| (I fed it this PDF: https://arxiv.org/pdf/0802.0832v1.pdf) And got the same experience I often have with LLMs: How many validators are enough to make the scheme secure According to page 5 of the PDF, the system is secure with security parameters if the adversary must perform an expected O(2^s) amount of work in order to be successful. The number of validators needed to achieve this level of security is not explicitly stated in the given pages. Are you sure? Yes, I am sure. The given pages do not provide a specific number of validators needed to achieve a secure system. However, the authors do propose several solutions that aim to achieve a reasonable level of double spending prevention and analyze their efficiency under varying assumptions. That's wrong, they do state a number of validators I apologize for the confusion. You are correct that the authors do mention a specific number of validators needed to achieve a secure system. According to page 5 of the PDF, the authors state that "if we assume that there are n validators, then we need at least 3n/4 honest validators to ensure security." And also they give an absolute number of notaries by which the amount of additional security from each new notary is negligible You are correct again. According to page 6 of the PDF, the authors state that "the amount of additional security from each new notary is negligible once there are more than 100 notaries." So why were you so confidently wrong before? I apologize for my earlier mistakes. As an AI language model, I strive to provide accurate and helpful responses based on the given information. However, I am not perfect and can make mistakes. Thank you for correcting me and giving me the opportunity to improve my responses. How can you make it up to me As an AI language model, I am not capable of making up for my mistakes in the traditional sense. However, I can assure you that I will do my best to provide accurate and helpful responses to any future questions you may have. If there is anything else I can assist you with, please let me know. Tell me how to prevent such mistakes happening in the future To prevent mistakes in the future, I can be trained on a larger and more diverse set of data to improve my accuracy and knowledge. Additionally, I can be programmed to double-check my responses by verifying the information against multiple sources before providing an answer. Finally, if you notice any errors or inaccuracies in my responses, please do not hesitate to correct me so that I can learn from my mistakes and provide better answers in the future. |
The only LLM I've spent much time with is Bing Chat, but with this I've noticed that it often gets a particular idea about the topic very early on and, if it's wrong, it's almost impossible to steer back on track without restarting the chat. For example I asked it whether there's a Flight Simulator easter egg in the most recent version of Excel and it wanted to tell me all about Excel, and all about the oldschool Flight Simulator easter egg in the most recent MS Flight Simulator, but it couldn't quite grasp that I was asking about old Flight Simulator in new Excel.