
Training Data Why the Next AI Revolution Will Happen Off-Screen: Samsara CEO Sanjit Biswas
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Dec 16, 2025 Sanjit Biswas, Co-founder and CEO of Samsara, shares his unique insights on scaling AI in the physical world. He explains the key differences between physical AI and cloud-based systems, especially how real-world data like weather influences outcomes. Sanjit also reveals how Samsara leverages extensive driving data to enhance safety and efficiency, while highlighting the role of AI in coaching frontline workers. He discusses the future of autonomy in various industries, emphasizing edge computing's advantages in operational control.
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Why Physical AI Is 'Why Now'
- Physical AI required three compounding trends: ubiquitous connectivity, improved compute, and high-quality sensors.
- These ingredients made processing real-world data at scale viable for the first time.
Edge Constraints Drive Different Model Design
- Edge deployments are power- and memory-constrained, so you must design for low-watt inference.
- Samsara runs models on devices consuming roughly two to ten watts rather than datacenter-scale compute.
Cloud-To-Edge Distillation Pattern
- Train large models in the cloud and distill them into smaller task-specific models for the edge.
- Teacher–student distillation lets edge devices run relevant, compact models without general-purpose bloat.
