Latency in voice interactions is important; if the response time is too long, it can break the illusion of a natural conversation, making it feel robotic.

In voice AI, reducing latency is crucial; a faster model with a refined prompt can help pass the Turing test by minimizing response delays.

Using background noise in voice applications can make users more accepting of latency, improving their overall experience.

The app should provide immediate feedback to user interactions; delays can frustrate users and lead to a poor experience.

Visual feedback is crucial in voice AI interactions; without it, users may not know if their voice is being recognized or if the system is responding.

The total response time has improved from 25 seconds to 12.5 seconds, significantly enhancing user experience by reducing the time to generate responses.

Ambient agents have less strict latency requirements compared to chat agents, as they can run for longer periods before needing a response.

Speed is critical; I aim to reduce the time between when a customer feels compelled to share feedback and when I can respond to them. When someone takes the time to communicate about your product, it's an incredible gift that should be treated with high priority. I often leave meetings to respond to such messages, even if it's just to say I'll get back to them later. This creates a sense of connection between the customer and the brand, making them feel valued.

Serving 30,000 messages per second incurs significant costs in GPU spending, and managing latency is crucial for consumer satisfaction.