The most significant risks that could jeopardize the success of the project is still the integration of the subsystems. We did not realize that the computer vision portion may be more complicated than intended and that the output format we chose, an FEN string, may be harder for the other subsystem for interpret than intended. These risks are being managed by building the portions of all 3 subsystems that depend on the CV in conjunction so that any tweaks to make either side of the exchange easier can be done and tested more quickly.
There were no changes to the existing design of the system.
We are planning to run the CV, move suggestion, opponent move generation on 100 different board states and testing the accuracy. Each subsystem during these 100 different boards states will also be measuring the latency and seeing whether they are under our goals of 500ms, 100ms, and 5s respectively. We also plan to run 10 full games to see whether the move deemed “most optimal” is indeed the most optimal and also whether the LLM is able to provide meaningful help during these 10 games.