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Physical AI is one of the hardest engineering problems the technology industry has faced.
Autonomous vehicles, industrial robots, delivery drones, surgical assistants, and humanoids have to sense the physical world, make decisions in real time, and act on them safely — all while meeting tight power, performance, and cost targets.
Among the many engineering challenges this presents, two are especially important: integration and functional safety.
Physical AI systems combine compute, AI models, sensors, actuators, mechanical and structural hardware, operating systems, middleware, cloud services, and applications, all of which have to work together as a single system. Today, much of that technology is developed and validated in isolation, placing the time, cost, and engineering burden of integration on Tier 1 suppliers and OEMs.
Functional safety raises the bar further. A machine that moves through the physical world and acts on its own decisions must do so predictably, even when conditions are dynamic and unpredictable. That requirement reaches into every layer of the system, changing how each one is designed, verified, and validated.
Because these challenges are beyond the reach of any single company, technology leaders are working together to simplify integration, strengthen functional safety, and accelerate the design and development of physical AI systems.
Architecting Physical AI SoCs with Standards‑Based IP for Real‑World Intelligence
A proven collaboration model, extended to a new market
Synopsys is helping address these challenges through our participation in the new Arm Total Design for Physical AI ecosystem. As part of this ecosystem, we’re working with Arm to provide interface IP, virtual development kits, and a complete silicon-to-systems design flow for companies developing autonomous vehicles, robots, and other physical AI systems.
Arm Total Design brings companies across the technology ecosystem together to collaborate on the compute, IP, tools, software, and services needed to accelerate system development. We have participated in Arm Total Design for Cloud AI since the ecosystem was formed in 2023, collaborating with Arm across multiple markets and technologies, including Arm Neoverse Compute Subsystems (CSS) for cloud, data center, and 5G infrastructure.
With Arm Total Design for Physical AI, we are building on that collaborative model to address the integration challenge of systems that combine compute, software, AI models, sensors, and actuators.
Three areas of collaboration
We are working with Arm across three connected areas to accelerate the development of physical AI systems:
- Interface IP for Arm CSS-based physical AI systems. These systems must deliver high performance within tight power budgets while meeting demanding safety requirements. We offer functionally safe, automotive-grade-ready interface IP developed for these conditions, backed by extensive experience in functional safety across IP and EDA. By integrating and validating our interface IP with Arm Zena CSS, we will give customers a pre-integrated foundation they can use with our hardware-assisted verification solutions to develop safe, reliable physical AI systems.
- Virtual development kits for physical AI. Electronics digital twins (eDTs), virtual prototypes, and hybrid setups with hardware-assisted verification allow software development, integration, and validation to begin before physical hardware is available. Building on our experience delivering a Virtualizer Development Kit for Arm Zena CSS, we are extending these technologies to physical AI platforms, helping developers accelerate software readiness, evaluate system behavior earlier, and reduce integration risk across systems that combine AI, software, sensors, and hardware.
- A complete silicon-to-systems design flow. Our capabilities span architecture exploration, interface and foundation IP, verification, digital implementation, silicon lifecycle management, and system simulation and analysis. Together, these capabilities connect decisions across chip architecture, implementation, software, and system behavior, helping teams develop physical AI systems as an integrated whole.
These areas reinforce one another. Pre-integrated and pre-validated IP provides the silicon foundation, virtualized development allows software integration and validation to begin earlier, and the broader design flow supports the engineering work from chip architecture through system-level analysis.
A faster path to physical AI systems
Pre-integrated, pre-validated solutions for physical AI remain limited, increasing development complexity and risk. Addressing that gap requires an ecosystem approach.
By bringing expertise across compute, IP, tools, functional safety, and services together, Arm Total Design for Physical AI gives companies a faster, more direct path to developing and validating deployable systems. Through our participation, Synopsys is helping build the integrated foundation needed to move physical AI systems from concept to deployment.
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