Lead with the senses; sense packs above the base models

README.md

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 ![Eximius Labs](assets/banner.png)
 
-Eximius Labs builds open-weight multimodal models and tools that run on your own hardware: the embedding, perception, memory, and control layers for physical AI. The technical report is on arXiv: https://arxiv.org/abs/2607.18666. Try a real robot's memory in the live playground: https://www.eximiuslabs.com/playground.
+Eximius Labs builds open models that give machines senses. Touch, heat, motion and sound become things you can search in plain language, on hardware you own.
 
-We freeze a strong base model and add new senses from the outside, so existing embeddings stay valid and gaining a modality never forces a re-index. One shared vector space spans text, image, video, audio, thermal, motion (IMU), and touch.
+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.
 
-## Fusion Embedding, the embedding layer
+Technical report: https://arxiv.org/abs/2607.18666. Try a real robot's memory in the live playground: https://www.eximiuslabs.com/playground.
 
-One vector space for cross-modal retrieval, RAG, clustering, and semantic search.
+## The senses
+
+Each pack is separately loadable and leaves the base model untouched.
 
-- [fusion-embedding-2](https://huggingface.co/EximiusLabs/fusion-embedding-2-2b-preview) — text, image, video, and audio in one space (connector plus modality-gated adapters).
-- [fusion-embedding-1](https://huggingface.co/EximiusLabs/fusion-embedding-1-2b-preview) — the connector-only first generation.
 - [Ember](https://huggingface.co/EximiusLabs/fusion-embedding-2-ember) — thermal and infrared, as a loadable sense pack.
 - [Tremor](https://huggingface.co/EximiusLabs/fusion-embedding-2-tremor) — body-worn and robot motion (IMU and accelerometer), read as language, with a [Unitree-G1 head](https://huggingface.co/EximiusLabs/fusion-embedding-2-tremor-g1).
 - [Tactus](https://huggingface.co/EximiusLabs/fusion-embedding-2-tactus) — touch (32x32 pressure/taxel arrays from FSR gloves, e-skins, and robot hands), as a loadable sense pack; matches, and at best exceeds, the STAG (Nature 2019) supervised baseline while remaining open-vocabulary.
 - [Tactus Mat](https://huggingface.co/EximiusLabs/fusion-embedding-2-tactus-mat) — the same tactile pack trained for a 64x32 body pressure mat (bed, seat, wheelchair, insole): 17 in-bed postures answered as text queries, 0.957 top-1 on held-out subjects.
+
+## The base models
+
+The shared space itself: one vector space for cross-modal retrieval, RAG, clustering and
+semantic search. The senses above attach to these and never modify them.
+
+- [fusion-embedding-2](https://huggingface.co/EximiusLabs/fusion-embedding-2-2b-preview) — text, image, video, and audio in one space (connector plus modality-gated adapters).
+- [fusion-embedding-1](https://huggingface.co/EximiusLabs/fusion-embedding-1-2b-preview) — the connector-only first generation.
 - [fusion-embedding-2-k3-vision](https://huggingface.co/EximiusLabs/fusion-embedding-2-k3-vision) — Kimi K3's vision encoder, projected into the shared space.
 
 ## Fusion Perception, the perception layer