In a recent LinkedIn post, Andrew Bolis tackles the often-intimidating subject of Artificial Intelligence, aiming to demystify its workings for a broad audience, including those new to the concept. Bolis frames AI not as a mystical force but as a practical tool deeply integrated into our daily digital lives. He breaks down the core components and functions of AI into digestible steps, emphasizing its accessibility and current ubiquity.
Understanding the Fundamentals of AI
Andrew Bolis begins by establishing a foundational understanding of what AI truly is. He asserts that at its core, AI is about leveraging data, algorithms, and models to identify patterns and generate predictions. This process, he explains, is far from magic and is built upon logical steps.
“AI uses data, algorithms, and models to find patterns and make predictions.”
Bolis further elaborates on the essential elements that power AI systems. According to him, the three basic parts are data, algorithms, and learning models. Data serves as the raw material, algorithms provide the instructions, and learning models enable the system to improve over time.
How AI Processes Information and Learns
A key aspect of Bolis’s explanation focuses on how AI ‘thinks’ and ‘acts’. He clarifies that AI does not possess consciousness or emotions; rather, it operates by processing vast amounts of data to predict potential outcomes. This distinction is crucial for understanding AI’s capabilities and limitations.
The Two Main Categories of AI
Andrew Bolis also differentiates between the two primary types of AI: Narrow AI and General AI. Narrow AI, which is prevalent today, is designed to perform a specific task, such as facial recognition or playing chess. In contrast, General AI, still largely theoretical, would possess the ability to understand, learn, and apply intelligence across a wide range of tasks, akin to human intelligence.
“Narrow AI does one task; General AI (future) could do many.”
The Learning Process in AI
The post highlights how AI systems improve and adapt. Bolis explains that AI learns through a continuous cycle of examples, pattern recognition, and feedback. This iterative process allows AI models to become more accurate and efficient over time.
AI in Everyday Applications
Bolis underscores the pervasive nature of AI in modern technology. He points to everyday applications like smart email suggestions, navigation apps, and content recommendation systems as prime examples of AI in action. His aim is to demystify these tools, showing that their underlying principles are understandable.
“From smart emails to map apps, AI is already all around you.”
In conclusion, Andrew Bolis’s LinkedIn post serves as an accessible primer on Artificial Intelligence. By breaking down complex concepts into simple, step-by-step explanations, he empowers readers to better understand the technology that shapes much of their digital experience. His approach emphasizes clarity and practicality, making AI less of a mystery and more of a comprehensible tool.
📝 About This Content
This article is based on insights shared by Andrew Bolis on LinkedIn.
📅 Originally posted on February 25, 2026 | View original post on LinkedIn →