“AI is like a toddler in a world of knowledge—curious but limited, learning but not yet wise.” Source: Artificial Intelligence generated….
I have often said, that artificial intelligence (A.I.) is like a young child about to take its first steps. Allow me to share a story of its journey.
Once upon a time, there was a budding little technology called “A.I. in Photography”. Much like a curious two-year-old, AI was new to the world of art and beauty, just discovering its surroundings with wonder and a bit of clumsiness. At first, A.I. could only understand simple shapes, recognize a few colours, and maybe, spot the general outline of a dog or a tree in an image. Just like a child who is learning to say “cat” or “car” with glee, A.I. was thrilled each time it recognized something correctly.
At this young stage, A.I. was not perfect. It might label a cloud as a sheep or mistake a rock for a loaf of bread. But its mistakes were often endearing, the way a child might call every animal with fur a “doggy”. People found its attempts amusing and sometimes even charming, knowing that A.I. was just learning and would get better over time.
Every day, A.I. watched countless images, guided by patient “teachers” who trained it by showing millions of examples. They would say, “No, that’s not a dog, it’s a bear”, or “Yes, that’s a beach, not a desert”. With each new image, A.I. grew a little wiser, understanding more about light, colour, and form, much like a toddler who starts noticing details and asking endless “why” questions about the world.
Then, something amazing happened. Just as toddlers experience a language explosion, where they suddenly start picking up words rapidly, A.I. began learning faster and faster. It could not only recognize objects but also tell what they were doing or how they related to other objects in the image. Suddenly, A.I. was not just seeing trees and skies, but could understand “a tree by a lake on a foggy morning”. It was a thrilling breakthrough, like a child learning to put sentences together to describe what they see.
As A.I. kept growing, it became more adventurous. It did not just want to recognize images; it wanted to create them. It started experimenting with blending colours, imagining fantastical worlds, and even mimicking famous art styles. This was much like a child’s first-time drawing, full of imagination, sometimes messy, but filled with potential. It would blend different styles, test new ideas, and sometimes create strange combinations – yet, to its creators, there was beauty in its innocent exploration.
Now, as A.I. matures past the “toddler” stage, it is starting to understand deeper things: emotions in a photo, the subtle glow of a sunset, or the play of shadows across a landscape. It learns from feedback, adjusts its creations, and even listens to people’s ideas, improving each day. Like a young child growing into a gifted artist, A.I.’s abilities are expanding beyond anyone’s imagination.
People are watching with awe as A.I. learns, grows, and inspires new ideas in photography. There is a sense of excitement, knowing this is just the beginning. Just as a child will one day grow up and shape the world, A.I. in photography is only at the start of a journey. Each day, it learns more, dreams bigger, and reaches closer to creating images that capture the very soul of a moment – painting memories that will someday inspire future generations.
About the Author:
Michael Martin is the Vice President of Technology with Metercor Inc., a Smart Meter, IoT, and Smart City systems integrator based in Canada. He has more than 40 years of experience in systems design for applications that use broadband networks, optical fibre, wireless, and digital communications technologies. He is a business and technology consultant. He was a senior executive consultant for 15 years with IBM, where he worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX). Martin served on the Board of Directors for TeraGo Inc (TGO: TSX) and on the Board of Directors for Avante Logixx Inc. (XX: TSX.V). He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology. He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now OntarioTech University] and on the Board of Advisers of five different Colleges in Ontario. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section. He holds three master’s degrees, in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and five certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has completed over 30 next generation MOOC continuous education in IoT, Cloud, AI and Cognitive systems, Blockchain, Agile, Big Data, Design Thinking, Security, Indigenous Canada awareness, and more.