What is Generative AI?

🧠 Generative AI is a branch of artificial intelligence that focuses on creating new content—like text, images, audio, video, or even code—based on patterns learned from existing data2.

🔍 How It Works

Generative AI models are trained on massive datasets and use deep learning techniques to understand structure and context. Once trained, they can generate outputs that resemble human-created content. Key model types include:

• Large Language Models (LLMs) like GPT, which generate text
• Generative Adversarial Networks (GANs) for realistic images and videos
• Diffusion Models used in tools like DALL·E for high-quality image generation

✨ What It Can Do

Generative AI can:

• Write essays, poems, emails, and code
• Create artwork and design prototypes
• Generate synthetic data for simulations
• Produce lifelike voices and music
• Summarize or translate content

🧩 Real-World Applications

• Software Development: Code generation and debugging
• Healthcare: Drug discovery and medical imaging
• Marketing: Personalized content and ad creatives
• Education: Tutoring and content simplification
• Entertainment: Game design, storytelling, and animation1

⚠️ Challenges & Risks

• Hallucinations: AI may produce inaccurate or misleading content
• Bias: Outputs can reflect biases in training data
• Copyright Issues: Use of copyrighted material in training
• Ethical Concerns: Deepfakes, misinformation, and job displacement

Source: https://www.ibm.com/think/topics/generative-ai

Wikepedia: https://en.wikipedia.org/wiki/Generative_artificial_intelligence