NVIDIA发布NemoClaw智能体开放蓝图
NVIDIA推出NemoClaw开放蓝图，将调优后的开放模型、智能体框架、优化与遥测工具以及OpenShell运行时治理组合起来。该蓝图支持OpenClaw、Hermes Agent和LangChain Deep Agents，使开发者能够在自有且可定制的基础设施上组装专用智能体。NVIDIA称，针对LangChain Deep Agents调优的Nemotron 3 Ultra配置接近前沿水平，单次运行成本约为领先闭源模型的十分之一，但该数据来自厂商自述。
NemoClaw将模型、智能体框架、可观测性与运行时策略控制整合为面向生产智能体的开放技术栈。
Building an autonomous agent requires a model, a harness, and domain-specific tools. To deploy an agent more securely, developers need a runtime that enforces policies, along with optimization and observability tools for reliable execution.
For production agents, the challenge lies in making these agents capable and safe to operate with access to real enterprise systems and data.
This post explains how these components work together, with a focus on how NVIDIA NemoClaw open blueprints enable developers to build specialized agents on a stack they can own, customize, and run. This post provides criteria to help developers integrate NemoClaw with a harness they already use: OpenClaw, Hermes Agent, or LangChain Deep Agents.
What an agent harness provides
An agent requires four things:
- A model that reasons.
- A harness that defines how the agent operates.
- Tools and skills that extend its capabilities.
- A runtime that governs what the agent can access and do in production.
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