Astrus, a Toronto and Waterloo-based AI startup, has secured $8 million in funding to accelerate development of its physics-aware foundation model for analog chip design. The round was led by Khosla Ventures, with participation from Pradeep Sindhu (founder of Juniper Networks), 1517 Fund, Drive Capital, Alumni Ventures, and other strategic backers.
While digital chip design has seen significant automation advances, analog layout remains a slow, manual process—often requiring months of engineering and costing hundreds of millions for cutting-edge designs. Astrus is tackling this challenge with a reinforcement learning architecture that understands the physics behind chip design, enabling it to generate thousands of optimized layouts in seconds.
Founded by Brad Moon and Zeyi Wang, with a team that includes RL expert Kenny Young, Astrus draws on breakthroughs from AlphaGo and applies them to semiconductor layout. The company’s technology promises to dramatically reduce design timelines and unlock new circuit architectures beyond human intuition.
How the funding will be used: With the new capital, Astrus plans to grow its research and engineering team, scale its compute infrastructure, and deliver AI-powered tools to top semiconductor companies working on next-generation chips.
KEY QUOTES:
“Analog layout is one of the biggest bottlenecks in the design process for the most advanced microchips. Our AI learns the physics behind chip design, allowing us to automate what has always been a manual process. This funding enables us to accelerate chip development for the world’s leading teams and drive faster progress in compute.”
Brad Moon, co-founder and CEO of Astrus
“We’re scaling toward one of the largest reinforcement learning training runs ever attempted, engineered to push chip design past human limits.”
Kenny Young, Astrus’s Founding Research Scientist
