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Book Overview & Buying
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Table Of Contents
LLMs in Enterprise
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The operational viability of connected LLM systems hinges on their ability to deliver responsive, cost-effective performance at scale. As highlighted in a 2024 McKinsey analysis of enterprise AI deployments, organizations report that performance considerations directly impact adoption rates, with systems exceeding 500 ms latency seeing 30–40% lower user retention (McKinsey Digital, 2024). This reality has driven significant innovation in optimization techniques that address the unique challenges of multi-model architectures, where bottlenecks can emerge from model coordination overhead, sequential dependencies, and resource contention.
The performance characteristics of these systems differ fundamentally from single-model deployments. A joint study by Microsoft Research and Carnegie Mellon University identified three primary sources of inefficiency in connected LLM architectures: inter-model communication latency (accounting for 35–50% of...