Chain of thoughts

From Claude with some prompting
This diagram titled “Chain of thoughts” illustrates an inferencing method implemented in AI language models like ChatGPT, inspired by human deductive reasoning processes and leveraging prompting techniques.

Key components:

  1. Upper section:
    • Shows a process from ‘Q’ (question) to ‘A’ (answer).
    • Contains an “Experienced Knowledges” area with interconnected nodes A through H, representing the AI’s knowledge base.
  2. Lower section:
    • Compares “1x Prompting” with “Prompting Chains”.
    • “1x Prompting” depicts a simple input-output process.
    • “Prompting Chains” shows a multi-step reasoning process.
  3. Overall process:
    • Labeled “Inferencing by <Chain of thoughts>”, emphasizing the use of sequential thinking for complex reasoning.

This diagram visualizes how AI systems, particularly models like ChatGPT, go beyond simple input-output relationships. It mimics human deductive reasoning by using a multi-step thought process (Chain of thoughts) to answer complex questions. The AI utilizes its existing knowledge base and creates new connections to perform deeper reasoning.

This approach suggests that AI can process information and generate new insights in a manner similar to human cognition, rather than merely reproducing learned information. It demonstrates the AI’s capability to engage in more sophisticated problem-solving and analysis through a structured chain of thoughts.

Questions

From Claude with some prompting
This image highlights the significance of questions in the AI era and how those questions originate from humanity’s accumulated knowledge. The process begins with “Sensing the world” by gathering various inputs. However, the actual generation of questions is driven by humans. Drawing upon their existing knowledge and insights, humans formulate meaningful inquiries.

These human-generated questions then drive a combined research and analysis effort leveraging both AI systems and human capabilities. AI provides immense data processing power, while humans contribute analysis and interpretation to create new knowledge. This cyclical process allows for continuously refining and advancing the questions.

The ultimate goal is to “Figure out!!” – to achieve better understanding and solutions through the synergy of human intellect and AI technologies. For this, the unique human capacity for insight and creativity in asking questions is essential.

The image underscores that even in an AI-driven world, the seeds of inquiry and the formulation of profound questions stem from the knowledge foundation built by humans over time. AI then complements and accelerates the path toward enhanced comprehension by augmenting human cognition with its processing prowess.

2 Questions

From DALL-E with some prompting
This illustration contrasts two distinct purposes of conversation. The left card emphasizes collaboration and unity through dialogue with people, symbolizing teamwork and the achievement of shared goals. On the right card, conversing with AI like ChatGPT appears primarily aimed at acquiring information. However, it also portrays numerous users to indicate that the information is the product of collective intelligence. Even though the conversation with AI focuses on individual information acquisition, it underscores that the underlying force is the power of collective knowledge contributed by a multitude of users.