Unlocking AI Efficiency: The Semantic Telemetry Project
As large language models (LLMs) redefine AI systems, the Semantic Telemetry project emerges as a game-changer, facilitating:
- Real-Time Insights: Analyzing hundreds of millions of Bing Chat conversations weekly.
- User-Centric Classification: Understanding expertise, topics, and satisfaction to enhance human-AI interactions.
Our engineering journey delves into:
- Scalable Architecture: A unique ETL structure combining PySpark and Polars for high-performance processing.
- Dynamic Solutions: Tackling latency, variabilities, and model evolutions with innovative strategies like:
- Dynamic Concurrency Control: Adjusts LLM calls based on real-time metrics.
- Modular Prompt Templates: Enable swift adaptations for classification tasks.
The future of human-AI interaction is bright. These insights not only drive performance improvements but also lay the groundwork for next-generation AI applications.
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