WIRED.jp Publishes Article on Substack Writers’ Use of AI

WIRED.jp published an article about Substack writers’ use of AI.

When considering this as a development in physical AI, it is necessary to distinguish the circulation of AI-generated writing from robots’ perception and control, and their operation in real-world environments. The information provided establishes only that WIRED.jp published an article about Substack writers and AI use; it does not make it possible to verify the details of the article’s findings or any connection to physical AI. It would therefore be inappropriate to draw conclusions about robots’ capabilities, the quality of their training data or their safety in the field based on reporting about text generation. Our related coverage includes an article introducing an AIMaker opinion piece on managing subscriptions to Substack and competing sites, among other sources, and tracking updates via RSS and Make.com: AIMaker Opinion Piece on Managing Substack Subscriptions Introduces Use of RSS and Make.com. It addresses the effort involved in gathering information and does not verify the findings of the current article’s investigation into AI use. Also, our previous reports on combat robots drawing attention at IFA 2026 and Pudu Robotics unveiling the PUDU D7 for the first time worldwide at WAIC 2026 and receiving a 36Kr award concern robot displays and announcements at events; they do not show a causal link or shared technical foundation with text generation on Substack. Even when topics both touch on “AI,” their subjects and types of evidence differ. Any discussion of the industry implications would first require examining the article’s research methods, scope and criteria, while avoiding conflating findings about writing on a platform with evaluations of data and models used in robot development. The excerpt provided does not contain the information needed for that assessment. Please refer to the original source for details. Any discussion of the relationship to physical AI would also require separately checking whether public information confirms specific examples of adoption by robotics companies or development teams, or concrete effects on training and evaluation.