You can only really recognize AI-generated music if you've created it yourself. SUNO provides the most likely suitable patterns for each genre and pieces them together so that it almost certainly sounds like the input prompt. Whether it's created in Georgia, the USA, or on my desk in Munich, the music always sounds the same. A month ago, we were at a heavy metal festival in Italy, and what was interesting was that all the bands looked the same and used the same sound, the same mannerisms, and the same lyrical clichés in their lyrics. What is it that bothers the AI? It primarily delivers compromises, as if you were playing in the wrong band, and after lengthy discussions, your original idea became a compromise that no longer fully reflects your vision. The digital reject pool of SUNO-generated songs is enormous. Of the 2500 credits, 10 go towards the song itself and 50 credits for downloading stems, which can then be further processed in Audacity, GarageBand, or Logic. This is where you hear what's so problematic about AI music: the poor sound quality and the repetitive compositional patterns that have been used for years in certain genres. Interestingly, while the accuracy of the prompts has improved, the sound quality and musical range remain limited. The gradual acoustic desensitization of listeners due to constant access to low-quality music leads to the continued use of AI tools instead of real instruments. Because one hopes for new ideas from AI, frustration is high when AI, like humans, relies on existing patterns. Therefore, to be truly creative, a band needs a high degree of internal tension to be truly innovative. In times of cancel culture, such conditions are not sought after, and therefore the number of generic, run-of-the-mill music continues to increase.
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