LLM Inference Optimization — Quantization, Speculative Decoding, and KV Cache
Optimize LLM inference speed by 10×. Master quantization tradeoffs, speculative decoding, KV cache management, flash attention, and batching strategies.
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Optimize LLM inference speed by 10×. Master quantization tradeoffs, speculative decoding, KV cache management, flash attention, and batching strategies.
Create searchable, up-to-date AI knowledge bases by ingesting documentation from Confluence and Notion with access controls, conversational search, and feedback loops.
Comprehensive guide to evaluating LLM performance in production using offline metrics, online evaluation, human sampling, pairwise comparisons, and continuous monitoring pipelines.
Comprehensive guide to versioning LLM deployments including semantic versioning, model registries, canary deployment, A/B testing, and automated rollback strategies.
Build multi-agent systems using supervisor-worker patterns, agent specialization, shared state management, and result aggregation with LangGraph.