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AI Inference: Good, Fast, and Cheap, with Lin Qiao & Dmytro Ivchenko of Fireworks AI

"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis

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Optimizing AI Inference with LoRa

This chapter explores the innovative LoRa method for fine-tuning AI models, drawing parallels to OpenAI features and its benefits for developers. It highlights the significance of low-rank adaptation in reducing parameters for improved efficiency and cost savings in deployment. Additionally, the discussion covers model architecture, latency types, and optimization techniques like KV caching, focusing on improved performance for AI applications.

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