Embedded Files
What is the Class about?
What is the Class about?
The SRGS AI class covers two main branches of AI: classic search algorithms (minimax, A*, local search) and modern neural networks/LLMs. Tic tac toe and chess were used as hands-on coding projects to implement minimax and understand how game-tree search works. The LLM side focused on how models like GPT generate text, predicting next-word probabilities and sampling from them. Together, the class bridges older symbolic AI (search/game-playing) with modern AI (language generation).
What have we learnt?
What have we learnt?
We've learned a wide range of concepts, with our teacher building each lesson around a deeper idea we need to grasp to code properly. Every topic connects back to that core thread, from search algorithms like minimax to how neural networks actually generate language.
Below is an example of the word translator model along with a student's notes!
This comes from the word translator model we looked at and wrote code for! This project helped us learn how the AI looks at models and started to give us a basic to how LLM's work!
This was an example of a student's notes when we discussed the dot product value and how neural networks work.
Projects we've completed
Projects we've completed
Search- Maze
“Hill climbing”- N-queens
Adversarial search- tic tac toe
Probabilistic Search- multi armed bandit
Page updated
Google Sites
Report abuse