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Meryem Arik discusses strategies for designing low-cost LLM inference architectures for high-volume, non-real-time workloads. She explains how software architects and engineering leaders can achieve order-of-magnitude cost reductions by making critical trade-offs across hardware, inference runtimes, speculative decoding, and smart queue reordering. By Meryem Arik

Key takeaways

  • 01Meryem Arik discusses strategies for designing low-cost LLM inference architectures for high-volume, non-real-time workloads.
  • 02She explains how software architects and engineering leaders can achieve order-of-magnitude cost reductions by making critical trade-offs across hardware, inference runtimes, speculative decoding, and smart queue reordering.
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