# Decision Making Processes **Note** * **Computational Methods** Gaby AI does not fine-tune large language models. Computational demand is expected to remain at the scale of basic numerical methods—comparable to ordinary least squares (OLS) regression or stochastic gradient descent (SGD)—rather than the high FLOPs required for large-scale model training. **Pros of RL / Temporal Isolation** The benefits per tech department: * **Software development**: decoupling the knowledge base from model training avoids the instability and inconsistency inherent to current AI systems. By isolating Gaby’s temporal and long-term memory from the underlying base models, the application gains scalability and resilience, reducing susceptibility to fluctuations in evolving AI technologies. * **Database management**: As the application is still in its early stages, it requires a strong and robust framework for database management. Once this framework is optimized, the efficiency of the existing data-cleaning ETL pipeline can also be improved. **Cons of RL / Temporal Isolation** * **Database vulnerability**: If the database workflow and architecture are not properly defined, the system is at high risk of structural failure. * **LLM Personalization**: would require more time invested in the data analytc stages when drawing data features to fine-tune models. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://whoamimi.gitbook.io/blog/projects/readme-1/decision-making-processes.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.