Source URL: https://news.ycombinator.com/item?id=41710227
Source: Hacker News
Title: Show HN: A real time AI video agent with under 1 second of latency
Feedly Summary: Comments
AI Summary and Description: Yes
Summary: The text discusses the innovative efforts of Tavus, an AI research company, in developing a conversational video interface with low latency suitable for human-computer interactions. The focus is on overcoming technical challenges to achieve under 1-second latency, which is critical for creating realistic and engaging digital twin experiences.
Detailed Description: The content outlines the experiences of the co-founders of Tavus, achievements in AI-based video models, and the technological hurdles they faced during the development process. Key points include:
– **AI Video Models**: Tavus specializes in creating digital twins or avatars, utilizing AI-driven video interfaces, aiming for an interactive experience that replicates human conversation.
– **Latency Challenges**:
– Achieving low latency was fundamental for the project’s success. The target was to keep the conversation latency below 1 second, ideally near 600 ms, to mimic natural, human-like interactions.
– Understanding the nuances of conversation dynamics, including the typical timing between statements, influenced architecture decisions.
– **Architecture Considerations**:
– The development of the system involved balancing latency, scalability, and overall costs. The team transitioned from a focus on seconds to a precise measurement of milliseconds.
– An initial reliance on expensive, high-performance hardware (H100 GPUs) was deemed unsustainable. They moved towards more efficient models, like the newly designed Phoenix-2, which utilized Gaussian Splatting to enhance processing speed and performance on lower-end hardware.
– **Optimizations Implemented**:
– Streamlining the model architectures for each component, including vision, automatic speech recognition (ASR), large language models (LLM), text-to-speech (TTS), and video generation.
– Focused specifically on minimizing time-to-first token with the LLMs, emphasizing that fast token generation alone was insufficient for real-time communication.
– Investigated techniques to accurately detect end-of-speech, mitigating latency arising from conventional methods reliant on silence detection.
– **Resulting Customer Engagements**:
– Tavus has attracted clients such as Delphi, facilitating extended conversations with digital twins, showcasing the application potential of their technology in training and coaching scenarios.
Overall, Tavus’s journey highlights significant advancements in AI video interaction and practical engineering solutions to achieve real-time digital communications, presenting valuable insights for professionals in AI, cloud, and infrastructure security fields regarding the intersection of innovative technology and user experience.