Can Artificial Intelligence Devise a Better Zlevanka Than Our Grandma? We Tried and Were Surprised

What happens when a self-proclaimed "IT illiterate" dives into the world of artificial intelligence and cooking? For one writer, the journey began with a friendship with restaurateur Vladimir Stipan, who was exploring AI's culinary ambitions. Initially intimidated by technology, the writer found himself drawn into a fascinating interplay between human creativity and digital intelligence.

Their exploration led to an experiment with AI-generated meals, focusing on practicality and cost-effectiveness. Stipan, aiming to optimize his personal diet and create meals suitable for consumption on the go, tasked the AI with developing recipes that were both nutritious and economical. The AI proved adept at analyzing current grocery sales and discounts, devising an algorithm that significantly reduced the cost of a tasty meal to just a few euros.

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If you feed him shit, it recycles shit.

Stipan emphasized the importance of providing the AI with high-quality data, likening it to the adage "garbage in, garbage out." By feeding the AI a comprehensive dataset, including global and domestic cookbooks, nutritional studies, and even scientific principles like the Maillard reaction, they unlocked its potential to go beyond simple recipe replication. The AI demonstrated a remarkable ability to synthesize complex information and generate novel, personalized culinary solutions, surprising the writer with its sophisticated approach.

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If you give him 100 relevant PDFs, all possible world and domestic cookbooks, from Schwarzenegger's dietary records to studies on autophagy, including thermal processing, the Maillard reaction, then...