Artificial Intelligence (AI) is a field of computer science. AI provides methods and algorithms to mimic human intelligence, reasoning, and decision-making and provide insights, which businesses could use in research or industry to build new exciting and innovative products or services. Machine Learning (ML) is a subset of AI with algorithms that learn from data. In this post, we sort out the differences between AI and ML.

Python is relatively easy to learn and beginner-friendly. I like Python because you can program any kind of project with it. It is open-source and free for anyone to use. Python has well-tested machine learning libraries and a very supportive community. I will overview herein a basic syntax of the Python programming language. This will be useful for beginners or people who move quickly from another programming language to Python.

Version control systems are handy to keep track of file versions. This is useful for tracking your code, scripts and text information. Currently, GIT is one of the best open-source and cross-platform version control solutions. It enables distributed repository management; it works fast over HTTP and ssh protocols. GIT is relatively easy to use, with command-line utility or Graphical User Interface.

Artificial neural networks (ANNs) are the cornerstone of Deep Learning algorithms. The name and the architecture are adopted from the human brain's neural network. ANNs are designed to simulate human reasoning based on how neurons communicate. ANNs contain a set of artificial neurons connected.

This post explains the basics of Python iterators and their successful alternatives, such as list comprehension. While these alternatives use more memory, they are still useful in practice. The post also covers advanced techniques for working with iterators, including using the itertools module and creating generators with the yield keyword. By mastering iterators, readers can create elegant and efficient code and become better Python programmers.

In this post, I discuss voice synthesis and cloning, and mention fantastic AI tools and APIs for creating high-quality human-like voices from text or for automatic voice dubbing.

In this post, I collaborated with ChatGPT to explore the captivating World of Dutch art and Johannes Vermeer. As an art critic and historian, ChatGPT provides fascinating insights into Vermeer's masterpieces and the historical events that influenced them. I also share my emotional experience of visiting a Vermeer art exhibition, and we'll have some fun creating AI art with Jasper.ai, DALL-E, Stable Diffusion Playground and Midjourney bot. Take advantage of my tips for refining ChatGPT's output and the prompts I used to get the best results. Join me on this adventure and discover the beauty of Dutch art and AI-art outcomes!

Why AI will never void humanity? What AI wants badly? I was thinking about these questions while travelling. I will share my initial thoughts with you, my dear reader.

Manual content pipelines inevitably fail at scale. After outgrowing brittle Python cron jobs, I migrated my infrastructure to n8n—a self-hosted, node-based orchestration layer. Here is the technical breakdown of configuring databases, managing OAuth2 security, and deploying AI-driven agents.

Learn what Codex CLI is, how to install it on Mac, Linux, and Windows, and take your first steps with this AI coding assistant that runs in your terminal.

AI agents like OpenClaw are wonderful tools — but without strict access rules and proper supervision, they can turn an ordinary Tuesday into something you will be explaining to HR for weeks. In this post, we explore the very real risks of deploying AI assistants carelessly, from leaked credentials to messages you absolutely did not mean to send. Most importantly, we look at how to use OpenClaw the right way, because when deployed thoughtfully, it is one of the most exciting and capable tools we are only just beginning to understand.