Artificial Intelligence: Three Building Blocks

Artificial intelligence (AI) began in the 1950s, emerging alongside technological advances during the Atomic Age. Alan Turing, best known for his WWII codebreaking, laid the groundwork in 1950 by publishing a paper that imagined machines displaying human-like intelligence. The term “artificial intelligence” was introduced in 1956 by John McCarthy and his colleagues at a conference now seen as the official starting point in the field. At its core, AI relies on three main ingredients: data, algorithms, and computing power. These can be understood by comparing AI to a car: 1. Data acts as fuel: Just as your car needs gasoline or electricity, AI needs data to run. For example, a local bakery gathers sales numbers from past days as its fuel.

2.Algorithms are the engine:Algorithms turn data into action— much like an engine converts fuel into movement. If the bakery notices it sells more pies on weekends, it uses that pattern to decide how many to bake today. That’s an algorithm at work: recognizing patterns, making decisions, and solving everyday problems to better match supply to demand.

3. Computing power is the electricity, that is, the energy that keeps everything running. Whether it’s a car relying on its battery or a bakery depending on electricity for ovens, lighting, and computer systems, consistent energy is vital to daily operations in both settings. By using past sales data and recognizing that certain days require more or fewer pies, the bakery’s owner can make a more qualified whole foods purchase decision without wasting ingredients and money. Computing power is like an engine turning fuel into motion and meaningful action.

Moving from a small bakery to a full grocery store, AI takes inventory management to the next level. Instead of relying on past buying patterns,AI tracks shelves in real time and forecasts demand using sales trends and weather, then automates reorders. This shift is important for grocers, who manage many products with a limited shelf life such as produce, meats and fish, and dairy products. Less waste on the shelves translates into purposeful buying decisions for grocery stores. AI personalizes the customer’s experience through data-driven product recommendations and can track detailed individual customer shopping paths to optimize store layout and service efficiency. Looking back, AI has traveled from theory and codebreaking to reshaping how we shop for food each week. What began as academic speculation now powers the decisions behind every restock and fresh display of produce. Today’s grocery store is a smart ecosystem ensuring shelves stay filled and every shopper’s trip feels a bit more tailored to their needs.

Lisa Musick, of Praha, is a writer, historian and welcomes feedback and questions via email at: lisa@lisamusick.com