our user. It can be as simple as scheduling an appointment, providing directions to a location or getting a recipe that matches a list of ingredients. Intents are triggered by utterances . An utterance is something you say that has meaning. “I need an appointment with Dr. Smith”, “When can I see Dr Smith?”, “Is Dr. Smith available next week Wednesday?” are all utterances for the same intent: making an appointment. Lex is powerful enough to generalize these utterances so that slight variations can also trigger the correct intent. Finally, in the case of registering an appointment, you need to specify a few slots , pieces of data required for the user to provide in order to fulfill the intent. In the case of the example above, the name of the person you want to see, the time period and perhaps the reason of your visit. Even though the requirements are pretty simple, everything depends on the quality of the utterances and the chaining of intents. If you don’t have enough sample sentences or the conversation keeps asking information that the user already presented, your user will end up frustrated and overwhelmed. Predict demand with Forecast A fairly new service provided by AWS is called Forecast . This service also emerged from Amazon’s own necessity to estimate the demand for their immense product inventory. With Forecast, you can get insight in historical time series data. For instance, you could analyze the energy consumption of a region to project it to the near future. This gives you a probability of what the electricity demand tomorrow would be. Likewise, you might be able to predict that a component of your production facility needs maintenance before it wears out. Forecast can leverage Automated Machine Learning (AutoML) to find the optimal learning parameters to fit your use case. The quality of this services depends on the amount and quality of the data you can provide. This service used to be only available to a select group until very recently, but is now available to everyone. You can sign up for Forecast here . 🚀 Takeaway If you want to bring machine learning to your customers but are held back by a lack of understanding, Amazon offers out-of-the-box services to add intelligence to your applications. These services, trained and used by Amazon, can help your business grow and can give a personal experience to your customers, without any prior knowledge on machine learning.

Reading time 5 min

Peter Jans

Like every year, Amazon held its AWS re:Invent 2021 in Las Vegas. While we weren’t able to attend in person due to the pandemic, as an AWS Partner we were eager to follow the digital event. Below is a quick rundown of our highlights of the event to give you a summary in case you missed it! AWS closer to home AWS will build 30 new ‘ Local Zones ’ in 2022, including one in our home base: Belgium. AWS Local Zones are a type of infrastructure deployment that places compute, storage, database, and other select AWS services close to large population and industry centers. The Belgian Local Zone should be operational by 2023. Additionally, the possibilities of AWS Outposts have increased . The most important change is that you can now run far more services on your own server delivered by AWS. Quick recap: AWS Outposts is a family of fully managed solutions delivering AWS infrastructure and services to virtually any on-premises or edge location for a consistent hybrid experience. Outposts was previously only available in a 42U Outposts rack configuration. From now on, AWS offers a variety of form factors, including 1U and 2U Outposts servers for when there’s less space available. We’re very tempted to get one for the office… AWS EKS Anywhere was previously announced, but is now a reality! With this service, it’s possible to set up a Kubernetes cluster on your own infrastructure or infrastructure from your favorite cloud provider, while still managing it through AWS EKS. All the benefits of freedom of choice combined with the unified overview and dashboard of AWS EKS. Who said you can’t have your cake and eat it too? Low-code to regain primary focus With Amplify Studio , AWS takes the next step in low-code development. Amplify Studio is a fully-fledged low-code generator platform that builds upon the existing Amplify framework. The platform allows users to build applications through drag and drop with the possibility of adding custom code wherever necessary. Definitely something we’ll be looking at on our next Ship-IT Day! Machine Learning going strong(er) Ever wanted to start with machine learning, but not quite ready to invest some of your hard-earned money? With SageMaker Studio Lab , AWS announced a free platform that lets users start exploring AI/ML tools without having to register for an AWS account or leave credit card details behind. You can try it yourself for free in your browser through Jupyter notebooks ! Additionally, AWS announced SageMaker Canvas : a visual, no-code machine learning capability for business analysts. This allows them to get started with ML without having extensive experience and get more insights in data. The third chapter in the SageMaker saga consists of SageMaker Ground Truth Plus . With this new service, you hire a team of experts to train and label your data, a traditionally very labor intensive process. According to Amazon, customers can expect to save up to 40% through SageMaker Ground Truth Plus. There were two more minor announcements: the AI ML Scholarschip Program , a free program for students to get to know ML tools, and Lex Automated Chatbot Designer , which lets you quickly develop a smart chatbot with advanced natural language processing support. Networking for everyone Tired of less than optimal reception or a slow connection? Why not build your own private 5G network? Yep: with AWS Private 5G , Amazon delivers the hardware, management and sim cards for you to set up your very own 5G network. Use cases (besides being fed up with your current cellular network) include warehouses or large sites (e.g. a football stadium) that require low latency, excellent coverage and a large bandwidth. The best part? Customers only pay for the end user’s usage of the network. Continuing the network theme, there’s now AWS Cloud WAN . This service allows users to build a managed WAN (Wide Area Network) to connect cloud and on-premise environments with a central management UI on a network components level as well as service level. Lastly, there’s also AWS Workspaces Web . Through this service, customers can grant employees safe access to internal website and SaaS applications. The big advantage here is that information critical to the company never leaves the environment and doesn’t leave any traces on workstations, thanks to a non-persistent web browser. Kubernetes anyone? No AWS event goes without mentioning Kubernetes, and AWS re:Invent 2021 is no different. Amazon announced two new services in the Kubernetes space: AWS Karpenter and AWS Marketplace for Containers Anywhere . With AWS Karpenter, managing autoscaling Kubernetes infrastructure becomes both simpler and less restrictive. It takes care of automatically starting compute when the load of an application changes. Interestingly, Karpenter is fully open-source, a trend which we’ll see more and more according to Amazon. AwS Marketplace for Containers Anywhere is primarily useful for customers who’ve already fully committed to container managed platforms. It allows users to search, subscribe and deploy 3rd party Kubernetes apps from the AWS Marketplace in any Kubernetes cluster, no matter the environment. IoT updates There have been numerous smaller updates to AWS’s IoT services, most notably to: GreenGrass SSM , which now allows you to securely manage your devices using AWS Systems Manager Amazon Monitron to predict when maintenance is required for rotating parts in machines AWS IoT TwinMaker , to simply make Digital Twins of real-world systems AWS IoT FleetWise , whichs helps users to collect vehicle data in the cloud in near-real time. Upping the serverless game In the serverless landscape, AWS announced serverless Redshift , EMR , MSK , and Kinesis . This enables to set up services while the right instance type is automatically linked. If the service is not in use, the instance automatically stops. This way, customers only pay for when a service is actually being used. This is particularly interesting for experimental services and integrations in environments which do not get used very often. Sustainability Just like ACA Group’s commitment to sustainability , AWS is serious about their ambition towards net-zero carbon by 2040. They’ve developed the AWS Customer Carbon Footprint tool, which lets users calculate carbon emissions through their website . Other announcements included AWS Mainframe Modernization , a collection of tools and guides to take over existing mainframes with AWS, and AWS Well-Architected Framework , a set of design principles, guidelines, best practices and improvements to validate sustainability goals and create reports. We can't wait to start experimenting with all the new additions and improvements announced at AWS re:Invent 2021. Thanks for reading! Discover our cloud hosting services

Reading time 3 min

Peter Jans

The world is rapidly changing, both from a technological and environmental point of view. Often, these challenges go hand in hand. For example, through the push towards electric vehicles, smart homes and sustainable energy. But while there has been a longstanding focus on the automotive, manufacturing and agricultural industries, there is no pathway to a cleaner environment without addressing the sizable energy consumption of data centers and cloud computing. The carbon footprint of cloud computing According to the International Energy Agency’s (IEA) latest report , data centers around the world in 2021 used 220 to 320 TWh of electricity, which is around 0.9 to 1.3% of the global electricity demand. In addition, global data transmission networks consumed 260-340 TWh, or 1.1 to 1.4% of electricity. Combined, data centers and transmission networks contribute to 0.9% of energy-related emissions. While these may seem fairly low numbers, the demand for data services is rising exponentially. Global internet traffic surged over the past decade, an evolution that accelerated during the pandemic. Since 2010, the number of internet users across the world has more than doubled and global internet traffic has increased 15-fold , or 30% per year . This means that the carbon footprint of cloud computing is something all companies, large or small, must consider. But what can you do without sacrificing the computing power needed to support innovation and deliver goods and services as promised? Amazon Web Services (AWS) While cloud computing also comes with a footprint, it offers a much more eco-friendly way to operate your IT systems than local servers. That’s why we believe a cloud-first approach is key to make your business more sustainable. Especially when cloud-based technologies are powered with renewable energy. That’s why ACA Group carefully chooses its partnerships and evaluates the environmental impact of those partners. In this context, we have selected AWS as a cloud provider. Combined with our flexible Kubernetes setups, it allows us to choose for the least amount of carbon emissions while still meeting (and even exceeding) the expectations of our customers. It shows that cloud computing needs do not come at the planet’s expense. But why AWS? As the world’s most prominent cloud provider, Amazon Web Services is focused on efficiency and continuous innovation across its global infrastructure. In fact, they are well on their way to powering their operations with 100% renewable energy by 2025. Amazon recently became the world’s largest corporate purchaser of renewable energy ; Their investments supply enough electricity to power 3 million US households for a year. Efficient computing Creating clean energy sources is essential, but no less important is rethinking how computing resources are allocated. In a cloud efficiency report, 451 Research showed that AWS’s infrastructure is 3.6 times more energy efficient than the median of U.S. enterprise data centers they surveyed. Amazon attributes this greater efficiency to, among other things, removing the central uninterruptible power supply from their data design and integrating small battery packs and custom power supplies into the server racks. Tese changes combined reduce energy conversion loss by about 35%. The servers themselves are more efficient as well: their Graviton2 CPUs are extremely power- efficient and offer better performance per watt than any other processor currently in use in Amazon data centers. AWS offers unlimited access to cloud computing and services. While this comes at a price, efficient use of resources not only reduces costs, but also indirectly reduces carbon emissions. How can you achieve this? Build applications that are resource-efficient. Consume resources with the lowest possible footprint. Maximize the output on resources used. Reduce the amount of data and distance traveled across the network. Use resources just-in-time. ➡️ Curious how we at ACA Group set up our cloud stacks for maximum sustainability without giving up power, availability and flexibility? Talk to us here !