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Link the corpus paper (arXiv:2608.01560)
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README.md
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The method is the same every time: freeze a strong multimodal base, attach a sense from the outside, and keep every existing embedding bit-for-bit valid. Adding a sensor is a small trained head and an afternoon of compute, not a new foundation model. One shared space spans text, image, video, audio, thermal, motion and touch.
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Technical report: https://arxiv.org/abs/2607.18666. Try a real robot's memory in the live playground: https://www.eximiuslabs.com/playground.
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## The senses
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The method is the same every time: freeze a strong multimodal base, attach a sense from the outside, and keep every existing embedding bit-for-bit valid. Adding a sensor is a small trained head and an afternoon of compute, not a new foundation model. One shared space spans text, image, video, audio, thermal, motion and touch.
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Technical report: https://arxiv.org/abs/2607.18666. On what a training corpus actually teaches an audio embedding: https://arxiv.org/abs/2608.01560. Try a real robot's memory in the live playground: https://www.eximiuslabs.com/playground.
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## The senses
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