Currently, there are 1.9 billion active websites with 4.6 Google searches per day and more than 5.4 billion unique Internet users. To date, the market size of the Web Design Services industry is equal to $11 billion, with the total number of web developers and designers in the US expected to increase to 205,000 in 2030 from 178,900 in 2020.number of jobs

The revenue in the application development software industry is expected to reach $149.7 billion in 2022 and grow to $218.80 billion by 2027 at a CAGR of 7.89%. The top 5 countries expected to generate the most revenues over the 2022-2027 period include:

Source de l’article sur DZONE


Omar from LightningChart here. As my first article for DZone, I wanted to experiment with how to create different charts available from the lcjs library.

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We want to make the Dev Interrupted podcast a vital, enjoyable part of your week. Please take 2 minutes and answer our new Listener Survey. It lets us know a bit about you, what you want from Dev Interrupted and what you want from podcasts in general! 

Almost every single company we talk to focuses on having their engineering teams solve problems.

Source de l’article sur DZONE

We want to make the Dev Interrupted podcast a vital, enjoyable part of your week. Please take 2 minutes and answer our new Listener Survey. It lets us know a bit about you, what you want from Dev Interrupted and what you want from podcasts in general! 

At LinearB, we like to think we spend all our time figuring out how to unlock developer potential. To find ways to let devs do more of the work they love and reduce the amount of time they spend dealing with needless hurdles, idling and churn.

Source de l’article sur DZONE

Few companies have mastered making products consumers actually want to use like Toast.

A $30 billion giant in the tech-food business, Toast faced their worst case scenario during the pandemic when the restaurants at the heart of their business were all forced to shut down.

Source de l’article sur DZONE

This article is an excerpt from the book Machine Learning with PyTorch and Scikit-Learn from the best-selling Python Machine Learning series, updated and expanded to cover PyTorch, transformers, and graph neural networks.

Broadly speaking, graphs represent a certain way we describe and capture relationships in data. Graphs are a particular kind of data structure that is nonlinear and abstract. And since graphs are abstract objects, a concrete representation needs to be defined so the graphs can be operated on. Furthermore, graphs can be defined to have certain properties that may require different representations. Figure 1 summarizes the common types of graphs, which we will discuss in more detail in the following subsections:
Common types of graph

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For decades Artificial Intelligence has been a focus of best-selling science fiction authors and an antagonist for blockbuster Hollywood movies. But AI is no longer relegated to the realm of science fiction, it inhabits the world around us. From the biggest enterprise companies to plucky startups, businesses everywhere are building and deploying AI at incredible speed. 

In fact, open source allows anyone with a laptop to build impressively good AI models in a day.

Source de l’article sur DZONE

Data junkies rejoice, this is the episode for you. 

On this week’s episode of Dev Interrupted, Einat Orr, co-founder and CEO of Treeverse, sits down with us to talk about the state of data… where it’s been, where it’s going and why having bad data might be worse than having no data at all.

Source de l’article sur DZONE

You’ve heard of the supply chain, but what about the software supply chain? 

Unlike the standard supply chain that you often hear about in the news, this week’s episode of Dev Interrupted dives into the supply chain responsible for holding together the systems that companies, orgs and governments depend upon. 

Source de l’article sur DZONE

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Chatbots Are Here To Stay

Chatbots have been around for a long time and based on the global chatbot market size (and the expected growth), they will stick around for a long time and gain importance. In the past, they’ve rarely met customer expectations or provided much positive experience. However, over the last few years, advances in conversational AI have transformed how they can be used. Since chatbots offer a wide range of applications, in certain cases, they become responsible for collecting and protecting personal information as well. 
Consequently, they are a great attraction for hackers and malicious attacks too. The responsibility of ensuring chatbot security has become more evident after the introduction of GDPR in Europe. As statistics show that this technology will be a determining factor in our lives, security testing must also become part of our daily tasks, so that these chatbots can be used with confidence.

Security Risks, Threats, and Vulnerabilities                 

The words risk, threat, and vulnerability are often confused or used interchangeably when reading about computer security, so let’s first clarify the terminology:

  • Vulnerability refers to a weakness in your software (or hardware, or in your processes, or anything related). In other words, it’s a way hackers could find their way into and exploit your systems.
  • A threat exploits a vulnerability and can cause loss, damage, or destruction of an asset – threats exploit vulnerabilities.                
  • Risk refers to the potential for lost, damaged, or destroyed assets – threats + vulnerability = risk! 
The well-known OWASP Top 10 is a list of top security risks for a web application. Most chatbots out there are available over a public web frontend, and as such, all the OWASP security risks apply to those chatbots as well. Out of these risks, there are two especially important to defend against, as in contrast to the other risks, those two are nearly always a serious threat — XSS (Cross-Site Scripting) and SQL Injection.
In addition, for artificial intelligence-enabled chatbots, there is an increased risk for Denial of Service attacks, due to the higher amount of computing resources involved.

Vulnerability 1: XSS – Cross-Site Scripting

A typical implementation of a chatbot user interface:           


  • There is a chat window with an input box.
  • Everything the user enters in the input box is mirrored in the chat window.
  • Chatbot response is shown in the chat window.

The XSS vulnerability is in the second step — when entering text including malicious Javascript code, the XSS attack is fulfilled when the web browser is running the injected code:


Possible Attack Vector

For exploiting an XSS vulnerability the attacker has to trick the victim to send malicious input text. It can be done through one of the following ways: