How I use LLMs to learn complex topics

Laurentiu Gabriel, an engineer, developed ChipTycoon, an interactive low-poly simulation that teaches chip manufacturing by guiding a cart from sand collection to final chip delivery, using LLMs to build and review the knowledge base and generate the animation. The tool, available at https://laurentiugabriel.github.io/ChipTycoon/, aims to make learning complex topics more engaging and accurate, with plans for enhancements like 3D object mapping and interactive challenges.

How I use LLMs to learn complex topics LLMs are used for any things. Learning new things is one of the top use cases. Many engineers I know use generative AI for many functions, like building PoCs, internal tools or dashboards, or even learning new stuff. I personally find the style used by LLMs to explain things difficult to follow. It's just too simplistic and depending on the number of emojis used, a bit annoying too. While I was analyzing new AI bottlenecks that might slow down data center buildup, I realized there are many aspects of chip production that I do not know. Surfing the web, I asked myself what if there would be a game to get you through the process of building a chip at a fab? For sure learning this way will stick, since you can map concepts with objects within the game. This is when I decided to try it, and it actually turned out really well. The flow Instead of just asking AI to explain a topic, I use the following flow: - In plan mode using CC, or OpenCode I ask a model to build the foundational knowledge for X topic. - I ask it to review the accuracy of the knowledge base it built in the previous step. - I proceed asking it to build a simulation of that topic in a low-poly, Rollercoaster Tycoon-like animation. I add some UX elements as well, like the page needs to be visible on both large and small screens, have controls to stop the flow whenever I want etc. - I then push it to a new repo and enable GitHub Pages for it. The result What you get is a beautiful animation that is 100% accurate and free of hallucinations. For me, this method works a lot better than just reading endless materials that I find on Google, or trying to digest a bulleted list that is spat by a language model. I've done this specifically for learning chip building and launch it under this website: ChipTycoon https://laurentiugabriel.github.io/ChipTycoon/ . You get to follow a cart from the moment when sand is collected, to the moment when a chip is finalized and delivered to a data center. Visually, you can follow the cart and see how it changes too. Since it's low-poly, the details might be missing, but it's still a good indicator for showing how the product changes once it goes through the many steps required in the manufacturing process. How to improve it further Let's say that the low-poly design requires to much immagination to actually visualize what happened to the quartz sand pile after it left the furnace. To transform this into a more realistic representation, you can use my skill for transforming pictures into 3d objects https://github.com/LaurentiuGabriel/unreal-game-assets-creation-skill , and map the resulting objects to your simulation. This way you get more accurate design. Also, you can add challenges to your simulation too. Trying to answer questions about a previous step in the chip manufacturing process will help you retain the knowledge tremendously. Add intuitive puzzles too that will help you learn even better. Check out what other pages I created: