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Riffusion is a groundbreaking music creation platform powered by AI, designed to help users create music from their imagination. Currently in its beta stage, the platform demonstrates its potential through four demo tracks that cover various genres, such as contemporary hip-hop infused with funk, indie pop with atmospheric elements, melodic trap, and French house with techno influences. The San Francisco-based company behind Riffusion is a well-funded startup that is actively enhancing its technology and recruiting musicians, AI researchers, and software engineers to further develop their creative AI tools.
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Cyanite is a powerful music search and tagging platform utilizing artificial intelligence to analyze millions of songs and classify them in a short time, enabling users to provide the appropriate music content for any scenario. It features tagging, audio-based similarity search, keyword search, song recommendations, and data visualization to assist users in locating the required music efficiently. Additionally, it includes keyword cleaning to identify errors in manual tagging.
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Kits AI is a voice platform powered by artificial intelligence specifically designed for musicians to utilize and generate AI voices. It provides users with the ability to transform their voice using a selection of AI voices available from a range of either artist-licensed or royalty-free options. Users can also create and train their own AI voice through an effortless one-click RVC v2 model training process, and upload pre-existing .pth files to RVC v1 or v2 models. Music produced with voices from the commercial use library can be released without needing approval, while music using voices from the Official Artist Licensed Library requires the artist’s approval for commercial publication. During the early access beta phase, Kits AI is available for free.
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Replicate and MusicGen are tools that enable users to generate music from text through machine learning models. Replicate offers a platform for developing models with minimal coding requirements, whereas MusicGen is a model created by Facebook Research, trained on 20,000 hours of licensed music.