A：The competitive landscape for AI video generation models is characterized by substantial user adoption potential and a vibrant phase with diverse stakeholders maximizing their strengths to drive industry upside. The segment features a more concentrated market structure with clear dominant leaders and a higher level of concentration among tier 1 players, unlike the fragmented competitive landscape of large language models. Companies are leveraging platform ecosystems, vertical scenarios, and technological capabilities to compete through differentiation, which continues to expand the commercialization boundaries of AI video generation across various narratives.

A：clean AI has consistently remained among the tier 1 players in the AI video generation segment, demonstrating strategic foresight and strong execution capabilities. Notable achievements include the launch of the world's first commercially available video model product based on the Dit architecture in June 2020, the introduction of the world's first multimodal visual language interaction architecture in April 2025, and the release of the world's first harmony model based multimodal B2 generation model in December 2025. The company's track record shows its commitment to innovation and research, engineering, and strategic execution capabilities.

A：clean AI focuses on serving professional content creators by leveraging video generation large model technology to improve their productivity. It enables precise and coherent creative expression in terms of visual quality, production, and scalability, satisfying the need for high-quality video content. Clean AI also supports native 4K output, allowing users to generate 4K videos with a single click without additional upscaling or post-processing.

A：AI has been deeply integrated across key processes in online marketing services, including the generation of AI C marketing materials, intelligent bidding, and generative recommendation. In the generation of marketing materials, AI connects user interest modeling with video production capabilities, moving from searching for marketing videos to creating videos tailored for users. On the intelligent bidding front, AI uses historical account data and marketing placement and conversion goals to develop self-learning and continuously optimized automated trading strategies, enhancing long-term customer value and marketing placement performance. AI models improve user product matching efficiency by converting product live streams, search queries, and industry information into semantic representations.

A：The recommendation system has been enhanced through AI by launching agents like 'Agent X' and 'Agent R'. The old recommendation process involved multiple steps such as data analysis, solution design, product code modification, and involved heavy manual execution by algorithm engineers, which limited efficiency. With the new agents, the recommendation iteration process is automated, freeing engineers from repetitive tasks and enabling them to focus on goal setting, critical reviews, and higher-level judgment and decision-making. As a result, both the iteration efficiency and performance of recommendation strategies have been significantly improved.

A：The in-house developed agent tools, including 'My Flicker', have achieved over 90% employee adoption, covering diverse functions including technology, R&D, data analytics, and business operations. These tools have significantly enhanced internal productivity. For example, the technological R&D team's average delivery cycle was shortened by more than 10% in the second quarter of 2026 compared to the first quarter. The average daily lines of code submitted on AI-assisted R&D increased by over 70% sequentially, and AI contributed to more than 60% of newly added code. These improvements not only support internal AI use cases but also provide infrastructure services to external enterprise clients, resulting in strong revenue growth.

A：Strategies to reduce merchant operational pressure and empower their growth include segmenting merchants based on their business profiles, providing tailored operational support initiatives, and resources, and leveraging AI capabilities to assist in daily operations and cost management. The company has restructured its merchant facing teams, aligning strategies with each segment's core needs, and introduced more precise resource allocation. Additionally, AI integration across marketing, material creation, and customer service has helped merchants to reinvest in growth initiatives.

A：The company has restructured its merchant support by business type, implementing tiered operations that offer more tailored resources and services. Brand merchants are now under a specialized team with dedicated professional services, ad-driven merchants received resources more in line with their revenue contribution, and influencer and content-driven merchants have seen improvements in long-term viability through increased platform support and fan reach.

A：AI is deeply integrated into merchants' daily operations and cost management across various aspects such as marketing, material creation, and customer service. It is also utilized to optimize growth initiatives and has been instrumental in the positive growth cycle experienced by brand merchants on the platform. The company anticipates leveraging AI to provide a competitive edge and to help merchants achieve greater predictability in their marketing placement.

A：For the second half of the year, the company expects a moderate recovery in consumer demand with a continued shift in spending from discretionary to essential categories. Merchants are expected to prioritize operational predictability. The company plans to provide traffic resources and commission rate support while anticipating pressure on marketing service revenue and commission income. The strategies include steering traffic synergy toward brands and merchant partners with the ability and commitment to sustain long-term operations, further strengthening intelligent placement capabilities, and capturing structural opportunities to drive high-quality growth in the e-commerce business.

A：The performance of the non-e-commerce advertising segment is influenced by the broader macro environment and client marketing budgets. In the second half of the year, visibility on external conditions remains limited, and AI applications in instant retail face a high base. Customer budgets may be affected by industry competition and marketing strategy changes. However, structural opportunities are seen in some industries. Specifically, growth is anticipated in the short-form content sector, with significant cost reductions and a broader range of formats enabled by AI. The company expects to capture growth opportunities through revenue sharing incentives and domain traffic support in partnership with high-quality content and copyright holders. There is also potential for further growth in certain verticals with room for improvement in terms of monetization.

A：AI is being applied to various workflows in customer operations, including business opportunity identification, product selection, placement diagnostics, and performance reviews, as well as customer service. On the platform side, AI models improve the matching and conversion efficiency of the advertising system by better understanding marketing materials and user interests, along with intelligent bidding and price adjustment capabilities.

A：Structural growth opportunities for online marketing services will persist in the second half. The company plans to utilize AI as a key capability to optimize marketing efficiency and return on investment (ROI) for marketing placement, which will drive operational efficiency improvements and commercialization growth for clients.

A：After completing its financing, the company has gained more flexibility in managing cash flow expenditures, including addressing computing power needs through leasing. This will optimize capital allocation and improve the group's overall cash flow position. For the second half of the year, the company plans to continue a prudent financial strategy, maintain positive group-level free cash flow, and focus on executing the majority of capital expenditures (CapEx) in the first half of the year.

A：The company has focused on creating long-term value and has executed a proactive shareholder return strategy, purchasing shares and paying cash dividends. Total shareholder returns have already nearly reached last year's full-year level, while continuing to invest in the AI strategy. The company expects total shareholder returns for the full year 2026 to exceed last year's level, demonstrating its ability to generate sustainable cash flows and confidence in long-term business development.

A：The company fully embraces the AI era and aims to safeguard and strengthen its financial foundation. It is committed to reducing costs and improving efficiency through prudent financial discipline, maintaining a robust cash position, and using a resilient financial structure. The goal is to achieve a healthy and sustainable balance between business expansion and shareholder returns, thereby laying a solid foundation for high-quality, long-term growth.