Why Time-To-First-Token Is The Key To Speed And Safety In Physical AI

InnovationWhy Time-To-First-Token Is The Key To Speed And Safety In Physical AIByLee-Lean Shu,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 11, 2026, 07:30am EDTLee-Lean Shu, CEO, GSI Technology. getty​Reaction time is a critical feature of AI. Say you’re trying to rebook a hotel reservation and you get connected to a customer support chatbot. If that chatbot responds quickly to your requests, the interaction can feel helpful. If the response time is slow, you’re more likely to get frustrated and abandon the attempt and switch to another vendor.This reaction time, known as time-to-first-token (TTFT), is how quickly an AI system generates output after receiving a request. In physical AI applications, like warehouse robots or delivery drones, this reaction speed is critical. That’s because a fast TTFT isn’t a matter of mere convenience; it can actually improve overall safety and increase productivity.In physical AI, the time it takes to process inputs and respond directly affects how effectively the machine can do its job. For example:• Microsecond-level responses can control basic motor functions, like maintaining direction.• Sub-15-millisecond responses can let the robot integrate more complex motor functions.• Sub-50-millisecond responses can let the robot integrate multiple motor response effects and perform emergency obstacle avoidance.• Sub-three-second responses can support higher-level awareness and decision-making, allowing more natural obstacle avoidance.Consider a simple two-wheeled robot in which motor sensors control its motion. When both wheels are aligned, the robot goes straight. To turn, one wheel moves faster than the other. This type of basic system can react to inputs in microseconds.Integrating AI can add more sophisticated controls, such as torque stabilization or adaptive gait generation, but f...