A staff of AI researchers at Meta’s Basic AI Analysis staff are making 4 new AI fashions publicly accessible to researchers and builders creating new purposes. The staff has posted a paper on the arXiv preprint server outlining one of many new fashions, JASCO, and the way it may be used.
As curiosity in AI purposes grows, main gamers within the subject are creating AI fashions that can be utilized by different entities so as to add AI capabilities to their very own purposes. On this new effort, the staff at Meta has made accessible 4 new fashions: JASCO, AudioSeal and two variations of Chameleon.
JASCO has been designed to simply accept various kinds of audio enter and create an improved sound. The mannequin, the staff says, permits customers to regulate traits such because the sound of drums, guitar chords and even melodies to craft a tune. The mannequin may settle for textual content enter and can use it to taste a tune.
An instance can be to ask the mannequin to generate a bluesy tune with a whole lot of bass and drums. That may then be adopted by related descriptions concerning different devices. The staff at Meta additionally in contrast JASCO with different methods designed to do a lot the identical factor and located that JASCO outperformed them throughout three main metrics.
AudioSeal can be utilized so as to add watermarks to speech generated by an AI app, permitting the outcomes to be simply recognized as artificially generated. They be aware it can be used to watermark segments of AI speech which were added to actual speech and that it’s going to include a business license.
The 2 Chameleon fashions each convert textual content to visible depictions and are being launched with restricted capabilities. The variations, 7B and 34B, the staff notes, each require the fashions to achieve a way of understanding of each textual content and pictures. Due to that, they will do reverse processing, equivalent to producing captions of images.
Extra data:
Or Tal et al, Joint Audio and Symbolic Conditioning for Temporally Managed Textual content-to-Music Technology, arXiv (2024). DOI: 10.48550/arxiv.2406.10970
Demo web page: pages.cs.huji.ac.il/adiyoss-lab/JASCO/
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