看看 Latent Space Pod 与 Basil Chatha 合作推出的新 Forward Deployed Engineering pod，了解企业级语音智能体构建的实际挑战和解决方案！
OpenAI、Anthropic、Google 和 Microsoft 近几个月承诺投资超过 90 亿美元将 AI 应用于企业。我们与 Decagon、Vapi、Retell、Smallest AI 和 Daily 合作，探讨构建企业语音智能体的实际挑战，包括为什么使用 STT-LLM-TTS 流程而非语音到语音模型，如何平衡智能与延迟，以及为什么轮流说话问题尚未解决。
🆕 We’re launching a new Forward Deployed Engineering pod with @realbasilchatha! https://t.co/f72We...
🆕 We’re launching a new Forward Deployed Engineering pod with @realbasilchatha ! youtube.com/watch?v=MwNvow… s In just the last few months, $9B+ has been committed by OpenAI, Anthropic, Google, and Microsoft to deploy AI into the enterprise. Model capabilities are there, but it takes a lot to make them reliable and usable for customers at scale. In our pilot episode, we dive deep into the practical realities of building enterprise voice agents with @decagon , @vapi , @retell , @smallest_ai , and @daily . We talk about: -> Why STT -> LLM -> TTS pipelines are used instead of voice-to-voice models -> How to balance intelligence vs latency for different use cases -> Why turn-taking is still not a solved problem Check it out! 💬 0 🔄 0 ❤️ 11 👀 889 📊 3 ⚡