Preeti
Sumit, a Senior SDE at a major Tech company, has started learning about Generative AI (GenAI) and noticed the lack of cohesive information on the topic. In this article, he aims to provide a basic understanding of Generative AI and its evolution.
Artificial Intelligence (AI) is the field of Computer Science focused on creating machines that can perform tasks requiring human intelligence. Machine Learning (ML) is a subset of AI where systems learn from data to optimize processes and innovate quickly. ML applications learn from experience and find insightful information without direct programming.
Neural networks are machine learning models that mimic the human brain’s decision-making process. Deep learning, a subset of ML, uses multi-layered neural networks to simulate complex decision-making.
Generative AI is a type of AI that can create new content like text, images, and videos. Foundation models are neural networks trained on massive datasets to handle various tasks, while Large Language Models (LLMs) are trained on vast amounts of data to understand and generate natural language.
Sumit’s article provides a clear overview of the basics of AI, ML, neural networks, and deep learning before delving into Generative AI. By summarizing key concepts and providing references for further reading, he aims to simplify the understanding of Generative AI for beginners.
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Source link: https://medium.com/@kumarsumit.flyhigh/get-started-with-generative-ai-3957a7203181?source=rss——large_language_models-5
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