Spark
Somewhere between high school and the rest of my life, I stopped wondering how to build simulated worlds. At the time, exploring the idea seemed to require knowledge, software, computing power, and time that I did not have. So I put it on the shelf and got on with the things in front of me.
A couple of years ago, I began exploring generative AI because of work. My first questions were practical. What is a qubit — a basic unit in quantum computing? How do large language models work? What might organizations need to understand about them?
Those questions opened doors I had not expected to find. I found myself revisiting the science fiction stories that first made me curious about intelligent machines. From there I wandered through ancient civilizations, mathematics, probability, astronomy, language, the history of technology, educational games, podcasts, comics, and knowledge maps. I even wandered into astrology, not because I expected it to predict the future, but because I was curious why it has fascinated people for thousands of years.
Every answer seemed to unlock two more questions.
Eventually, I found my way back to simulated worlds. What began as simple curiosity turned into small experiments and, more recently, a much deeper dive into building educational simulations. I suspect a few future articles will come from that particular rabbit hole.
Along the way, I returned to old curiosities while learning new things.
Observations
Observation 1: Curiosity often loses to adulting.
Curiosity still needs time. During the years when school, work, raising a family, caring for parents, maintaining a home, and everyday responsibilities fill the calendar, an interesting question can lose its place in line without anyone deciding that it no longer matters.
Sometimes “not now” quietly becomes years.
Observation 2: Some curiosities used to require resources we did not have.
Mine seemed to require years of programming experience, specialized software, and more computing power than I could reach.
Even ordinary research took work before the research could begin. When I was a kid, if the answer was not in our ten-year-old set of Encyclopaedia Britannica, my mother had to drive me across town to the library.
The library opened a world to me, but the trip took part of her afternoon. My time to wonder came, in part, from hers.
Looking back, I realize that my curiosity depended on an entire support system.
Other questions might have required weeks in libraries, expensive tools, access to experts, or simply more uninterrupted time than life allowed. The reason for putting a curiosity aside was not always a lack of interest. Sometimes the path into it was too steep.
Observation 3: Generative AI changed what was practical for me.
For me, generative AI has lowered the cost of trying — not by solving curiosity for everyone, but by making a first attempt cheaper than it used to be.
Over the past several years, I have learned how to frame useful questions, test what the tools produce, verify what matters, and recognize when the work needs something beyond the conversation. The tools keep changing, so the learning continues.
That practice — try, check, know when you need more than the chat — gave me a way back into old questions. I could describe an idea, work through the pieces, see where it failed, and try again.
That was enough to move old questions off the shelf.
Observation 4: Conversation gave the question somewhere to go.
I expected generative AI to be useful for finding answers. I did not expect the conversations to matter as much as they did.
I could ask for another explanation, challenge an assumption, compare two approaches, or simply think out loud without having to know exactly where the conversation was headed. The conversation did not have to end with the first answer.
We wandered, and this wandering turned out to be the most interesting part.
Observation 5: There may be something interesting on your shelf too.
That experience has left me wondering whether other people have a question like that somewhere in their past.
Perhaps the interest simply ran its course. Perhaps life moved in another direction. Or perhaps the question is still there, patiently waiting to see what you would ask now.
Maybe there is something you wanted to understand: another language, the night sky, your family history, the birds returning each spring, or the story of the place where you live.
Maybe there is something you wanted to make or preserve: a mystery, a piece of music, a board game, a classroom simulation, a working model railroad, restored photographs, or a record of stories that live only in your family.
Or perhaps yours would never appear on someone else’s list. Bring that one too.
Closing Thought
Lately, I have been picturing a few curious people gathered around a table at the coffeehouse, each bringing one old curiosity.
Someone may arrive with the seed of a company. Someone else may want to understand a family recipe, a patch of sky, or the birds that return each spring. The evening I am imagining leaves room for both.
The question does not have to impress anyone. It only has to interest the person asking it.
Big ambitions are welcome. So are questions with no obvious use beyond the pleasure of following them.
We would ask questions, follow interesting threads, challenge assumptions, check what we discover, and perhaps build something small before the evening was over. Some projects might last only an evening. Others might turn into months of exploration.
The goal is to satisfy a curiosity that has been patiently waiting its turn. For now, I am calling the idea An Invitation to Be Curious Again.
The name may change. The question feels like the right place to start.
What did you stop wondering about?