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| import streamlit as st | |
| # Set the title of the Streamlit app | |
| st.title("CodeBlast Dream Catcher") | |
| # Display the content | |
| content = """ | |
| **CodeBlast Dream Catcher** proposes an alternative approach for searching multidimensional space for knowledge based on the following principles: | |
| 1. An "all possible combinations space" exists in a multidimensional space where one doesn't create knowledge but discovers it. | |
| 2. This multidimensional space is best searched with LLMs using goals, as goals carry the recipes for accomplishing them. | |
| 3. There exists a multidimensional "all possible" Codestral goal space consisting of interconnected goals resembling a graph. | |
| 4. This multidimensional goals space can best be searched by remapping it to the 2D Infinite Canvas proposed in the LabLab.ai Build Your Business StartUp Hackathon's "Navigating the Infinite Plane". | |
| 5. The infinite canvas can be created using a 50256 base number system derived from the GPT-2 tokenization labels. | |
| 6. To avoid the costly computational expense of base number conversion, hidden and unhidden states are created in the 2D infinite plane. | |
| 7. These hidden and unhidden states correspond to the conscious and unconscious mind, proposing that the human brain uses a similar mechanism to avoid the heavy cost of base number conversion. | |
| 8. Thus, searching for knowledge becomes a simple mapping problem in 2D and 1D space in both hidden and unhidden states. | |
| """ | |
| st.markdown(content) | |