Cadence Design Systems has announced major new collaborations focused on artificial intelligence and robotics. These partnerships aim to enhance how systems are designed, simulated, and deployed, especially in the semiconductor and robotics industries. The company revealed these updates at its recent CadenceLIVE event, highlighting its commitment to integrating AI with advanced simulation tools.

Strengthening Ties with Nvidia for Robotics and System Design

Cadence is deepening its work with Nvidia by combining AI with physics-based simulation and high-performance computing. Their joint efforts focus on modeling and deploying complex systems, including robotic platforms and large-scale AI infrastructure. Nvidia describes these as physical AI, which blends real-world physics with artificial intelligence to create more accurate simulations.

Through this partnership, Cadence will integrate its multi-physics simulation and system design tools with Nvidia’s CUDA-X libraries, AI models, and Omniverse simulation environment. These tools help engineers simulate how thermal and mechanical factors influence system behavior under real-world conditions. This approach extends beyond chip design to include infrastructure components like networking and power, enabling a comprehensive view of system performance before physical building begins.

Advancing Robotics Development with Physics Engines and AI

The collaboration also emphasizes robotics development. Cadence’s physics engines, which simulate how materials and components interact physically, are being linked with Nvidia’s AI models used for training robots in virtual environments. This allows for realistic training of AI-driven robots, reducing the need for extensive physical testing and data collection.

Nvidia’s CEO Jensen Huang highlighted the importance of these collaborations by mentioning how training robots in simulation can cut down on time and costs. The datasets used to train these models are generated through physics-based simulations, making their accuracy crucial. Cadence’s CEO, Anirudh Devgan, added that better simulation data leads to more reliable AI models, improving robotic performance in real-world scenarios.

Many industrial robotics firms, such as ABB Robotics, FANUC, YASKAWA, and KUKA, are already using Nvidia’s Isaac simulation frameworks and Omniverse digital twin tools. These tools help test robotic operations and entire production lines in virtual environments before actual deployment, reducing risks and saving time. Such digital twins simulate complex processes and production workflows, making sure everything works smoothly before physical setup.

New AI Tool for Chip Design Automation

In addition to robotics, Cadence introduced a new AI agent aimed at automating later-stage chip design tasks. This tool focuses on translating circuit designs into physical layouts on silicon chips. It builds on an earlier AI system that handled front-end design, where engineers define circuits in code-like descriptions.

The new agent simplifies the process of converting those logical designs into physical implementations, streamlining the transition from circuit concepts to manufacturable chips. This automation aims to speed up chip development and improve accuracy, helping companies meet tight production timelines and reduce errors.

Cadence plans to make this new AI agent available soon, providing chip designers with a powerful tool to accelerate their workflows. As chip complexity continues to grow, these AI-driven solutions are expected to become essential parts of the design process, enabling faster innovation in the semiconductor industry.

Overall, Cadence’s latest partnerships and tools demonstrate a clear focus on integrating AI, physics-based simulation, and automation to push forward the capabilities of both robotics and chip design. These developments promise to make systems smarter, more reliable, and quicker to bring to market, benefiting a wide range of high-tech industries.

Inspired by

• https://www.artificialintelligence-news.com/news/cadence-expands-ai-and-robotics-partnerships-with-nvidia-google-cloud/

Sources

• physicalaiconference.com
• unsplash.com
• ai-expo.net
• techexevent.com
• techforge.pub