How Does Generative AI Work, and How Is It Changing Industries and Business?
PART 1. How Does AI Understand Language?
Understand the fundamental concepts behind generative AI.
- What Is a Token?
- What Is an LLM (Large Language Model)?
- What Is a Parameter?
- How Does AI Convert Language into Numbers?
- How Does AI Understand Relationships Between Words and Sentences?
- What Is a Context Window?
PART 2. How Does AI Learn and Generate Answers?
Understand how AI learns and produces responses.
- What Does AI Learn?
- Why Does AI Training Require So Much Data?
- What Is Pre-Training?
- What Is Fine-Tuning?
- What Is Inference?
- Why Can AI Be Biased?
PART 3. Why Are AI Models So Different from One Another?
Understand the differences between AI models and services.
- What Is the Difference Between Large and Small AI Models?
- What Is the Difference Between General-Purpose AI and Task-Specific AI?
- What Is the Difference Between a Base Model and a Fine-Tuned Model?
- What Is the Difference Between Open-Source AI and Proprietary AI?
- What Is the Difference Between Cloud AI and On-Device AI?
- How Is AI Model Performance Compared?
PART 4. What Powers the AI Industry?
Understand the industries and infrastructure that make AI services possible.
- Why Does AI Need GPUs?
- Why Do AI Training and Inference Have Different Cost Structures?
- Why Do AI Services Need Data Centers?
- Why Are Electricity and Cooling Important for AI?
- Why Are AI Companies Also Building Smaller Models?
- Why Is Semiconductor Competition Important in the AI Era?
PART 5. How Does AI Change the Way Companies Work?
Understand how work changes before and after AI adoption.
- How Does Information Search Change Before and After AI Adoption?
- How Does Document Creation Change Before and After AI Adoption?
- How Does Customer Support Change Before and After AI Adoption?
- How Does AI Connect with Existing ERP and CRM Systems?
- How Does the Role of People Change in the AI Era?
- What Makes a Company Good at Using AI?
