What do y'all think about the latency/quality tradeoff with LLMs?
Human voices don't take 30 seconds to think, retrieve, research, and summarize a high quality answer. Humans are calibrated in their knowledge, they know what they understand and what they don't. They can converse in real time without bullshitting.
Frontier real time-ish LLM generated voice systems are still plagued by 2024 era LLM nonsense, like the inability to count Rs in strawberry. [1]
I'd personally love a voice interface that, constrained by the technology of today, takes the latency hit to deliver quality.
Not affiliated with Sesame, but this is what the realtime models are trying to solve. If you look at NVIDIA’s PersonaPlex release [0], it uses a duplex architecture. It’s based on Moshi [1], which aims to address this problem by allowing the model to listen and generate audio at the same time.
Human voices don't take 30 seconds to think, retrieve, research, and summarize a high quality answer. Humans are calibrated in their knowledge, they know what they understand and what they don't. They can converse in real time without bullshitting.
Frontier real time-ish LLM generated voice systems are still plagued by 2024 era LLM nonsense, like the inability to count Rs in strawberry. [1]
I'd personally love a voice interface that, constrained by the technology of today, takes the latency hit to deliver quality.
[1] https://www.instagram.com/reel/DTYBpa7AHSJ/?igsh=MzRlODBiNWF...