According to Sam Altman on Twitter, ChatGPT has updated its personalization page by consolidating personality configuration, custom instructions, and memory features into a single, streamlined interface. This change, rolling out over the next few days, is designed to improve usability and user experience for both individual and business users. The unified interface allows for more efficient workflow customization and deeper personalization, which creates new opportunities for enterprises to tailor AI interactions to their specific operational needs. This update also reflects a broader trend towards user-centric design in AI platforms, increasing adoption potential in enterprise and customer service environments (Source: Sam Altman, Twitter, Sep 16, 2025).

According to DeepLearning.AI (@DeepLearningAI), most large language models require post-training to effectively follow instructions, reason clearly, and ensure safe outputs. Their latest short course, led by Assistant Professor Banghua Zhu (@BanghuaZ) from the University of Washington and co-founder of Nexusflow (@NexusflowX), focuses on practical post-training techniques for large language models. This course addresses the business need for AI models that can be reliably customized for enterprise applications, regulatory compliance, and user trust by using advanced post-training methods such as reinforcement learning from human feedback (RLHF) and instruction tuning. Verified by DeepLearning.AI’s official announcement, this trend highlights significant market opportunities for companies seeking to deploy safer and more capable AI solutions in industries like finance, healthcare, and customer service.