Leading Tech Voice Lambasts AI Media Generation as Cringe, Citing Suno's Valuation and Industry Disconnect

A prominent tech commentator, known for his AI coverage, has issued a sharp critique of current AI media generation technologies, drawing a clear distinction from Large Language Models (LLMs) and their application in software development. Citing his background as an audio engineer, the commentator expressed deep concern over the trajectory of tools like Suno, highlighting its reported $2.45 billion valuation as an “insane” figure within an industry that generates roughly $30 billion annually. His core argument posits that successful AI integration should augment existing professional “toolboxes”—such as Copilot assisting developers within VS Code—rather than attempting to replace established creative workflows and software. He contends that companies developing media generation AI often lack fundamental understanding of the creative fields they aim to disrupt, leading to solutions that are neither viable nor valuable for seasoned professionals.

The critique extends to the inherent malleability of different media types: code is highly adaptable, images moderately so (allowing for post-generation refinement), while music and video are significantly less flexible, making full-replacement AI problematic. The commentator argues that current AI media generation primarily serves “unmotivated people who don’t care about music that much” rather than genuinely empowering aspiring artists, citing examples of groundbreaking music produced with accessible, low-cost tools and a wealth of free educational resources. Furthermore, the economic realities of the creator economy, coupled with restrictive copyright practices from major labels (exemplified by the Netspend case and the Facebook-Warner deal), exacerbate these issues, creating an ecosystem where AI’s disruptive potential is misdirected. He advocates for AI development focused on automating tedious tasks within professional tools—like Co-create’s video workflow automation or Daddy Kev’s music engineering tools—asserting that domain experts learning to code offer a more promising path for truly useful AI integration than “tech bros” attempting to replace established industries. Crucially, the commentator differentiates LLMs, which generate value beyond human consumption, from media generation AI, whose value is almost exclusively tied to human consumption, deeming the latter inherently less impactful and “soulless” from a creative standpoint.