This document introduces the fundamentals of Generative AI, outlining its core concepts, applications, and significance in modern technology. Key topics include foundational principles, real-world use cases, and the impact of generative models across industries.
This document explores the diverse capabilities of Generative AI, including text, image, audio, video, code, data generation, and virtual world creation with real-world applications and examples. It also covers the latest advancements in multimodal AI, AI agents, and the impact of generative AI on various industries.
This document traces the evolution of Generative AI, from early rule-based systems in the 1950s to the latest advancements in Large Language Models (LLMs), highlighting key milestones like GANs and Transformers.
This document covers the wide-ranging applications of Generative AI across various domains such as content creation, drug discovery, engineering finance and healthcare.
This document provides an overview of leading tools and platforms for text generation, including LLMs like GPT and PaLM, as well as open-source and commercial solutions for creative, conversational, and code-related tasks.
This document provides an overview of leading tools and technologies for image generation using generative AI, including DALL-E, Stable Diffusion, StyleGAN Craiyon, Freepik, Picsart, Fotor, Deep Art Effects, DeepArt.io, Midjourney Microsoft Bing Image Creator, and Adobe Firefly.
Overview of generative AI tools for audio and video, including speech generation, music creation, audio enhancement, and video synthesis. Covers key platforms, capabilities, and real-world applications in creative and professional domains.
Comprehensive overview of generative AI tools for code generation, including capabilities, strengths, limitations, and key platforms such as ChatGPT Gemini, Copilot, Polycoder, Watson Code Assistant, Amazon CodeWhisperer, Tab9 and Repl.it. Covers productivity, best practices, and ethical considerations.