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Last year’s emergence of user-friendly interfaces for models like DALL-E 2 or Stable Diffusion for images and ChatGPT for text generation was key to boost the world’s attention to generative AI. Some people expect that a “ChatGPT moment” for AI-powered music generation is just around the corner.
For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. It sounds like ChatGPT for images, and it is actually named SegGPT. Source: [link]. SegGPT Many successful approaches from NLP are now being translated into computer vision. Source: own study.
For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. It sounds like ChatGPT for images, and it is actually named SegGPT. Source: [link]. SegGPT Many successful approaches from NLP are now being translated into computer vision. Source: own study.
The pre-train and fine-tune paradigm, exemplified by models like ELMo and BERT, has evolved into prompt-based reasoning used by the GPT family. LLMs have gained widespread popularity, with ChatGPT reaching approximately 180 million users by March 2024. This has sparked interest in smaller language models (SLMs) like Phi-3.8B
Symbolic Music Understanding ( MusicBERT ): MusicBERT is based on the BERT (Bidirectional Encoder Representations from Transformers) NLP model. It addresses issues in traditional end-to-end models, like datascarcity and lack of melody control, by separating lyric-to-template and template-to-melody processes.
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