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Watching the Generative AI Hype Bubble Deflate
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Only a few short months ago, Generative AI was sold to us as inevitable by the leadership of AI companies, those who partnered with them, and venture capitalists. As certain elements of the media promoted and amplified these claims, public discourse online buzzed with what each new beta release could be made to do with a few simple prompts. As AI became a viral sensation, every business tried to become an AI business. Some businesses added "AI" to their names to juice their stock prices, and companies talking about "AI" on their earnings calls saw similar increases. While the Generative AI hype bubble is now slowly deflating, its harmful effects will last.
Forward citations
Cited by 3 Pith papers
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A Fourier Explanation of AI-music Artifacts
Zero-upsampling in audio generators replicates the low-frequency spectrum at fixed intervals, creating architecture-dependent spectral peaks that enable a simple, interpretable detector for AI-generated music.
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AI-Generated Music Detection and its Challenges
A simple convolutional classifier detects autoencoder-generated music with 99.8% accuracy, but accuracy collapses under audio manipulation and on unseen generator families.
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Segment Transformer: AI-Generated Music Detection via Music Structural Analysis
A two-stage transformer framework classifies AI-generated music from short clips and beat-segmented full tracks, reporting 99.9% accuracy on SONICS without releasing code or ablations.
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