Whenever AI comes up in a conversation, people jump to chatbots or whatever new model just dropped: maybe a new model of ChatGPT, Nano Banana, or another AI model. Although those models of AI are interesting to discuss, they aren’t the only way to look at AI. AI shows up in places that do not seem technical at first.
An example of this is with video games. An eight-year-old me came back from school, full of energy as usual, because I was in elementary school, and I couldn’t wait to play Nintendo’s new Legend of Zelda game, The Legend of Zelda: Breath of the Wild. While playing, I remembered something my teacher told me at school, “Always stay curious and keep an open mind to the things around you.” Now, of course, as an eight-year-old, I thought my world was so easy to understand, but today, when I loaded up the game, I started wondering about the enemies. The enemies in the game were reacting to my character's actions. This sparked my curiosity. Although it was simple, I was still interested to know how characters in the game were able to play without a user but still play as if they were being controlled; they attacked me with different types of moves and used their shield when I attacked. I asked my brother and did some research to discover that this was a Dynamic, Autonomous CPU. This was my first exposure to AI.
This is also a place where AI exists. AI isn’t just limited to LLMs or agents; it’s everywhere.
Not in some dramatic robot takeover way. Just in the systems behind the scenes. The way characters move. The way difficulty adjusts. The way the environment feels responsive instead of random. Later on, I branched into other Nintendo titles and games known for strong soundtracks and puzzle mechanics, and the pattern became obvious. The draw was always systems that required strategy and pattern recognition.
That realization changed everything, and that's when I became interested in AI. Interest in AI does not have to start with language models or advanced research papers. It can start with whatever already feels interesting. Music lovers can look at recommendation algorithms or AI-generated compositions. Sports fans can explore performance analytics and predictive models. Artists can experiment with image enhancement tools. Even scrolling through social media involves algorithms learning from behavior. AI is less about one specific tool and more about intelligent systems solving problems in different contexts. Of course, it’s important to know about the different AI models and agents in the world we live in today, but it doesn’t have to start there; people’s interest in AI can start with what they are interested in.