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Ransomware has come to be a customary instrument in the arsenal of cybercriminals who routinely attack individuals and organizations. Under such circumstances, their victims experience financial damage either by owning up to large ransomware payouts or by bearing the price of recovering from attacks. By Alina Georgiana Petcu.

Unfortunately, ransom demands can sometimes be in the millions of dollars. Below, you will find the most significant confirmed ransomware payouts of all time to illustrate just how costly falling victim to this kind of attack can be.

The article also covers:

• Top 5 ransomware payouts of all time
• 2019 ransomware stats
• 2020 ransomware stats
• 2021 ransomware stats
• Average ransomware payouts trend
• Cumulative ransomware payouts trend
• To pay or not to pay the ransom?

Ransomware payouts and the attacks that lead to them are on the rise yet again in 2021. And while paying the ransom is an expensive affair in itself, mitigation after the fact is even costlier. Good read!

Facebook AI Research has built and open-sourced BlenderBot 2.0, the first chatbot that can simultaneously build long-term memory it can continually access, search the internet for timely information. By Facebook.

A current trend in machine learning models is to concentrate on training ever-larger models, which requires substantial computational resources. Those models attempt to store what they learn in their model weights. But storing the entire internet — which is always growing and changing – would seem to be next to impossible. Our method instead accesses the internet on the fly.

BlenderBot 2.0 uses a model based on Facebook’s Retrieval Augmented Generation — an approach that enables generating dialogue responses that incorporate knowledge beyond that contained in the conversation itself.

During conversation, the model, which combines an information retrieval component with a seq2seq generator, seeks relevant information both in its long-term memory and from documents it finds by searching the internet Very interesting!

Microservices have emerged as a common architecture pattern over the last decade. By Craig Buckler.

Building resilient and scalable services is crucial. For stateless microservices, this is fairly straightforward. But if data needs to be persisted, you ultimately need a resilient database architecture that scales together with the microservice to support increasing service usage.

The article describes:

• Common patterns for microservices in Couchbase
• Pattern 1: Dedicated Couchbase cluster per microservice
• Pattern 2: Isolation using buckets
• Pattern 3: Isolation using collections
• Pattern 4: Isolation using buckets and collections

There’s no doubt: Today’s development environments are shifting toward microservices. At the same time the industry is moving towards containerized deployments managed through Kubernetes and OpenShift. For the details please follow the link to the full article. Good read!

This article explains how to use IndexedDB to store state in a typical client-side JavaScript application. IndexedDB has good cross-browser support and offers at least 1GB of storage. By Craig Buckler.

Note that Web Storage is synchronous: your JavaScript code pauses execution while it accesses data. This can cause performance issues when saving larger datasets.

The article content is split into:

• What do we mean by state?
• Is IndexedDB suitable for storing state?
• Creating an IndexedDB-based state management system
• Creating an IndexedDB wrapper class
• Creating the State manager class

Projects often avoid IndexedDB because its API is clunky. It’s not an obvious choice for state management, but the indexed database and large storage allocation could make it a good option for complex projects which store significant volumes of data. You will also get the code in Github - it provides an example to-do app which you can use or adapt for your own projects. Perfect!

In a world where an ever-increasing amount of data is being gathered, companies often find themselves without the tools to optimally use the often unstructured data they’ve gathered. By trackit.io.

How can Company X manage to salvage the unstructured data it has gathered and still make use of it in a structured way? Solution: ETL pipeline — a pipeline that automatically Extracts data from their NoSQL database, Transforms it into a specific format suitable for exploitation and Loads it into a destination relational database.

The article then describes:

• AWS services that allow you to clone and migrate data
• Bridging the gap
• A DynamoDB to Aurora ETL pipeline architecture
• How the pipeline works
• Data propagation
• Lambda functions for Quality control

… and more. To get the schema of example ETL architecture and to learn pros and cons follow the link to the full article. Nice one!

How author went about his goal – to come up with an overarching technical vision for the whole company aligned with their 3-year business strategy, and that would move us away from a monolithic architecture and central SRE team to a distributed system where we shift ownership to each team. By Daniel Micol.

To accomplish the goal, author started working with other engineers and product leaders to understand the history of our technical architecture and the challenges that we were facing including developer productivity issues, site reliability problems or scalability limitations. From these goals, we derived a set of requirements for our 3-year technical vision:

• Features
• Leveraging Data
• Performance
• Scale
• Quality
• Self-Service
• Development Process

We must streamline our internal development processes and progress along the DevOps Big 4 to these levels: Deployment frequency: Elite (Daily for web and backend services and up to weekly for native apps), Lead time for changes: Elite (Less than one hour), Mean time to restore service: Elite (Less than one hour), and Change failure rate: Elite (0-15%).

We liked sOme interesting thoughts around development process. To learn how their effort led to long-term thinking technical vision that will provide the right guidance to our teams, indicate how the different pieces in our system should fit together - follow the link to the full article. Nice one!

We will explore concepts in Angular that seem simple but are very powerful and critical for the application architecture. By Max Schulte is engineer consultant at Thinktecture.

Every Angular developer knows the async pipe. It is almost always present when writing components and using some observables or promises. This article will explore how it works and for what it is suitable.

The article then pays attention to:

• Where do we profit from using the async pipe?
• How does the async pipe work?
• The async pipe in action
• An alternative to the async pipe

As alternatives to the async pipe, you can resolve the observable or promise in your component. This article explores the async pipe, how it works, what it is used for, and examines its source code in detail. We have seen how to use it and provided examples, demos, and alternatives. Now it is up to you to decide where to use it in your projects and when. This conclusion might help you further with that decision. Good read!

Even with the most optimized code, it is hard for eCommerce sites to reach a 100 out of 100 score on PageSpeed Insights unless they serve only static HTML. By Misko Hevery.

By removing all of the JavaScript execution we can get a perfect score of 100 and pass with flying green colors! But, therein lies the problem. These pages are static. We need our pages to deliver content dynamically, full of interaction and life. How can we serve static HTML to receive high scores, but at the same time provide rich interaction?

The reason is that all existing frameworks are not designed with time-to-interactive in mind. They have complex bootstrap processes which require a lot of code to be downloaded and executed before the page can become interactive. Yes, most support server-side-rendering to get a quick flash of initial content, but the first thing they need to do is to download all of the templates on the page and execute them to rehydrate the page and make it interactive.

Introducing Qwik, an open-source DOM-centric, resumable web-app framework designed for best possible time-to-interactive, by focusing on resumability of server-side-rendering of HTML and fine-grained lazy-loading of code. The basic goal of Qwik is to focus on the time-to-interactive metric by delaying JavaScript as much as possible to take advantage of the browser’s lazy loading capabilities.

Qwik’s goal is to crush time-to-interactive to a blink of an eye on the slowest mobile device. We want to serve static pages to the user so that they are fast, but retain all of their interactivity. We want to have our cake and eat it too! Good read!

From listening better to citizens, to making operations more efficient, AI brings multiple benefits to governments to make better decisions. By Hugo Cen.

The continuous progress of technology has led to different government organizations having to modify their structures, as well as the way in which they execute their processes.

Nowadays, applying tools such as Artificial Intelligence (AI ) in government is essential, since AI makes all operations more efficient, allows citizens to listen better, have greater sensitivity about what they are asking for, what they need, and know the general feeling you have.

According to Christian Peñaloza , doctor in Cognitive Neuroscience, there are three categories into which the main current benefits of Artificial Intelligence in government can be grouped. These are:

• Perfect existing processes: it is based on automating many of the tasks that are carried out, particularly those that consist of data collection and procedures that are carried out for the government
• Improve decision-making with data : here AI can be used to analyze all the data collected and, from it, make better decisions
• Crime prevention: it is more focused on using this technology to be able to detect certain frauds, for example, many use it in the part of the Tax Administration Service (SAT) in collaboration with banks, to be able to detect strange movements and to be able to identify transactions that are not legitimate. It is also implemented in security departments to prevent crime

What’s more, data should be the mainstay of current public policies since, as mentioned above, they generate enormous value. Good read!

Day by day the number of machine learning models is increasing at a pace. With this increasing rate, it is hard for beginners to choose an effective model to perform Natural Language Understanding (NLU) and Natural Language Generation (NLG) mechanisms. By Purnasai Gudikandula.

The wide availability of other sequence-to-sequence learning models like RNNs, LSTMs, and GRU always raises a challenge for beginners when they think about transformers. And it is important to a beginner to have basic knowledge of these models before they get to know more about transformers. If you still struggle why not RNNs, LSTMs, and GRUs, here we listed a few important points that can help you out.

The article does a good job of explaining:

• Why Transformers?
• Transformer architecture
• Transformer architecture flow
• Code for language translation
• Transformers for tomorrow

Source: ARXIV via https://deeplobe.ai/machine-learning-for-transformers-explained-with-language-translation/

Transformers are pretty versatile and can be used in a variety of NLP tasks, such as; Machine Translation, Text Summarization, Speech Recognition, Question-Answering systems, and so on. Well worth your time!