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TheProposal.txt
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TheProposal.txt
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I. Thesis
Artificial Intelligence is being utilized by many people to subsize their work, help them
communicate with other people, and even to tutor them in some cases. But what if AI used other
AI to do the same for its own purposes. Cases like AlphaGeometry, created by the AI lab
DeepMind, show this to be potentially a fruitful approach. In their paper they claim to have used
a language model to assist a deduction engine to solve Olympiad-level geometry problems. In
my project I intend to show that large generative models can assist in creating and fine tuning
smaller, rigid models to accomplish narrow tasks that the large model would be incapable of
solving on its own.
II. Method
First would be to do research into the potential novel and interesting problems that the
models would be best used to solve. Some examples being utilizing a C++ physics engine to
design virtual robots to achieve a goal or using already built software such as video games for
the models to discover the best techniques to beat the game. The next step is to then decide on
the best models to solve the problems. Potentially pairing things like Reinforcement Learning
and a Large Language Model. The RL can be used as the small model to solve the narrow
problem while the LLM can be used to analyze results and suggest changes to the RL model.
Lastly reporting on the success or failure to reproduce the benefits of having a creative and rigid
models working in tandem. This might include cases of attempting to do utilize just one model
without the other in the loop to compare with both working in tandem.
III. Outcome
The outcome of the project will be a program that includes a problem for the models to
solve and the two models that will be tied into the project code. There will also be a formal
report with information on my results and how to replicate every step taken in the project.