Developer Experiments with Moving AI Reasoning Into Latent Space on DeepSeek

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A developer has shared an experimental project that attempts to shift the 'thinking' process of DeepSeek's AI model into latent space, rather than performing it in the standard token output space. The approach, dubbed 'latent reasoning,' packages this modified reasoning mechanism as a standalone model. The project was shared on Hacker News as a personal showcase post, attracting modest early attention. Details of the methodology are outlined on the developer's personal blog. The work appears aimed at exploring more efficient or internalized reasoning architectures for large language models.

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