10 ideas for maintaining AI thought process
Has a pioneering and effective strategy for managing the model's thought process.
![10 ideas for maintaining AI thought process](https://notepd.s3.amazonaws.com/posts/ai/A_robot_thinking_in_a_monastery_dressed_as_a_monk._There_are_shelves_of_books_nearby_and_the_robot_is_looking_out_the_window_painting_by_Leonardo_da_.webp?time=1725752014427)
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1. Use a database to track prompts over time
2. use the model's own history function as a backup
3. Ask the model to tell you its thought process: how did you, the AI, make these decisions?
Many times this will be a hallucination. Do this as part of the prompt workflow.
4. have a competing AI/LLM perform the same task and compare the output
5. Use AI to analyze the prompts, responses, and self analysis
6. Use an LLM that provides sources
There are a few that do this. It will provide web links.
7. LLMs are evolving so quickly that the AI "thought" process of today will be completely different in six years or even six months
8. Depending on the workflow use process that compares multiple engines and filters their result to what they agree on
9. x.ai (from Elon Musk) just released a code editor for prompts
![](https://notepd.s3.amazonaws.com/posts/multi/image_EAuCeQr.png?time=1699359887370)
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10. Every few days there is a major announcement. Chat GPT four can analyze and summarize PDF documents that you upload right now but it couldn't do it (publicly)10 days ago.
It is already extremely difficult to understand what an AI "thought process" really is. You have to rely on what it is willing to tell you. We are racing towards the singularity where human beings will not be able to to understand how artificial intelligence comes up with its output.
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