SenseTime introduced SenseNova U1 Pro at WAIC 2026, positioning it as a system for complex multimodal delivery rather than a model built only for single-pass image generation. According to the event presentation and the original report by QbitAI cited by MarsBit, U1 Pro is designed to handle a full chain of tasks around a target outcome: understanding, planning, information organization, multimodal generation, checking, revision and final delivery. The launch demo centered on an ultra-long 8K image themed around the ninth anniversary of WAIC from 2018 to 2026. The report said the original file was 51 MB and remained legible when enlarged. It summarized U1 Pro’s core strengths in three parts: native 8K generation that preserves text, layout and detail on very large canvases; a text-and-image interleaved workflow that can move from sketching to refinement, coloring, checking and adjustment; and a product focus on deliverable outputs for use cases such as infographics, urban planning, film storyboards, academic posters and commercial design. The article also described four practical tests, including a 24 solar terms panoramic image, a laboratory-style visual poster, a glazed-texture traditional landscape with futuristic architecture, and an original movie poster intended to look ready for commercial use. SenseTime CEO Xu Li summarized the broader issue this way: “Being interactive does not mean being deliverable.”

SenseTime Chairman and CEO Xu Li used a keynote speech at the 2026 World Artificial Intelligence Conference to lay out his view on AI accessibility and safety. He said several AI categories already validated by the market — software development, content generation and embodied intelligence — are following the same path, moving from single-purpose tools built for specialists to long-horizon task systems aimed at the broader public. In that shift, he said, the most visible change is in who the users are, with demand emerging more naturally from end users rather than from the original target customer base. Xu argued that broad AI adoption should not be framed around replacing humans. In his view, the goal is to expand the capability boundaries individuals did not previously have. On safety, he said governance should run through product design, model development and physical deployment boundaries. He also said data security should be addressed in both pre-training and post-training, with multi-model cross-checking used in operation. For embodied AI, he called for rollout through sandbox testing and constrained scenarios. Xu added that as AI moves toward the era of “super individuals,” pricing will shift away from tokens and toward the price of completed tasks, with the “Task economy” pushing AI from compute consumption to value delivery.