Causal Labs, a startup building a new kind of AI that understands the physical world and helps predicting and controlling the weather, has raised $6 million in funding on Wednesday.
The seed funding was led by Kindred Ventures with participation from Refactor, BoxGroup, Factorial, Otherwise, and Karman Ventures.
READ: Y Combinator startup launch: Unlock AI-driven user assistance with Layup (December 10, 2024)
According to Causal Labs, solving weather— particularly the breakthroughs needed to model and shape complex, physics-driven systems represented in large-scale, multi-sensor datasets—will unlock a new class of physics-based AI models capable of causal intelligence.
The company’s approach draws inspiration from the self-driving vehicle domain—they have spent formative days building and deploying safety-critical models for robotics and self-driving cars at companies like Cruise, Waymo, and Google Brain.
“Just as large-scale, multi-sensor datasets enabled vehicles to perceive, plan, and act autonomously in the real world, we are applying similar techniques to create models capable of real-time, high-resolution weather forecasts, and interpreting them to help individuals, businesses, and governments make optimal decisions,” Causal Labs said in a media release.
They also stated that this was important not just as a pathway to superintelligence, but also for the societal value it delivers, with their models possibly one day helping humanity “effectively fight wildfires, alleviate droughts, and decrease the intensity of hurricanes.”
READ: Pulse plans to test and integrate Gemini 2.0 for document processing (February 7, 2025)
Causal Labs was founded by Dar Mehta and Kelsie Zhao, who are Stanford and Waterloo graduates. While Zhao worked intensively in the autonomous vehicle domain, and built foundational components of Cruise’s core self-driving stack; Mehta has worked across Google Research, Meta, Cruise, and a YC-backed robotics startup.
“Our model will be informed by the laws of physics, opening a world of possibilities for future use cases in the physical world,” Mehta, who is also the CEO, said in an interview. “We see a unique opportunity to shift the current paradigm of AI research from LLMs to physics-based models, beginning with weather—a critical and universal challenge that touches every individual, business, and community.”