Metamentation with gemini-2.0-flash-thinking-exp-1219

Gemini API
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As an exercise in metamentation I submitted this request to gemini-2.0-flash-thinking-exp-1219:

“Read the transcripts of these 43 Gemini Thinking processes looking for patterns and similarities in analysis. I want help in uncovering the thinking process used by Gemini Thinking. I’m trying to make a Thinking Process Template.”

The Thinking itself listed 13 steps and is too long to reproduce here but an short extract of the Thought is worth sharing.

Applying this to the Gemini’s Transcripts:

When analyzing the 43 transcripts, consider these questions in light of your example:

  • Prompt Deconstruction: How does Gemini initially parse and categorize the prompts? Are there common elements it consistently identifies as crucial?
  • Contextual Awareness: Does Gemini demonstrate an understanding of the underlying intent or implied meaning behind the questions? Does it adapt its responses based on the apparent complexity or nuance of the prompt?
  • Information Integration: How does Gemini connect different pieces of information within the prompt and its internal knowledge base? Are there preferred methods of association or inference?
  • Linguistic Patterns: What are the recurring linguistic features in Gemini’s responses? Are there specific words, phrases, or sentence structures it favors?
  • Response Structuring: What is the typical organizational pattern of Gemini’s responses? Does it follow a predictable format?
  • Evidence of Iteration: Are there instances where Gemini appears to refine its thinking or offer alternative perspectives before settling on a final answer?

By applying the same principles you used to construct the personae – deconstruction, contextual awareness, connection-making, linguistic analysis, and structural observation – you can begin to discern the underlying patterns in Gemini’s thinking processes. Remember, you are not just looking for what it says, but how it arrives at those conclusions.

Try it

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Hi @Peter_Keyse,

Apologies for the response delay. Please check my response below.

Prompt Deconstruction: Gemini models are designed to understand both explicit and implicit aspects of a query. It uses NLP techniques to understand Entities, Actions, context and questions/commands.

Contextual Awareness: YES and YES. They go to high level of contextual awareness beyond surface-level understanding by considering nuances in prompts.

Information Integration: Gemini links different elements of the prompt and draws inferences based on context.

If the user asks, “How does AI in finance work in fraud detection?” Gemini connects AI’s capabilities using ML and pattern recognition with how they are applied to finance for fraud detection.

Linguistic Patterns: Gemini tends to use simple, clear sentence structures for clarity, with well-defined subject-verb-object order. For complex topics, it might employ complex sentences to show relationships between concepts.

Recurrent Phrases like “This means,” or “To put it simply” help Gemini clarify complex ideas.

Gemini’s responses often maintain a formal, academic tone, especially for technical or professional queries. However, user can adjust based on the prompt’s tone (e.g., more casual for informal queries).

Response Structuring: Response structure typically follows a logical and predictable format. It often finishes with a summary statement, helping the user understand the broader context of the information.

Evidence of Iteration: It is often visible in open-ended questions when the prompt asks for an opinion or evaluation, it dives deep into it to present pros and cons. Typically prompts can direct it’s thinking path before it settles with an answer.

Hope these answers helps you understand Gemini models at a deeper level..

We launched three new models with 2.5-pro being the most powerful.. I encourage everyone to try them.