Introduction to Generative AI

About this video

• Video Title: Introduction to Generative AI
• Channel: Qwiklabs-Courses
• Speakers: Roger Martinez
• Duration: 21:57

Overview

This video provides a comprehensive introduction to Generative AI, explaining its core concepts, how it differs from traditional AI and machine learning, and its various applications. It covers topics like AI vs. Machine Learning, supervised vs. unsupervised learning, deep learning, generative vs. discriminative models, and introduces Google Cloud's tools for leveraging generative AI, such as Vertex AI Studio, Agent Builder, and Gemini.

Key takeaways

• Definition of Generative AI: Generative AI is a type of artificial intelligence that can produce new content, including text, imagery, audio, and synthetic data, by learning from existing data.
• AI vs. Machine Learning vs. Deep Learning: AI is a broad discipline; Machine Learning is a subfield of AI that allows systems to learn from data without explicit programming; Deep Learning is a type of machine learning using artificial neural networks with multiple layers to process complex patterns.
• Generative vs. Discriminative Models: Discriminative models classify or predict labels for data points, learning the relationship between features and labels. Generative models, on the other hand, generate new data instances based on learned probability distributions of existing data.
• Applications of Generative AI: Generative AI has diverse applications, including text generation, image and video creation, code generation, and task automation.
• Google Cloud Tools for Generative AI: Google Cloud offers tools like Vertex AI Studio, Vertex AI Agent Builder, and Gemini to help developers explore, customize, deploy, and leverage generative AI models for various applications.