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How OpenAI delivers low-latency voice AI at scale

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Re: How OpenAI delivers low-latency voice AI at scale

#5
> Voice AI only feels natural if conversation moves at the speed of speech […] At OpenAI’s scale, that translates into three concrete requirements: Global reach for more than 900 million weekly active users

Surely the number refers to the total users of ChatGPT overall, and the fraction of those who use voice features is considerably smaller, is it not?

That’s the kind of thing that influences business decisions like knowing how much hardware and software optimization to throw at a problem.

Re: How OpenAI delivers low-latency voice AI at scale

#8

I hate the voice ai though, it's so much dumber

Fwiw - I found the advanced AI voice feature to be actually detrimental. It's good if you just want a single sentence answer. I've turned it off though when I want a more detailed, structured, considered answer.

Re: How OpenAI delivers low-latency voice AI at scale

#10
post #6

if anyone is looking to get into this. pipecat is a great open-source repo and community. https://github.com/pipecat-ai/pipecat

I wish I had known about Pipecat a lot sooner. I found out about it a few weeks back, and since Gemma 4 launched, I've been building my own entirely local voice assistant using Gemma 4 + Kokoro TTS + Whisper from scratch - https://github.com/pncnmnp/strawberry.

Pipecat's smart turn model is really good for VAD - https://huggingface.co/pipecat-ai/smart-turn-v3

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