ChatGPT Extends Its AI Memory Feature to All Paid Users | Beebom
Earlier in February, OpenAI introduced a ‘Memory’ feature that revolutionized the way key details and preferences are stored across all your chats. This feature is now being made available to all paid ChatGPT Plus users, enhancing the personalized touch of your chat experience.
Enhanced Personalization
ChatGPT's Memory feature now allows the AI to remember various preferences such as your love for traveling, a preference for bullet points in summaries, concise answers, and much more. This feature goes beyond just broad-level preferences and extends to storing personal details, enabling ChatGPT to respond more intimately during conversations.
The Memory feature is seamlessly enabled by default, allowing ChatGPT to update its memory as it encounters pertinent information during chats. Users will receive a notification stating “Memory updated” whenever new information is stored. Additionally, users can input “remember it” in their prompts to ensure specific details are saved for future conversations.
Managing Your Memories
While the Memory feature enhances personalization, users have the option to disable it within ChatGPT. Some users may have concerns about privacy and may prefer ChatGPT not to retain personal information. By simply stating “forget” when a memory update occurs or by accessing the settings menu, users can manage and delete memories under Settings -> Personalization.
Prior to the Memory feature, OpenAI had introduced Custom Instructions, allowing users to provide additional personal details for ChatGPT to offer more tailored responses. With the integration of the Memory feature, ChatGPT is set to become even more personalized.
Privacy Considerations
It's essential for ChatGPT users to acknowledge that all conversations are utilized for model training by default. However, there is a way to opt out of this model training process. By referring to our tutorial on opting out of ChatGPT model training, users can follow detailed steps to ensure their data is not included in the training dataset.
As privacy becomes a growing concern, taking proactive measures to safeguard personal data from being part of training datasets is crucial. Companies are increasingly seeking various forms of data, including generating synthetic data to train their models.
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