OpenAI has released a tool called Computer History for the desktop ChatGPT application on macOS. It analyzes user activity across different applications and websites to make the model's subsequent responses more accurate and personalized.
The update was released on August 13th and is available for Pro, Business, and Enterprise subscribers. Residents of the EEA, the UK, and Switzerland will gain access later—the company plans to bring the feature into compliance with local data processing requirements in the coming weeks.
The company announced the launch on the social network X, calling Computer History an evolution of an earlier experimental project called Chronicle. According to OpenAI's statement, the new version consumes fewer tokens to maintain context and offers users more privacy management tools than the early test release.
How It Works
Computer History is built into the desktop ChatGPT application for Mac and runs in the background. The service records which applications and websites a person uses and adds this data to a temporary activity timeline. In subsequent dialogues, the model can rely on this history, reducing the amount of context that would otherwise need to be entered manually.
According to the company, the timeline interface allows users to return to previously completed tasks, track recurring work scenarios, clear the entire history or only a selected period—either through the timeline itself or via the menu in the macOS status bar.
The key condition is enabling the option in the Settings section, under the Integrations tab. Without this step, data collection does not start, and the function's status is always displayed openly in the settings so the user can see whether tracking is active.
OpenAI describes the Computer History function not simply as an extension of memory about conversations within ChatGPT, but as a mechanism that allows the model to account for the user's recurring work patterns outside of dialogue with the chatbot.
ChatGPT's Memory Expands, Europe Waits for Now
In 2026, OpenAI significantly accelerated the implementation of permanent memory across all its key products. The experimental Chronicle function, which is now being replaced and enhanced by Computer History, had already introduced the idea of cross-session context for users of the desktop version.
The new release reduces the computational costs of maintaining such context. On the same day, OpenAI announced GPT-5.6 Ultrafast mode on Cerebras chips—for API customers, generation speed reaches 750 tokens per second. This was announced several hours before the launch of Computer History.
Meanwhile, regulators in the EU and the UK are closely monitoring tools that involve the permanent storage of user data. The decision to delay the launch of Computer History in the EEA, the UK, and Switzerland indicates that the company first aims to bring the feature into compliance with local regulations before granting access in these regions.
Users who do not want the system to track their activity can simply not enable this function—it operates solely on the principle of voluntary consent.
AI Opinion
From the perspective of machine data analysis, the predecessor of the new feature contained technical risks not mentioned in the article. The official OpenAI documentation for the Chronicle project directly indicated increased risks of prompt injection and storage of records in unencrypted form on the user's device—these details are important when assessing the maturity of the technology underlying Computer History.
The macroeconomic context here also deserves attention. The trend towards persistent personalization through analysis of user activity intensifies competition with other major players in the chatbot market—particularly with Anthropic's Claude and Google's Gemini, which are developing similar memory mechanisms in parallel with OpenAI. The delayed launch in the EEA, the UK, and Switzerland can be viewed not only as a gesture of compliance with regulations but also as an indicator of how difficult it is to balance deep personalization with data protection requirements across different jurisdictions.
Will voluntary consent remain a sufficient barrier for user trust as the volume of collected activity data grows?
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