理解人Understand people
融合语言指令、场景观测、任务进度和历史记忆，理解复杂任务意图与执行约束。Fuse language, scene observation, task progress, and memory to understand intent and execution constraints.
Synkrotron / World Action Model
构建面向物理世界智能的闭环系统A closed-loop system for physical-world intelligence
清科灵境以 World Action Model 为核心，结合 Dora 低延迟数据流底座与 Lingo 产品体系，让机器人和智能设备能够理解任务、生成动作，并在真实反馈与仿真经验中持续进化。Synkrotron builds around the World Action Model, Dora's low-latency dataflow foundation, and the Lingo product system so robots and intelligent devices can understand tasks, generate actions, and improve through real feedback and simulated experience.
Why it matters
具身智能的壁垒，不在单点演示，而在持续闭环The moat is not a demo. It is the loop
真实场景中的机器人需要同时理解人、会操作、能实时闭环。模型、数据、仿真和控制必须形成一个持续吸收失败、扩展经验、验证风险并回到机器本体的系统。Robots in real environments must understand people, operate physically, and close the loop in real time. Models, data, simulation, and control need to work as one system that absorbs failures, expands experience, validates risk, and returns to the embodiment.
会操作Operate physically
基于环境状态、物体关系和动作逻辑，生成可执行、可约束、可适配的长程动作。Generate executable, constrained, and adaptable long-horizon actions from state, object relations, and action logic.
实时闭环Close the loop
将真实反馈、失败样本和人类纠偏回流为数据资产，驱动下一轮训练、评测和部署。Turn feedback, failure cases, and human correction into data assets for the next training, evaluation, and deployment cycle.
Lingo Product System
从真实示教到虚拟推演，构建物理世界中持续进化的具身智能From real-world demonstrations to simulated reasoning — embodied intelligence that keeps improving
Lingo Brain 赋予机器人理解任务和执行动作的能力；Trace 标准化采集真实轨迹，Data 将原始传感转化为可训练的模型资产，World 在虚拟世界中扩展经验边界。四个产品协同，将感知、决策、执行和反馈连成一条持续收敛的闭环。Lingo Brain gives robots the ability to understand tasks and execute actions. Trace standardizes real-world capture, Data transforms raw sensor streams into trainable model assets, and World expands the experience frontier through simulation. Together they connect perception, decision, execution, and feedback into a continuously improving loop.
Lingo Brain
任务理解、动作规划、执行控制与持续学习，赋予机器人本体可闭环的具身智能。Task understanding, action planning, execution control, and continuous learning — end-to-end embodied intelligence that closes the loop on real robots.
查看产品Open productLingo Trace
标准化采集真实世界操作轨迹、多模态传感器数据与人类专家示教，构建高质量具身基座数据集。Standardized capture of real-world trajectories, multimodal sensor streams, and expert human demonstrations for embodied foundation datasets.
查看产品Open productLingo Data
多模态具身数据治理、标注、版本管理与训练集构建，将原始采集转化为可复用的模型燃料。Multimodal embodied data governance, labeling, versioning, and training-set engineering — turning raw capture into reusable model fuel.
查看产品Open productLingo World
构建高保真仿真世界，生成合成数据与长尾场景，在虚拟环境中训练、评测并完成 Sim2Real 验证。High-fidelity simulated worlds, synthetic data, and long-tail scenarios for training, evaluation, and Sim2Real validation.
查看产品Open productSolutions
以 AI Lab 为旗舰，扩展到更多物理世界场景AI Lab as the flagship, expanding across physical-world scenarios
清科灵境以科学实验机器人与自主实验室承接 AI4S 场景，同时将同一套闭环能力延展到自动驾驶仿真与合成数据、具身数据生产等高价值场景。Synkrotron anchors its AI4S story in scientific robots and autonomous labs, while extending the same closed-loop capability to autonomous-driving simulation, synthetic data, and embodied data production.
Technology Foundation
三层架构，一道护城河Three layers. One moat
WAM 统一感知与动作空间。Dora 承载毫秒级数据流。飞轮让每次失败成为下一次更强的起点。WAM unifies perception and action. Dora carries real-time dataflow. The flywheel turns failure into advantage.
World Action Model
统一编码任务意图、环境状态与人类指令，联合生成动作并预测物理演化。一个模型，端到端。Unifies task intent, environment state, and human instruction to jointly generate actions and predict physical evolution. One model, end to end.
Dora Runtime
零拷贝张量管道，毫秒级延迟。承载感知、推理与控制的实时协同，开源，边缘可部署。Zero-copy tensor pipelines at millisecond latency. Carries perception, inference, and control in real time. Open-source. Edge-deployable.
虚实双向飞轮Real-Synthetic Flywheel
真实失败回流 → 仿真扩展长尾 → 模型迭代 → 回到部署。物理世界越用越强。Real failure → simulated long-tails → model iteration → back to deployment. Every run makes the system stronger.