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Sure seems like Fenix Flexin used AI music generator Treblo
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The maker of the Treblo AI music model released an open-source classifier that can detect whether a track was generated with Treblo, and applied it to Fenix Flexin’s charting song “Rubberz,” finding it very likely AI-generated.
Engineers building music-creation or moderation tools now have a concrete example of a model-specific detector being made publicly available, showing how provenance can be traced back to a single generator. The release also highlights the limits of such detectors: they only work for the model they were trained on and can produce false positives, so reliance on them alone cannot settle disputes over AI-generated content.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
The Treblo AI Music Classifier is open source and designed to flag audio produced exclusively by the Treblo model.
When run on Fenix Flexin’s “Rubberz,” the classifier returned a high confidence score indicating the track is very likely Treblo-generated.
Because the detector is model-specific and has a non-zero false-positive rate, it cannot be used as definitive proof in legal or platform-policy decisions.
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What elseif makes of it.
On Monday the company behind Treblo published the source code for an AI music classifier that looks for signatures of its own model in audio files. The tool is intended to help platforms or rights holders identify when a song was created solely with Treblo. When the classifier was run on the track “Rubberz” it output a high probability score, labeling the song as very likely Treblo-generated. This marks the first time the maker’s own detector has been used to assess a commercially successful hit.
Adopting the classifier requires integrating its code into existing audio-processing pipelines and allocating compute for inference on each uploaded track. Teams must also maintain the model as updates to Treblo are released, otherwise detection accuracy may drift. Because the classifier is open source, there is no licensing fee, but engineering effort is needed to wrap it in a service and handle its output. The documentation notes a low false-positive rate, meaning occasional legitimate recordings could be flagged as AI-generated.
The detector only recognizes audio that matches the statistical patterns of Treblo and will not flag songs made with other generative models or traditional production. A low confidence score does not prove a track is human-made; it merely indicates insufficient evidence of Treblo involvement. Determined users could potentially alter AI-generated audio to evade detection, reducing the tool’s reliability in adversarial settings. Consequently, the classifier should be treated as one piece of evidence rather than conclusive proof in any takedown or royalty decision.
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