Anthropic Launches Model Hardware Standard for AI-Enabled Robotics
- Published
- Source
- leaderobot.com
On August 27, Anthropic officially released a research preview of the Model Hardware Standard (MHS). This unified specification is designed for the safe operation of physical devices by AI agents, enabling models like Claude to directly interpret and control robots, scientific instruments, and industrial equipment.
The MHS aims to replicate the success of the Model Context Protocol (MCP) in the software domain, which serves as a universal language for AI interactions with applications like Gmail and Slack. By establishing standardized 'dialogue rules' between AI and hardware, MHS simplifies programming interfaces into basic commands such as 'read' and 'write', allowing devices to discover and communicate across networks without the need for specialized coding.
Notably, MHS enables AI to understand previously unseen devices by incorporating essential information like weight and safety limits directly into the standard. Anthropic's collaboration with the Janelia Research Campus has led to the initial preview being made available to select research labs and advanced manufacturers, with plans for open-sourcing after the preview period. The AI-driven robotics market is projected to reach a trillion-dollar valuation by 2035, highlighting the significance of MHS in bridging AI capabilities with physical operations.
Original report
Anthropic Unveils Model Hardware Standard for AI-Driven Robotics
leaderobot.com · LeaderobotThis briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
Rights concerns? Contact [email protected] with the relevant URL and details. We will review the matter and take appropriate action where warranted.
More related news
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
-
9
RobotToday Weekly October 5 – 9, 2026 RobotToday · 3 days ago
- 10
- 11
- 12
Related Suppliers
Anthropic
United States
AI safety and research company and public benefit corporation that builds the Claude family of large language models.
Numurus LLC
United States
Seattle software company building NEPI, a source-available ROS 2 edge AI platform with plug-and-play drivers and AI orchestration for robots and smart systems.
AtomBite.AI 元界智能
China
Beijing embodied-AI startup building a flexible-manipulation foundation model and the M1 takeout-packing robot for commercial kitchens.
Versatile Robotics
Germany
Wessling, Germany DLR spinoff founded 2024; builds patented MPTC controller software for safe, high-speed human-robot collaboration.
Gerhard Schubert GmbH
Germany
German family-owned global market leader in digital top-loading packaging machines with AI-driven robotic systems since 1966.
Rainbow Robotics
Korea, Republic of (South)
Korean robotics maker building collaborative robots, quadrupeds, dual-arm manipulators and HUBO humanoids from KAIST-originated technology.
Onyx Robotics
United States
Boston-based AI controls startup founded 2022, providing cloud platform and tooling for physics simulation and hardware AI model training.
Opto 22
United States
US manufacturer of edge programmable industrial controllers, edge I/O and solid state relays for automation, IIoT and remote monitoring.
Tech Rim Standards LLC
United States
US manufacturer of NAAMS automation components, robot-cell cable reels (Tech-Winder), and end-of-arm tooling for automotive, aerospace, and packaging.
Deccan AI
United States
Enterprise data company providing expert-curated SFT, RLHF datasets, RL environments and evaluations for training LLMs and AI agents.
Lovell AI
United States
Texas startup building a hybrid-cloud Physical AI platform that designs, trains and deploys multi-agent robot brains for industrial robot fleets.
Thinking Robots Inc.
United States
Developer of AI software enabling robots to be instructed in natural language without programming or prior training, with on-the-fly learning and task.
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
Join the RobotToday community on LinkedIn
Daily robotics news, in-depth analysis, conference highlights, and discussions with professionals worldwide.
