Update 8-summary.md

kprks · web-flow · commit 3e5bcd1f49cd · 2025-06-06T12:16:18.000-05:00
diff --git a/learn-pr/philanthropies/architecture-of-thought/includes/8-summary.md b/learn-pr/philanthropies/architecture-of-thought/includes/8-summary.md
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-## Summary
-
-In this module, learners explore the core concepts, architecture, and applications of AI-powered dialogue systems. Starting with a high-level overview, they learn what dialogue systems are, how they function, and where they are used across industries like customer support, education, and healthcare.
+In this module, learners explore the core concepts, architecture, and applications of AI-powered dialogue systems. Starting with a high-level overview, learners discover what dialogue systems are, how they function, and where they're used across industries like customer support, education, and healthcare.
 
 The module covers the main components of a dialogue system: the user interface, the natural language processing engine, the dialogue management layer, the knowledge base, and the response generation layer. Each part plays a key role in enabling natural, efficient interactions between users and AI.
 
 Learners also examine the AI models behind these systems, such as GPT-3 and GPT-4. They also examine how conversational AI uses large-scale training and reinforcement learning to improve performance over time. Azure Open AI is introduced as the main platform for prototyping and deploying dialogue models. We focus on Azure Open AI's scalability, integration features, and real-time testing tools.
 
-By the end of the module, learners gain a solid foundation in how AI-powered dialogue systems are built and why they are essential to modern digital experiences. This prepares them for more advanced tasks such as creating custom models, fine-tuning outputs, and designing human-like interactions in future modules.
+By the end of the module, learners gain a solid foundation in how AI-powered dialogue systems are built and why they're essential to modern digital experiences. This prepares learners for more advanced tasks such as creating custom models, fine-tuning outputs, and designing human-like interactions in future modules.
