Let me guide you on how Tharaka Invention Academy helps turn problems into inventions. Hello, my name is Mandla, and I want to show you very simply how Tharaka Invention Academy is designed to work. Let me use a real design challenge as an example. I have worked with solar cooking for many years. Solar cookers can be wonderfully simple. You put the cooker outside, collect free energy from the sun, and cook food without burning wood, charcoal, or gas.
But I began thinking about a problem. Why should the cook have to stay outside? Could we design a solar cooker that collects its energy outdoors where the sunshine is, but allows the person preparing the food to work from inside the kitchen, much more like using an ordinary stove? Now, I could simply ask artificial intelligence to design that for me, and artificial intelligence can be very useful. In fact, I did have an ordinary ChatGPT conversation about this challenge. We explored several possibilities.
We considered concentrating sunlight through the wall. We looked at heat pipes that could carry thermal energy indoors. We created images. We examined costs. We rejected some ideas and developed others. Eventually, we arrived at a simpler possibility: keep the solar collector and cooking chamber outside, but position the cooker against a window or wall opening so the cook can access it from inside. That was useful problem-solving.
But Tharaka Invention Academy is designed to go further than simply getting a useful answer from AI. Inside the academy, the first question would not necessarily be: What should we build? The innovation coach would help me clarify the problem first. Who is the cooker for? Why is indoor access important? How much should it cost? What kinds of food must it cook? Can local craftspeople build and repair it? What will make the design safe? Those questions turn an interesting idea into a defined invention challenge.
Then the academy can draw upon its own learning ecosystem. For example, our learning library already contains material about a simple solar oven, including video, audio, and transcript material dealing with heat transfer, thermodynamics, locally available materials, and practical solar cooking. So instead of AI pretending that nothing has been learned before, the coach can connect the apprentice with relevant academy knowledge and ask: What can we borrow from this earlier design? What doesn’t apply to our new problem? And what questions remain unanswered?
Then we can use one of the TIA invention toolboxes to structure our thinking. And when there is a very specific job to perform, we have our problem pearls. One problem pearl might help us simplify the concept. Another can examine a drawing and identify areas that are difficult to understand. Another can help us identify possible failure modes before we build something dangerous. The important point is that these tools do not all rush into the project at once. The innovation coach helps select the right resource for the particular task we face at that moment.
Then we return to the invention. In this solar cooker project, creating images helped us see the idea more clearly. But the images also exposed questions. Where should the absorber be? Where should the heat pipes go? How should the glazing be arranged? How does the cook open the chamber from indoors? And then we discovered a much more serious question. Suppose the cooker is sitting in full sunshine, but nobody is cooking. The sun does not know that we are finished. The collector keeps collecting heat.
So now we have a possible overheating problem. That means the project has moved beyond making an attractive picture. We need to think about safety. Perhaps the cooker needs a reflective shutter or louvers that can block the sunlight, a real off position for the solar stove. And this is where invention becomes iterative. We identify a problem. We develop an idea. We simplify it. We visualize it. We discover weaknesses. We revise it. And eventually, we stop talking and start testing.
We might build only a small section of the collector first. Measure its temperature. Close the solar shutter. Measure what happens next. Does the temperature stop rising? How quickly? What did we expect? What actually happened? That physical evidence comes back into the academy, and the innovation coach helps us decide what question to investigate next.
Over time, the apprentice is also building something else: a record, a problem statement, notes from the learning library, sketches, alternative concepts, AI-assisted images, risk analysis, prototype photographs, test measurements, failures, revisions, reflections. Together, those become a portfolio of evidence showing not only what someone invented, but how that person learned to invent. That is the larger idea behind Tharaka Invention Academy.
Professor Singer’s textbook, “Innovate Now,” is provided in 10 major languages and provides broad knowledge and concepts. Tharaka Invention Academy’s website can be viewed in more than 120 different languages. The learning library provides videos, audio, transcripts, stories, examples, and supporting material. The invention toolboxes provide structured methods. The innovation coach helps the apprentice understand where they are and what should happen next. The problem pearls help with focused tasks.
Artificial intelligence can help us research, compare, visualize, question, and organize. But AI does not replace the inventor, and it does not replace mentors, community knowledge, observation, physical testing, or human responsibility. The apprentice remains at the center.
So when I think about bringing solar cooking inside the home, I am not only asking whether we can invent a new kind of solar cooker. I am also demonstrating a way of learning. One real problem, one useful question, the right resource, one piece of evidence, then the next experiment. That is how Tharaka Invention Academy is designed to help transform curiosity into capability and ideas into responsible inventions.
