A Developer’s Guide to Building AI Applications with Retrieval Augmented Generation (RAG)

A Developer's Guide to Building AI Applications with Retrieval Augmented Generation (RAG) Large Language Models (LLMs) like GPT-4, Claude, or Llama are powerful tools, but they have inherent limitations: they…

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Developing AI Applications with Retrieval Augmented Generation (RAG)

Developing AI Applications with Retrieval Augmented Generation (RAG) Introduction Large Language Models (LLMs) have revolutionized how we interact with information, but they come with inherent limitations: they can hallucinate (generate…

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Profiling and Optimizing High-Concurrency Go Applications for Low-Latency Systems

Introduction High-concurrency, low-latency systems are critical in fields like high-frequency trading, real-time analytics, and gaming. Go, with its excellent concurrency primitives, is a prime candidate for building such systems. However,…

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Mastering RAG: Building Context-Aware LLM Applications with Retrieval Augmented Generation

Mastering RAG: Building Context-Aware LLM Applications with Retrieval Augmented Generation Large Language Models (LLMs) have revolutionized how we interact with information, but they come with inherent limitations: knowledge cut-offs, the…

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Mastering Advanced Observability: From Metrics to Distributed Tracing and Beyond

Mastering Advanced Observability: From Metrics to Distributed Tracing and Beyond Introduction In today's complex, distributed systems, "it works on my machine" is a relic of the past. Microservices, serverless functions,…

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A Developer’s Guide to Integrating Large Language Models (LLMs) into Your Applications

A Developer's Guide to Integrating Large Language Models (LLMs) into Your Applications Introduction Large Language Models (LLMs) have revolutionized what's possible with artificial intelligence, offering capabilities like human-quality text generation,…

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