Polymathic

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Building voice-driven AI applications using LLMs

The article discusses the potential of voice-driven AI applications and the use of large language models (LLMs) in these applications. It highlights the importance of speech-to-text, text-to-speech, and the LLM itself as the three basic components for building an LLM application. The article also mentions the benefits of running application logic in the cloud, the challenges of phrase detection and endpointing, and the considerations for audio buffer management. It emphasizes the need for reliable and low-latency data flow in voice-driven LLM apps.

Original article: How to talk to an LLM (with your voice)


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About Me

Visionary leader driving digital transformation across higher education and Fortune 500 companies. Pioneered AI integration at Emory University, including GenAI and AI agents, while spearheading faculty information systems and student entrepreneurship initiatives. Led crisis management during pandemic, transitioning 200+ courses online and revitalizing continuing education through AI-driven improvements. Designed, built, and launched the Emory Center for Innovation. Combines Ph.D. in Philosophy with deep tech expertise to navigate ethical implications of emerging technologies. International experience includes DAAD fellowship in Germany. Proven track record in thought leadership, workforce development, and driving profitability in diverse sectors.

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