So which programming language is best for game development?
C#, C++, or Python?
Articles
Today, most companies are using Python for AI and Machine Learning. With predictive analytics and pattern recognition becoming more popular than ever, Python development services are a priority for high-scale enterprises and startups. Python developers are in high-demand — mostly because of what can be achieved with the language. AI programming languages need to be powerful, scalable, and readable. Python code delivers on all three.
While there are other technology stacks available for AI-based projects, Python has turned out to be the best programming language for this purpose. It offers great libraries and frameworks for AI and Machine Learning (ML), as well as computational capabilities, statistical calculations, scientific computing, and much more.
In this sample, we will implement the server-side of a client-server style messaging app. To do so, you could use your preferred programming language, but for speed, we’ll use Linx, a low-code developer tool for backend APIs, integrations, and automation.
For a quick review of Linx and how it works, see this video.
Scope
We will implement some web methods, which will be useful for creating a messaging client. However, the following items fall outside the scope of this sample:
The concept of coroutine must be familiar to everyone now. After all, not only LUA, Go, and Kotlin but also C++ all support coroutines.
But different languages have different implementations. Such as LUA, coroutines will be scheduled when someone called yield() or resume().
You have probably read about Kubernetes, and maybe even dipped your toes in and used it in a side project or even at work. But understanding what Kubernetes is all about, how to use it effectively, and what the best practices are requires much more effort. Kubernetes is a big open-source project and ecosystem with a lot of code and a lot of functionality. Kubernetes came out of Google, but joined the Cloud Native Computing Foundation (CNCF) and became the clear leader in the space of container-based applications.
Let’s hear from Gigi Sayfan, author of the bestseller Mastering Kubernetes, Third Edition, about his methodologies and the approach he followed to create a powerful resource to acquaint learners all over the globe with the fundamentals and more advanced concepts of Kubernetes.
Suppose you have an opportunity to create a project on AI. Consider these five stages before starting. These five are learning, programming language, knowledge representation, problem solving, and hardware.
1. Learning Process
Learning means adding new knowledge to the knowledge base and improving or refining previous knowledge.
Though I have worked on Java for more than a decade, I have not had a chance to work on Groovy. While working for API Integration into Jenkins CI/CD pipeline, I extensively used Groovy to invoke REST API, validate the user input parameters, and business logic for that. After that, I found that Groovy is a fascinating program language for Java developers.
Why Is Groovy Easy for Java Developers?
It allows to use the Java syntax liberally and tries to be as natural as possible for Java developers. It is an object-oriented dynamic programming language for Java virtual machine (JVM) and can be integrated smoothly with any Java Program. The groovy syntax is lucid, familiar, and direct that makes to develop projects faster and easier. It demands a shorter learning curve for Java Developer to develop, test, and integrate to make production-ready code in a short span.
Loops in a programming language is a piece of code that get executed repeatedly until the specified condition becomes false. A loop consists of two parts, a block of statements and a condition that control the loop.
Loops mainly consisted of three statements – initialization condition, test condition, update condition.
You have probably heard about an innovative language model called GPT3. The hype is so overwhelming that we decided to research its core and the consequences for the tech players. Let’s explore whether the language deserves this much attention and what makes it so exceptional.
What Is GPT-3? Key Facts
GPT-3 is a text generating neural network that was released in June 2020 and tested for $14 million. Its creator is the AI research agency OpenAI headed by Sam Altman, Marc Benioff, Elon Musk, and Reid Hoffman.
The language is based on 175 million parameters and is by far more accurate than its predecessors. For example, GPT-2 had only 1.5 billion of parameters, and Microsoft Turing NLG – 17 billion of them. Thus, the power of GPT-3 is significantly surpassing the alternatives.
