Company news, media coverage, and conversations on AI simulation, physics intelligence, and our foundation model for physics.
In this SemiWiki interview, Vinci CEO Hardik Kabaria discusses why engineering requires AI systems that are repeatable, physically grounded, and usable in production workflows.
In a new conversation with Maribel Lopez on The AI with Maribel Lopez, Hardik explains why AI for physical systems must be evaluated differently than AI for language, code, or content workflows. In engineering, determinism, validation, and deployment trust are not preferences. They are requirements.
In a conversation with James Maguire on TechVoices, Hardik Kabaria explains why applying AI to physical systems requires a different standard than applying AI to language, code, or content.
This Electronics For You article covers Vinci’s thermo-mechanical simulation capability for automated warpage analysis in hardware designs.
Vinci’s physics AI foundation model delivers deterministic, solver-accurate warpage analysis across extreme scales—already in production use at leading hardware companies
In this Reuters article, Vinci discusses its $36 million Series A and its work building software for hardware simulation in chip and other design workflows.
Validated by early deployments at leading semiconductor companies, Vinci’s physics-based AI software operates up to 1000x faster than conventional simulation tools, at higher accuracy, and without training on customer data