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Book Overview & Buying
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Table Of Contents
LLMs in Enterprise
By :
This chapter covered key requirements for deploying LLMs in business, focusing on performance optimization and regulatory compliance. It outlined strategies for managing latency and throughput, including model optimization, load balancing, and caching. Additionally, it addressed compliance with data privacy laws, governance frameworks, and security protocols. Together, these practices ensure efficient, secure, and compliant LLM deployment, enabling real-time, scalable enterprise solutions.
The next chapter focuses on accelerating and optimizing the inferencing patterns for LLMs. It explores various strategies and techniques to enhance the speed, efficiency, and scalability of LLM inference, including hardware optimization, model quantization, and pruning. These optimizations are crucial for reducing the latency of LLMs while maintaining their accuracy and performance, enabling more practical and real-time applications in business environments.