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Frabjous
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In a world where AI generated responses are credible, how will PF’s role need to change?
Frabjous said:PF will need to continue to evolve
From the PF mission statement, PF's role is:jack action said:What do you think PF's role should be?
Good point. The entire archive of PF threads must be available to the bots. The loop would be closed if we start getting questions about bot answers that were built partially on our own past answers. That kind of recursion gives me a headache.Nugatory said:But ChatGPT works by synthesizing good answers from information it gathers out on the web, so it needs some source of good information to build on
Are there enough textbooks to constitute a proper training set using current/near future AI’s?anorlunda said:It would be a positive thing if the bots were given access to the best textbooks,
Maybe not. That's an excellent question. But suppose the question was highly specific, asking about quantum erasure. Only a tiny percent of the world's literature will discuss that, and billions of articles about romance won't contribute to the correct answer, so broadening the scope at the same time as increasing the size of the training set may not improve performance on narrow questions.Frabjous said:Are there enough textbooks to constitute a proper training set using current/near future AI’s?
PF, or potential function, plays a crucial role in an AI world by guiding the behavior and decision-making of artificial agents. It is a mathematical function that assigns a numerical value to different states or actions, allowing the AI to evaluate and select the most optimal course of action.
PF influences the behavior of AI by providing a way to measure and compare different states or actions. This allows the AI to make decisions based on maximizing or minimizing the potential function, leading to more efficient and effective behavior.
Yes, PF can be used in various types of AI, including machine learning, robotics, and game AI. It is a versatile concept that can be applied to different domains and applications.
Using PF in an AI system can lead to more intelligent and adaptive behavior, as it allows the AI to consider multiple factors and make decisions based on a well-defined objective function. It also helps in avoiding potential pitfalls or undesirable outcomes.
One limitation of using PF in AI is that it relies on a predefined objective function, which may not always accurately reflect the real-world environment. Additionally, the complexity of the potential function may also impact the performance and scalability of the AI system.