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 interactions, latency is crucial; responses should ideally be under one second to maintain a good user experience.

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

Once the auditory system has established tonotopic maps, background white noise at a low volume shouldn't pose a problem for learning, as it can support a heightened state of alertness and dopamine activation.

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.

Voice applications reduce user friction by allowing users to express their thoughts verbally, which is often less intimidating than typing.

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

Studies show that low-intensity white noise can significantly improve performance in auditory working memory tasks by enhancing neural circuitry activation.

We realized that our initial ideas for speech recognition weren't feasible, which led us to pivot and focus on developing noise cancellation technology.