Introducing ProfG.AI

Model Selection

The selection of the large language model (LLM) was a crucial step in creating a digital version of Scott Galloway. The team chose OpenAI's GPT due to its production capability and model performance, which were essential for building a large-scale consumer application 1. Many LLMs are designed for research or academic purposes, lacking the necessary infrastructure for such applications. The decision was influenced by the model's ability to scale and perform well in creating digital versions of creators.

We felt that OpenAI's products were best at addressing both of these criteria.

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Additionally, the model's fine-tuning capabilities offered bonus features that enhanced its suitability for the project.

   

Fine-Tuning

Fine-tuning the AI model was essential for tailoring it to emulate Scott's responses accurately. The process involved training a general-purpose model like GPT-3.5 with specific data to improve its performance in particular tasks 1. By providing the model with questions and desired responses, the team enhanced its ability to mimic Scott's communication style effectively.

We took GPT 3.5, gave it a bunch of questions, and then we gave it a bunch of responses in terms of how we would want the ideal stock bot to respond.

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This approach resulted in a model that outperformed the base version, demonstrating the power of fine-tuning in creating a more personalized AI experience.