The dominant recipe for building better language models has not changed much since the Chinchilla era: spend more FLOPs, add more parameters, train on ...
Understanding audio has always been the multimodal frontier that lags behind vision. While image-language models have rapidly scaled toward real-world deployment, building open models ...
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