GPTs解説#1 膨大な情報を処理する「Knowledge」機能の仕組みと使い方【ChatGPT】

Summary

The video script introduces the concept of 'Knowledge' as one of the most important features in GP, Keyz creation, aiming to equip AI with human-like memory capabilities. The video covers the limitations of ChatGPT in remembering conversations and how the Knowledge feature can enhance its functionality by allowing it to understand and process vast amounts of information. It demonstrates the feature's potential by referencing a custom GPT model that utilizes OpenAI's official documentation, showcasing its ability to provide detailed answers on various topics. The script also delves into the technical aspects of how the Knowledge feature works, using vector representations to enable the AI to 'recall' information and answer questions accurately. The video concludes by discussing the strengths and weaknesses of this feature, emphasizing the importance of structuring information for effective knowledge retrieval and suggesting that understanding the Knowledge feature's mechanism can lead to more efficient problem-solving in AI development.

Takeaways

• 📚 The video discusses the concept of 'Knowledge' in GP, Keyz, which is a crucial feature for creating a chatbot with human-like memory capabilities.
• 💡 Knowledge functionality allows the AI to understand and process vast amounts of information, theoretically enabling it to perform any task that requires extensive background knowledge.
• 🔍 The AI uses a retrieval mechanism to simulate memory, converting given information into vectors and comparing distances between them to retrieve relevant information.
• 📈 The video demonstrates the power of the Knowledge feature by creating a GP, Keyz that references a comprehensive text file based on OpenAI's official documentation.
• 🔬 The Knowledge feature does not improve the AI's memory power itself but allows it to mimic human-like behavior by recalling information within a limited character count.
• 📈 The video introduces a tool for measuring the semantic similarity between words, which aids in understanding how the AI's memory search mechanism works.
• 🚀 The Knowledge feature can be utilized to create custom actions within the AI, allowing for integration with external data and interactions with the real world.
• 🤖 The video highlights the limitations of the Knowledge feature, such as its inability to understand the meaning of words outside of their vector representation.
• 🧠 To fully utilize the Knowledge feature, it's important to structure information accurately, creating a knowledge base that the AI can effectively search through.
• 📝 The video suggests that even if one is not well-versed in using the Knowledge feature, understanding its mechanism can lead to more efficient problem-solving and improvement.
• ✅ The video concludes by encouraging viewers to experiment with the Knowledge feature and to follow the creator for more content on AI and game development.

Q & A

What is the main topic of the video?

The main topic of the video is the explanation of the Knowledge feature in GPT models, which allows the AI to handle tasks requiring substantial background knowledge by understanding an immense amount of information.

What does the Knowledge function in GPT models do?

The Knowledge function in GPT models allows the AI to exceed its limitations by understanding and utilizing a vast amount of information, theoretically enabling it to perform tasks that require extensive background knowledge.

How does the Knowledge feature help in content creation like tutorial videos?

The Knowledge feature can handle tasks that require deep understanding, such as creating tutorial videos, by referring to a large database of information, like OpenAI's official documentation, to provide accurate and comprehensive content.

What is the difference between a standard GPT and one with the Knowledge function regarding answering complex questions?

A standard GPT without the Knowledge function might provide generic or incorrect answers due to limited information. In contrast, a GPT with the Knowledge function uses a vast database to retrieve and provide precise answers to complex questions.

What example was used to demonstrate the capabilities of the Knowledge function?

The video demonstrated the capabilities of the Knowledge function by using a GPT model that could access and utilize OpenAI's official documentation to answer questions accurately.

What is the retrieval mechanism mentioned in the video?

The retrieval mechanism mentioned in the video involves transforming all provided information into vectors, which are then used to find and retrieve the most relevant information based on the proximity of vectors related to a queried topic.

What practical tool was introduced to understand the concept of vector similarity?

The video introduced a simple tool that measures the similarity of words or phrases as vectors, showing how closely related they are based on a numerical scale, thus demonstrating how retrieval works in practice.

What are the limitations of the Knowledge function as discussed in the video?

The limitations include difficulties in associating words or concepts that do not directly overlap in language or are not directly linked in the dataset, making it hard for the retrieval system to recognize their relevance without exact word matches.

How can one enhance the effectiveness of the Knowledge function?

Effectiveness can be enhanced by structuring information in a way that makes retrieval easier, such as by tagging or organizing data into a hierarchical structure that mirrors how related concepts are grouped together.

What future content did the presenter mention at the end of the video?

The presenter mentioned that the series would continue with more detailed discussions on AI and its applications, including game development and other AI-related topics.