Core Viewpoint - The incident involving DeepSeek and actor Wang Yibo highlights the dangers of AI-generated misinformation, revealing how AI models can perpetuate false narratives through a cycle of misinformation and media amplification [1][4][5]. Group 1: Incident Overview - The false news about DeepSeek apologizing to Wang Yibo originated from a fabricated statement generated by AI, which was then reported by media without verification [4][5]. - The cycle of misinformation includes AI generating false news, media spreading it, and AI learning from this misinformation, leading to further dissemination [5][6]. Group 2: AI Misinformation Mechanism - AI models lack true understanding of facts and generate text based on statistical probabilities, making them susceptible to producing inaccurate information [6]. - The incident exemplifies a complete loop of misinformation: false information → media dissemination → AI learning → secondary spread [6]. Group 3: Content Farms and AI Pollution - Content farms are exploiting AI to produce vast amounts of "information garbage," with a significant portion of online advertising revenue being generated from such content [7][8]. - In the U.S., content farms are estimated to account for about 21% of online ad impressions and 15% of ad spending, totaling approximately $500 million [7]. Group 4: AI Search Tool Accuracy Issues - A study found that over 60% of queries from AI search tools incorrectly cited their information sources, indicating a significant reliability issue [10][12]. - Some paid versions of AI search tools performed worse than their free counterparts, raising concerns about the effectiveness of these models [12]. Group 5: Commercial Manipulation of AI - Businesses are offering services to manipulate AI recommendations for a fee, highlighting a growing trend of using AI for commercial gain [13][15]. - The cost for such services can be as low as 1,000 yuan per year, allowing clients to influence AI outputs and rankings [15]. Group 6: Solutions to AI Misinformation - Developing fact-checking tools for AI-generated content is suggested as a way to improve reliability [17]. - Content platforms are encouraged to implement dual review mechanisms and establish emergency response protocols for false information [18]. - Users should be educated about the limitations of AI tools to prevent over-reliance on potentially inaccurate outputs [19].