感谢AI和平台，音乐界也有“通货膨胀”了

Core Viewpoint - The article discusses the rapid growth of AI-generated music and its implications for the music industry, highlighting the challenges of oversupply, devaluation of music, and the changing dynamics of music consumption and creation [6][22]. Group 1: Growth of AI Music - As of the end of 2024, the total number of registered songs in China is projected to reach 263 million, with AI music platforms generating millions of songs monthly [6]. - AI music creation has significantly lowered the barriers to entry for music production, allowing anyone with basic digital skills to create music [12][13]. Group 2: Economic Implications - The demand for functional music has increased, with businesses and content creators seeking affordable, easily accessible music solutions [14][15]. - AI music tools can be used for free or at a low cost, reducing the need for traditional licensing and copyright concerns [16]. Group 3: Impact on Music Professionals - While AI will not replace top artists, it threatens the livelihoods of many music professionals, as production costs decrease and budgets shrink [17]. - The market for "functional" music is rapidly evolving, with clients opting for AI-generated music over traditional compositions, leading to a decline in fees for music creators [17]. Group 4: Changes in Music Consumption - The consumption of music is shifting from full songs to short snippets, driven by attention economy dynamics where platforms prioritize brief, engaging content [22][23]. - This "fragmentation" of music consumption results in a phenomenon where songs become background material for short videos, diminishing the recognition of artists and their works [23][25]. Group 5: Algorithmic Influence - The relationship between AI music and platform algorithms creates a self-reinforcing system where AI-generated content feeds algorithmic demands, leading to homogenization in music creation [26][28]. - Platforms are increasingly becoming content producers, with algorithms determining the visibility and success of songs, sidelining traditional evaluation methods [29].