In the UK, almost nine out of ten (87%) consumers shop online. However, nine out of ten (89%) internet users fail to read the privacy policies of any online services or apps they use.

Just over a third (35%) admit to ‘sometimes’ reading privacy policies and just under a third (32%) say they only read them on rare occasions. More than one in six Britons (17%) admit to never reading the privacy policies of the online services or apps they use.

Do we truly grasp how our data is gathered and utilized?
Many remain unaware of the terms and conditions, leaving them in the dark about companies collecting their data. About 31% are oblivious to websites gathering information on their online behavior, even without registration.

Companies compile diverse personal data, encompassing browsing and purchase history, alongside demographics like age, gender, location, income, education, and marital status. This amalgamation enables them to predict consumer preferences and willingness to pay, even without direct engagement.

Moreover, 20% of Brits are unaware that social media platforms use their data for targeted ads, a crucial consideration for Black Friday shoppers. Despite concerns, 29% find targeted ads helpful, with 48% of those aged 18-34 and 32% of those aged 35-54 viewing them as beneficial, reflecting the perceived advantages among active social media users.

Furthermore, 82% express worry about social media platforms using smartphone data collected through microphones for ad targeting. However, it’s important to note that this can only occur if users have granted permission for microphone access.

C++ is one of the most widely used programming languages, even among tech giants like Google, Amazon, Flipkart, HP, IBM, Intel, Microsoft, Infosys, Sun Microsystems and many others who are constantly hiring C++ experts. Developing the right skills, willingness to learn new things and perseverance would open countless career doors for you.

Did you know that?
Simplilearn unlocks our curiosity with the interesting fact that C++ developers are not only some of the most in-demand, but also hold some of the highest paying jobs in the industry. The average salary in the US for a C++ developer is around $103,035 per year. Of course, we shouldn’t ignore the fact that the pay rate as a C++ developer also depends on the talents’ relevant skills, qualifications and experience.

In our gallery you will see the professions you can practice when you have knowledge of C++, which Simplilearn presented.

Recently, WebAssembly (Wasm) has also appeared. After the World Wide Web Consortium (W3C) declared it a web standard in 2019, it became the fourth web standard along with HTML, CSS, and JavaScript.

But while web browser apps represent the central and historical use case for Wasm, again, it’s a matter of it being designed to run anywhere on a properly configured processor – this is where Wasm and JavaScript diverge and become more integrated for some use cases.

Wasm and JavaScript
Wasm and JavaScript are closely related, but besides JavaScript, Wasm does other things. Wasm’s original goal of helping JavaScript run more efficiently in the web browser remains a key component of their integration. Today, it extends beyond the web browser and encompasses edge and server applications for which JavaScript is not best suited.

This is due to the way Wasm works in binary format at the processor level. And lest we forget, unlike JavaScript, Wasm is not a programming language. One of the main unique features of Wasm is that its functionality allows it to work with a number of different languages in addition to JavaScript, including Python, Rust, of course, as well as Go, .NET, C++, Java, and PHP, writes The New Stack.

Wasm could give JavaScript a performance boost by compiling the otherwise interpreted language and its runtime into Wasm modules, Torsten Volk, an analyst for Enterprise Management Associates (EMA), told The New Stack. Code that is already compiled will generally run faster than code that still needs to be interpreted at runtime, such as JavaScript, he said.

Volk also says that the integration of Wasm and JavaScript works well for a wide range of applications. These include browser-based machine learning in edge locations, browser-based games requiring high performance, augmented and virtual reality applications that require low-latency execution, and applications in general that need to be able to run quickly.
He also shares that the historical co-evolution of JavaScript and WebAssembly is complementary, as Wasm was created about 20 years after JavaScript and aims to extend JavaScript use cases to more performance-demanding application workloads.

Who is better?
For pure computational performance as well as for such tasks as image processing, WebAssembly has certainly proven its advantages as being much faster than JavaScript. But the context is probably much more complex than that.

“In the browser, I think the biggest advantage of WebAssembly is the potential to use libraries from other languages. Performance is good and can be useful for web applications like Figma. But code reuse is broadly applicable to many Web applications,”

Butcher says.

Because JavaScript is a language that is accessible to almost anyone and offers many community-supported libraries that “support tons of use cases without having to reinvent the wheel,”

Volk noted.

“The fact that Wasm can be combined with ReactJS and other popular JavaScript frameworks further expands the scope of JavaScript use cases, allowing developers to deliver full-fledged enterprise applications in a simple and responsive way,”

Volk continued.

Security issues
Volk’s view is that Wasm offers security advantages over JavaScript-only code. It serves to increase the security of JavaScript code when Wasm is used as a “compiler on steroids” with which JavaScript applications can be deployed. For example, Wasm isolates JavaScript from the browser, provides memory safety, and implements strongly typed variables that are harder to use than dynamically typed JavaScript variables. And using JavaScript in Wasm provides a nice security boost” to the entire application.

But that doesn’t mean JavaScript is inherently insecure. JavaScript can be made quite secure, according to Ralph Squilas, principal program manager at Microsoft, Azure Core Upstream, in an emailed response. He fired back in defense of JavaScript that browsers are some of the most attacked surfaces on the planet. However, WebAssembly facilitates defense-in-depth with a mathematically provable sandbox model that tools like Veriwasm take advantage of.

The company says trading is booming following fivefold annual growth through 2022 and the expansion of the business into three additional European markets: Norway, Finland and Germany.

According to Anyfin, customers save 50% on average loan costs using its platform.

The company plans an even bigger role for personal financial services with discounts to undercut traditional lenders. The key is likely to be in service delivery – no start-up wants to fall into the trap of negative media coverage of debt.

This Series C funding brings Anyfin’s total equity funding to $131 million, but that’s in addition to €500 million in debt facilities agreed to help Anyfin grow its loan book.

“With the current cost of living crisis putting increasing pressure on household finances, what we do is more valuable than ever for consumers, and this new capital will enable us to continue improving the scope and scale of our offering.”

Anyfin CEO and co-founder Mikael Hussain said.

He further said that the investment shows that the financial industry is undergoing a significant restructuring where the financial well-being of consumers is paramount.

With this capital, Anyfin will focus its internal resources on new product features, and aims to accelerate growth in its four operating markets.

Android 10 and higher versions support modular system components that allow us to accelerate functional and security updates across the Android ecosystem beyond major API-level releases and make new functionality backwards compatible with already released versions of Android. These enhancements help make development more agile and extend the reach of developers across applications.

Faster introduction of APIs and features
The ability to introduce new functionality beyond the core API level releases allows for faster innovation. As we mentioned in a previous post, we plan to release the initial beta of Privacy Sandbox on Android for Android 13 devices starting this year.

Backward compatibility
Extension SDKs also allow us to extend support for certain platform features to existing versions of Android, increasing user reach. For example, PhotoPicker application programming interfaces that were previously only available at API level 33 (Android T) and above are now also available up to API level 30 (Android R) via SDK extensions on devices with an R extension version of at least 2.

Before SDK Extensions, developers could check the value of Build.VERSION.SDK_INT, e.g. Build.VERSION.SDK_INT >= 33, to ensure that a minimum SDK level was available. While this check is still correct and supported, it will fail for devices with SDK level less than 33 and also with extension version R >= 2.

Modular system components are similar to Google Play Services in their intent to make it easier to update Android devices without the need for a new OS release. The main difference between the two solutions is that Modular System Components are part of AOSP, Android’s open source platform, while Play Services are a proprietary solution available only to Google and licensing partners. Being part of AOSP means that Modular System Components can also be delivered through third-party infrastructure in addition to Google Play, which will be the default for Google and licensing partners.

There are numerous documented methods for estimating or calibrating prediction uncertainty, but current uncertainty quantification tools and libraries are limited in scope and do not provide a comprehensive collection of methods. This results in large overhead and makes it difficult to incorporate uncertainty into production systems. Fortuna fills this gap by bringing together well-known techniques, making them accessible to users through a standardized and user-friendly interface.

Fortuna is an open source library for quantifying uncertainty in ML models. Fortuna provides calibration methods, such as conformal prediction, that can be applied to any trained neural network to obtain calibrated uncertainty estimates. In addition, the library supports a number of Bayesian inference methods that can be applied to deep neural networks written in Flax.

Fortuna offers three modes of use: 1/ Run from Flax models, 2/ Run from model outputs, and 3/ Run from uncertainty estimates. Their pipelines are depicted in the following figure, each starting from one of the green panels. The code sample above is an example of using Fortuna starting from Flax models, which allows model training using Bayesian inference procedures. Alternatively, you can start either from the model outputs or directly from your own uncertainty estimates. Both of these latter modes are framework independent and help you obtain calibrated uncertainty estimates starting from a trained model.

Applications that require critical decision making depend on an accurate estimate of the expected uncertainty. When there is uncertainty, it is possible to judge the accuracy of model predictions, defer to human judgment, or determine whether the model can be used safely.

 “Regulatory pressure is increasing. Investors, employees, and consumers are placing ever-growing importance on companies reporting their ESG impact and developing sustainable business models in line with their values. Our goal is to support them in this transformation process with innovative, digital tools.”

Its integrated module “automates measurement, analysis, and reporting of ESG performance, providing a central data management and reporting platform.”

Plan A plans to expand the decarbonization tooling and Scope 3 calculations for various industries.

The Berlin-based Greentech will also continue its international expansion. The goal is the current locations in Berlin, Paris, and Munich will be followed by others in the coming year, including London.

Coding is basically the act of translating codes from human language to a machine-based language. It can also be called a subset of programming since it is the foundation of programming. A coder has to be multilingual and has to write codes in different programming languages such as Java, C, Python, R based on the requirement. With the help of codes, you are providing instructions and information to the computer.

Three common components of most of the programming languages:

• Code syntax and rules that are to be followed when writing a code
• Compiler for converting code into the respective machine code
• Code execution and returning the results

A computer only understands the machine code, written in binary language. A coder’s task is to transform the requirements given to him into a language understandable by the machine. Also, some programmers translate logic into machine-understandable codes with a language. Coding used for implementing the fundamentals of computer programming in one way is also programming. The difference is that programming is used in a broader sense and deals with writing codes in multiple languages.

The coders work as per the received instructions. After this, the code implementation, debugging, code testing, and quality analysis is executed. These instructions are customarily called “source code.” Coding involves writing codes for creating a software program. Any sort of application, website, or game is a program. Let’s now have a look at the detailed explanation of programming.

Programming

Programming is a bigger aspect than coding, which is one of the parts of it. It is the process of developing an executable software program that is implemented without any errors. It is the programmer’s job to analyze a problem in the code and provide solutions.

Application creation requires several necessary steps, including planning, designing, testing, deployment, and maintenance. So, programming deals with not only coding but also analysis and implementing algorithms, understanding data structures, and mitigating issues. Altogether, the whole process is called programming.

A pseudocode is a good approach for explaining the algorithm to the coder. Coding is an essential part of programming, but a programmer requires a lot more knowledge, experience, and additional skills than coding.

A programmer creates complex programs, read, and executed by the machine providing a complete set of instructions for computers to perform. It takes years to become a professional programmer. If you can build a program and ensure that it doesn’t have errors, you can consider yourself that you have leveled up in your career as a successful programmer.

There is one simple example that can clearly explain programming. For instance, you can program the clock to wake you up at 6 AM. Also, you can program the AC to work on the temperature that you have chosen with the remote button that has codes at the backend to work on the given set of instructions by the user.

Difference between Coding and Programming

While coding and programming seem to be synonymous at the front, they are altogether different from each other. While coding means writing codes from one language to another, programming means to program a machine with a given set of instructions to run.

A coder’s task is to translate logic into language the machine can understand, whereas a programmer has to do more than just writing the codes.

1. Basic Difference

Coding is a part of programming that deals with converting the language into binary commands for the machine. Programming is the process of creating a program that follows certain standards and performing a certain task.

2. Scope

Coding is about translating the requirement logic into machine-understandable code. In contrast, programming demands analysis and conceptualization of different aspects of any program and finding solutions to any issues that may occur during the process. It also involves critical parameters such as debugging, compiling, testing, and implementation.

3. Tools

Coding doesn’t require so many software tools to be accomplished. Just a simple text editor like WordPad or Notepad would suffice. Nowadays, an IDE and debug tools such as Eclipse, Bootstrap, Delphi, ATOM are also used.

Programming requires document review and performing analysis along with coding that requires extra tools. The tools needed in the process are code analysis tools, code generators, databases, testing frameworks, linkers, compilers, code editors, GUI designers, assemblers, debuggers, and performance analysis tools.

A programmer is expected to know the advanced concepts of Git and Github, Database tools, analytical tools such as Apache Spark, presentation tools, cloud tools since it has a broader scope.

4. Skills

Coders are needed to have basic knowledge of programming languages. Programming would require creating algorithms, math models, data processing, and data structures know-how. A programmer needs a specialized degree and experience to write logic, analyze, design, and write complex programs. He also applies his imagination and analytical skills for solving specific problems. He is also expected to understand and create complex data structures and algorithms.

The coder’s job is to follow the programmer’s technical specifications to write code and ensure that the final outcome meets the requirements.