OpenAI：GPT-5就是All in One，集成各种产品

Core Viewpoint - OpenAI is integrating its various models, including Codex, Operator, Deep Research, and Memory, into a unified system to enhance programming efficiency and reduce model switching [2][11]. Group 1: Codex Development and Efficiency - Codex was initially a side project aimed at improving internal workflows, resulting in a programming efficiency increase of approximately 3 times when utilized effectively [5][17]. - OpenAI is exploring flexible pricing models, including pay-per-use options for Codex [5]. - The team aims to create a high-performance engine that supports multiple programming languages, allowing developers to use their preferred languages for extensions [8]. Group 2: Future Plans and Integration - The future plan is to consolidate existing tools into a cohesive system that feels integrated, enhancing user experience [11]. - OpenAI is working on a product called Operator, which is currently in research preview but aims to execute tasks on computers, further expanding the capabilities of GPT-5 [10]. Group 3: User Interaction and Learning - Codex is designed to assist not only advanced engineers but also those looking to solve simpler problems, making it accessible to a broader audience [13]. - The model currently utilizes information loaded during container runtime, such as GitHub repositories, but does not access real-time library documentation [15]. - OpenAI is considering incorporating retrieval-augmented generation (RAG) technology to improve the model's access to up-to-date knowledge [15]. Group 4: Long-term Vision and Impact - The team envisions a future where software requirements can be efficiently and reliably transformed into runnable software versions [18]. - Codex is intended to enhance human developers' capabilities rather than replace them, particularly aiding novice programmers in their learning process [19]. Group 5: Additional Resources - OpenAI has released a "Codex Getting Started Guide," which includes basic introductions, GitHub connections, task submissions, and prompt tips [24][25].