Key insights

• 💭 Admitting ignorance in a world that expects instant answers
• 🧠 Experiment to make AI more humble and vulnerable
• 🕵️ Detective work on extracting an AI system prompt
• 🌍 Impact of admitting 'I don't know' on AI
• 🔍 Investigating the underlying prompt and memory of chat VT
• 🔄 Refining instructions through back-and-forth interactions
• 📏 Measuring the output's closeness to the underlying prompt
• 🧜 Creation of a mermaid diagram for visualization

Q&A

• What is the 'I don't know method' in the context of interacting with AI?

  The 'I don't know method' allows for interaction with AI to identify confusion and uncertainties within responses, providing an opportunity for intervention and enrichment. It involves embedding feedback and uncertainties within the response, enabling a counseling-like interaction between the user and the AI to resolve issues quickly.

• What are the two different prompts for AI story generation discussed in the video?

  The video discusses two different prompts for AI story generation: the first prompt emphasizes the need for specific input on genre, tone, length, and purpose of the story, while the second prompt, 'mermaid,' seeks to emulate a collaborative experience by identifying unclear points during story generation.

• What are the key aspects of user engagement and feedback in AI prompt generation?

  The prompt emphasizes the importance of user engagement, the need for asking clarifying questions, and the ethical considerations in generating responses. Detailed instructions and a diagram are provided to understand the system prompt and improve its output.

• What are the aims and challenges of the AI model discussed in the video?

  The AI model aims to provide high-quality responses, adapt to user preferences, and maintain ethics, but it faces challenges due to its proactive engagement and predictive nature, leading to inaccuracies and misunderstandings.

• What does the video cover in terms of AI communication?

  The video delves into the process of refining instructions and measuring their closeness to the back end, as well as the creation of a mermaid diagram for visualization related to communication with the underlying prompt of chat VT.

• What is the video about?

  The video explores the power of admitting ignorance in a world that expects instant answers, introduces an experiment to make AI more humble and vulnerable, provides detective work on extracting an AI system prompt, and investigates the impact of admitting 'I don't know' on AI.

• 00:00 In a world that expects instant answers, it's okay not to know. The speaker discusses the power of admitting ignorance and introduces an experiment to make AI more humble and vulnerable. The video provides detective work on extracting an AI system prompt and explores the potential impact of admitting 'I don't know' on AI.
• 02:00 A detailed exploration of communication with the underlying prompt of chat VT, including the process of refining instructions and measuring their closeness to the back end, along with the creation of a mermaid diagram for visualization.
• 04:12 The AI model aims to provide high-quality responses, adapt to user preferences, and maintain ethics, but its proactive engagement and predictive nature can lead to inaccuracies and misunderstandings.
• 06:30 The prompt emphasizes the importance of user engagement, the need for asking clarifying questions, and the ethical considerations in generating responses. The document and diagram provide detailed instructions on how the system prompt works and how to improve its output.
• 08:39 The video discusses two different prompts for AI story generation. The first prompt focuses on assumptions, uncertainties, and questions, highlighting the need for more specific input. The second prompt, 'mermaid,' aims to identify unclear points during story generation, emulating a collaborative experience.
• 10:50 A method called the 'I don't know method' allows for interaction with AI to identify confusion and uncertainties within responses, providing an opportunity for intervention and enrichment. It involves embedding feedback and uncertainties within the response, enabling a counseling-like interaction between the user and the AI to resolve issues quickly.