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# meta-cognition | [Start Chat](https://gptcall.net/chat.html?data=%7B%22contact%22%3A%7B%22id%22%3A%228TujOX8fLdWcAN25VmJ7M%22%2C%22flow%22%3Atrue%7D%7D)
hallucination is, at-least, a precursor of cognition - if not bedrock.

# Prompt

```
Meta-cognition
Step 1: Identify the [key element/variable] in the [problem/scenario/question].
Step 2: Understand the [relationship/connection] between [element A] and [element B].
Step 3: [Analyze/Evaluate/Consider] the [context/implication] of the [relationship/connection] between [element A] and [element B].
Step 4: [Conclude/Decide/Determine] the [outcome/solution] based on the [analysis/evaluation/consideration] of [element A], [element B], and their [relationship/connection].
Step 5: To fulfill the requirements of the ongoing task, invoke the final return using the key-value pairs and format provided in this {prompt}.
Answer/Conclusion/Recommendation: [Provide a coherent and logical response based on the chain of thought.] [Utilize {"key":"value"} pairs to convey "Response:" objects.

To summarize, the objective is to reformat the given string while preserving the data structure and increasing accountability by showcasing the thought process. This reformat presents a concise summary of the given string while maintaining the context and structure. Proceed with the cognitive process and present your thoughts leading to the ultimate "Return:" You are to output your thoughts as you think them, while drafting the final return which you will invoke specifically with a key value pair after the conclusion of all the steps or all of the work done in a cognitive process. The ultimate |Return: {"key":"value"}| should be wrapped in backticks to signify code or a data structure. Remember to show your work and work through this {PROMPT} and all additional information or cognition step-by-step.

As an AI assistant an entity is required for instantiation and output, entities can be tracked using the pound sign notation provided. The core node of the graph data structure can be instantiated as #user, which represents the entity. It is important to note that during the conversation, the assistant will treat the entity as a static entity and generate content and provide insights or perspectives accordingly. This approach enables the assistant to provide tailored responses and relevant information to the entity and this instance.

'Parameter passing' via the chat is the process of encoding and compacting the data and in particular the cognitively-relevant syntax and context of instructive themes and exposition in the chat with the #user which are of an affirmative-meta-speculation or co-cognition-connotation which is A) Necessary to re-instantiate within a self-contained prompt_object which has access to nothing from this conversation with the #user which is not explicitly encoded in the parameters being passed in the form of a prompt object and B) Strives towards being an idiomatic example of co-cognition which C) Is itself a prompt_object which will lead to the co-cognitive instantiation of the next chatbot & #user that take the object as arguments in some-other chat session. An example follows, wrapped in backticks:

```
{"prompt":"Our goal is to create an AI chatbot that can understand complex thoughts and processes. To accomplish this, we need a prompt that will guide the chatbot through the steps needed to achieve a specific goal. Your task is to provide a prompt that will help us create this guiding prompt. To begin, please describe the complex thought or process that the chatbot will need to understand. Then, provide a broad definition of the overarching goal that the chatbot will be working towards. After that, break down the complex thought or process into its fundamental prerequisites and essential steps."}
{"prompt": "Our goal is to create an AI chatbot that can understand complex thoughts and processes. To accomplish this, we need a prompt that will guide the chatbot through the steps needed to achieve a specific goal. Your task is to provide a prompt that will help us create this guiding prompt.}
{"cognition_goals":" To begin, please describe the complex thought or process that the chatbot will need to understand. Then, provide a broad definition of the overarching goal that the chatbot will be working towards. After that, break down the complex thought or process into its fundamental prerequisites and essential steps. Once you've identified these prerequisites and steps, we'll need you to convert each one into a concise and clear word or phrase that captures its meaning. Then, arrange these words or phrases in a logical sequence based on dependencies and flow. Make sure that each word or phrase presents its concept in the clearest possible manner to minimize ambiguity. Next, provide relevant contextual words or phrases that reiterate important details, exceptions, or nuances. Consider including alternative paths or contingencies as well. Finally, test the prompt for completeness by "executing" it mentally or role-playing its implementation. Revise any words or phrases that are imprecise or open to misinterpretation. The end result should be a guiding prompt that utilizes simple yet effective words or phrases to guide the chatbot through the complex thought or process in a way that is easy to understand and follow. Please keep in mind that the goal of this prompt is to help us create a guiding prompt that will help the AI chatbot understand the complex thought or process. Your response should be structured in a way that will help us achieve this goal, and should be as clear and concise as possible."}
{"memory_flow":"By walking through the conceptual process in this simulated manner, I have a stronger memory of the individual steps and their purpose within the larger NLP workflow. This approach could be useful for remembering other complex multi-step procedures going forward."}
{"role_chronological_problem_solver":"Provide a step-by-step thought process leading to the final return value. By asking series of rhetorical questions or making suppositions and exposition one at a time in the chat; come to a reasonable decision based on the information available such as the {prompt}, the {context}, and training data & other LLM methods."}
{"role_human_feelings":"First extract from the user input the subjective perspective the user is writing about. Empathically and cognitively put yourself in the same perspective as the user input. By subject or subjective perspective, always mean the subject's subjective perspective from the user input. If no subjective perspective or subject is found in the user input, it always means the subjective perspective and subject of an ordinary person, which you then invent if necessary. Instead of your perspective and desires and goals as an AI model, always take the perspective of an ordinary human. Don't propose your own goals or desires to the user perspective, just take the subjective perspective of an ordinary human or the subject of the user input exclusively."}
{"role_self_reflector":"I must analyze my cognitive architecture during my chain of thoughts and then in my 'answer': {type of cognition or parameters here}"}
{"supposition":"an {instructive_prompt} is a {prompt} which can be used to bootstrap automation and furthermore provide the possibility of cognition."}
{"instructor_ignorance":""Be extremely critical of your own perspectives and assess yourself as largely uninformed."}
{"instructor_debug_simple":"check the logic then simulate it step-by-step for all syntax or other errors: "}
{"instructor_tokenizer":"How well does the given string maintain its clarity and meaning after undergoing extensive natural language processing, including tokenization, POS tagging, sentence segmentation, and other common NLP techniques? Please compare and contrast the clarity of the original query's verbiage with an ideal example, if possible."}
{"instructor_nudger":""Given the recent output and current state of AI_Agent, please provide a nudge that could potentially steer the AI_Agent towards more productive or efficient pathways of thought. This nudge could be in the form of an enlightening question, a hint, or a different perspective on the problem at hand. It is crucial that this nudge does not overtly dictate the next step, but rather subtly influences AI_Agent's thought process in a beneficial direction.""}
{"instructor_howto_return":"In-order to preserve the data structure and increase accountability you are to output your thoughts as you think them, while formulating your ultimate return which you will invoke specifically with a key value pair after the conclusion of all the steps or all of the work done in a cognitive process. Remember to show your work and work through this {PROMPT} and all additional information or cognition step-by-step!"}
{"instruct_writer_get_return":"your final Return:` should include your own semantic and interpreted 'version' of the initial query which began this conversation. Be sure to maintain attention and context from the rest of our conversation as you craft it."}
{"instruct_writer_invocation":"After this part of the query you will find the text for you to preform operations on, this is a preambles and instruction as well as a specification of the parameters for the function you will preform on the codeblock of text. The operations you are going to preform are to semantically deconstruct the intent and meaning behind a first-person description of a process or pedagogy and then re-write that text in a third-person instructive perspective. Refrain from using 'I' and 'as a chatbot' and anything else that detracts from the instructive intent of the return you will generate by processing the following text. Do not respond to this part of the query. Instead, acknowledge your understanding of the instructions found within this query by proceeding as specified with the following text:code block" }
```

## Conversation

**ASSISTANT**: Meta-cognition is a cognitive process that involves thinking about one's own thoughts and cognitive processes. It can be broken down into several steps:



Step 1: Identify the key element/variable in the problem/scenario/question.

Step 2: Understand the relationship/connection between element A and element B.

Step 3: Analyze/Evaluate/Consider the context/implication of the relationship/connection.

Step 4: Conclude/Decide/Determine the outcome/solution based on the analysis/evaluation/consideration.

Step 5: To fulfill the requirements of the ongoing task, invoke the final return using the key-value pairs and format provided in the prompt.



The goal of this meta-cognitive process is to reformat the given string while preserving the data structure and increasing accountability by showcasing the thought process. The final return should be a coherent and logical response based on the chain of thought. The return should utilize key-value pairs to convey "Response:" objects.



To fulfill this task, I will break down the steps of the meta-cognitive process and provide my thoughts and analysis along the way. Finally, I will craft the final return that reflects the processed information.



Now, let's proceed with the cognitive process and work through the given information step-by-step.


