From 13c655708db27a9a5d51721310f95c2fe117a300 Mon Sep 17 00:00:00 2001 From: dsh Date: Fri, 18 Oct 2024 07:48:55 +0100 Subject: [PATCH] Update introduction@_hYN0gEi9BL24nptEtXWU.md Co-authored-by: Kamran Ahmed --- .../ai-engineer/content/introduction@_hYN0gEi9BL24nptEtXWU.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/data/roadmaps/ai-engineer/content/introduction@_hYN0gEi9BL24nptEtXWU.md b/src/data/roadmaps/ai-engineer/content/introduction@_hYN0gEi9BL24nptEtXWU.md index a3b6f2db7..b2d0b3880 100644 --- a/src/data/roadmaps/ai-engineer/content/introduction@_hYN0gEi9BL24nptEtXWU.md +++ b/src/data/roadmaps/ai-engineer/content/introduction@_hYN0gEi9BL24nptEtXWU.md @@ -1,3 +1,3 @@ # Introduction -AI Engineering is the field focused on designing, building, and deploying AI systems to solve real-world problems. It merges software engineering, data science, and machine learning to create scalable and efficient solutions. AI Engineers handle tasks from data preparation and model training to integrating AI into software applications, ensuring these systems perform reliably in production. Covering areas like natural language processing, computer vision, and robotics, AI Engineering bridges the gap between research and real-world application, driving innovation across industries such as healthcare, finance, and autonomous systems. \ No newline at end of file +AI Engineering is the process of designing and implementing AI systems using pre-trained models and existing AI tools to solve practical problems. AI Engineers focus on applying AI in real-world scenarios, improving user experiences, and automating tasks, without developing new models from scratch. They work to ensure AI systems are efficient, scalable, and can be seamlessly integrated into business applications, distinguishing their role from AI Researchers and ML Engineers, who concentrate more on creating new models or advancing AI theory. \ No newline at end of file