Perceptron 发布 35B 具身智能模型 Mk1.5，请求完成速度最高提升 4.7 倍
机器人公司 Perceptron 出了个 35B 的第一人称视频模型，MMSearch 上开了搜索工具 F1 直接从 18.2 涨到 54.3，做具身智能的可以看看。
Perceptron 发布 35B 具身智能模型 Mk1.5，请求完成速度最高提升 4.7 倍。该模型专门用第一人称（egocentric）视频训练，针对机器人与智能眼镜中手部频繁入镜、遮挡和相机移动的场景。在 MMSearch 基准上，启用工具后 F1 从 18.2 提升到 54.3，提升 36.1 分，可用能力包括网页搜索、页面阅读、反向图搜索和图像放大。
Perceptron released Mk1.5, a 35B embodied-agent model with up to 4.7× faster request completion.
4. First-person video is a very different problem from ordinary video understanding.
For a robot or a pair of smart glasses, hands constantly enter the frame, manipulate objects, disappear, return, and partially occlude what matters. The camera itself is moving too.
Perceptron trained Mk1.5 specifically on egocentric video, and very interestingly the model gets a 36.1-point jump on MMSearch when tools are enabled. Moves from 18.2 to 54.3 F1 when it can use web search, page reading, reverse-image search, and zoom.
This is a useful way to think about embodied intelligence too.
A robot does not need every possible capability encoded into its weights. It needs to recognize when its current information is insufficient, pick the right external capability, use it, then continue the task.
