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Pika
@pika_labs
Building AI for the future of creative work.
加入 April 2023
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Under the hood: Text → transformer prompt conditioning Generation → text-conditioned diffusion transformer in compressed acoustic latent space Output → semantic-acoustic autoencoder decodes a 44.1 kHz stereo waveform Flow matching, teacher–student distillation, and post-training with human feedback reduce the generation path to a few high-quality steps.
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