Context and Latency
Fine-tuning models like Llama offers fast inference and effective performance, but challenges arise with larger models in answer generation. As context length increases, the complexity of instructions will evolve, yet trade-offs between latency and business outcomes remain critical. Even slight delays can significantly impact revenue, highlighting the delicate balance between context utilization and system performance.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Why Your RAG Pipeline Is Broken, and How to Fix It with Jason Liu - 709
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