Exceptional breakdown of how latency improvements transformed voice AI from theoretical to practical. Your point about sub-second response times being the critical unlock resonates deeply because it highlights how technical constraints often determine adoption curves more than feature completeness. The observation that Deepgram + Vapi + modern LLMs now achieve one-second latency is particularly valuable. What's fascinating is how this mirrors other infrastructure shifts: broadband enabling streaming video, 4G enabling mobile apps, SSDs enabling database workloads. In each case, crossing a latency threshold didn't just improve existing workflows; it unlcoked entirely new use cases. The background noise trick you mentioned is clever but also illustrates a deeper point about human perception: we accept imperfection if it feels contextually appropriate. That's why masking micro-pauses with ambient sound works better than trying to eliminate them completely.
Fantastic breakdown
Exceptional breakdown of how latency improvements transformed voice AI from theoretical to practical. Your point about sub-second response times being the critical unlock resonates deeply because it highlights how technical constraints often determine adoption curves more than feature completeness. The observation that Deepgram + Vapi + modern LLMs now achieve one-second latency is particularly valuable. What's fascinating is how this mirrors other infrastructure shifts: broadband enabling streaming video, 4G enabling mobile apps, SSDs enabling database workloads. In each case, crossing a latency threshold didn't just improve existing workflows; it unlcoked entirely new use cases. The background noise trick you mentioned is clever but also illustrates a deeper point about human perception: we accept imperfection if it feels contextually appropriate. That's why masking micro-pauses with ambient sound works better than trying to eliminate them completely.
Totally agree, amazing comment, thank you!