**Covariant 发布 RFM-1 机器人基础模型，开创人工智能推理新纪元**
全球领先的仓库机器人公司 Covariant，其国内分公司深圳灵变科技有限公司，近日宣布推出革命性的 RFM-1 机器人基础模型。这一创新技术标志着生成式人工智能在商业机器人领域的重大突破，首次赋予了机器人类似人类的推理能力，使其能够更深入地理解和应对语言与物理世界。
RFM-1 的核心特性包括物理世界模型、语言引导编程和自我反思学习。通过物理世界模型，机器人能够实时理解并适应其操作环境，实现灵活的动态决策。语言引导编程则让机器人能够理解并执行基于自然语言的指令，极大地简化了人机交互的复杂性。而自我反思学习功能则允许机器人从过去的经验中不断学习和改进，提升其智能水平和任务执行效率。
Covariant 的这一创新将对物流、制造业及其他自动化领域产生深远影响，为未来的智能机器人应用打开了新的可能。RFM-1 的推出，不仅提升了机器人在实际工作中的智能程度，也为人类与机器人的协作提供了更为高效和自然的方式，预示着人工智能与实体世界融合的新篇章。
英语如下：
**News Title:** “Covariant Launches RFM-1: A New Era in Robotic Reasoning, Bestowing Human-like Intelligence on Machines”
**Keywords:** RFM-1 Robot, Reasoning Capabilities, Covariant
**News Content:**
Covariant, a global leader in warehouse robotics, and its domestic subsidiary, Shenzhen Lingbian Technology Co., Ltd., have recently unveiled the groundbreaking RFM-1 robot base model, ushering in a new era in artificial intelligence (AI) reasoning within the robotics industry.
This innovative technology represents a significant milestone in generative AI for commercial robots, endowing them with human-like reasoning abilities, enabling them to comprehend and respond more deeply to both language and the physical world.
Key features of RFM-1 include a physics-based world model, language-guided programming, and self-reflective learning. With the physics-based world model, the robot can dynamically understand and adapt to its operating environment in real-time, facilitating agile decision-making. Language-guided programming empowers the robot to comprehend and execute commands in natural language, significantly simplifying human-robot interaction. The self-reflective learning function allows the robot to learn and improve from past experiences, enhancing its intelligence and task execution efficiency.
Covariant’s innovation is set to have a profound impact on logistics, manufacturing, and other automated sectors, opening up new possibilities for future applications of intelligent robots. The introduction of RFM-1 not only increases the cognitive capabilities of robots in practical tasks but also offers a more efficient and natural mode of collaboration between humans and machines, heralding a new chapter in the convergence of AI and the physical world.
【来源】https://covariant.ai/insights/rfm-1-a-world-model-that-understands-physics/
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