Small Models, Specific Jobs: ScaleDown on Building Efficient Voice AI
In this episode of the Convo AI World Podcast, Hermes Frangoudis speaks with Neal Patel, co-founder of ScaleDown, about choosing models for the specific jobs inside an AI application. Neal explains how his work forecasting data center demand led him to focus on token efficiency. At ScaleDown, that means building small language models for tasks such as classification, extraction, and summarization. He describes how the team combines existing model components with task-specific neural heads, and where these specialists can work alongside a larger model that handles planning and conversation…
The skinny
The skinny isn't ready yet — notes appear once the transcript is processed.