Inference Time Tactics: Voice Intelligence at Scale - From Call of Duty to Fraud Detection with Modulate AI
Every year, the world generates over a trillion hours of voice data across gaming, financial services, and customer support. Despite this volume, the vast majority of these conversations remain a "black box" to machines.
In the latest episode of Inference Time Tactics, hosts Calvin Cooper and Yash Sharma sit down with Carter Huffman, the CTO and Co-founder of Modulate, to discuss the architecture behind Velma 2.0—a system designed to understand voice at scale.
Moving Beyond General Foundation Models
- While large foundational models are powerful, they are often too slow and expensive for real-time, high-volume voice applications. Modulate has taken a different approach: an orchestration layer that manages over 100 specialized models. This ensemble architecture allows for:
* Nuanced Understanding: Capturing tone, emotion, and intent that traditional text transcripts miss entirely.
* Cost Optimization: Using "exploration vs. exploitation" algorithms to identify the most efficient model subset for a specific conversation, leading to order-of-magnitude cost savings.
* Real-Time Moderation: Successfully protecting massive ecosystems like Call of Duty from harassment and toxicity.
The Future of Context
- The conversation also explores the development of "context graphs." Instead of analyzing isolated snippets of audio, the next generation of voice AI aims to map participant intent and causality across entire interactions. This is a must-watch for anyone interested in inference optimization, audio machine learning, or the future of real-time moderation.
Learn how Modulate is redefining voice intelligence at the link below.
Listen to the full episode: https://inferencetimetactics.podbean.com/