Lecture on Generative AI
General Overview
- Ever since computers were invented: They have been glorified calculators executing exact instructions given by programmers.
- Recent Advancement: Computers now have the ability to learn, think, and communicate like humans (Generative AI).
- Impact: Generative AI can affect every individual and company positively or negatively.
- Key Product: Products like GPT (Generative Pre-trained Transformer) make intelligence available as a service.
What is Generative AI
- Analogy: Imagine having Einstein in your basement, representing collective intelligence. You can talk to him, but the main limitation is your imagination and communication skills.
- Prompt Engineering: The skill of effectively communicating with the AI is essential.
Traditional AI vs Generative AI
- Traditional AI: Machine learning, computer vision, recommendations, and search results.
- Generative AI: Generates new, original content instead of just classifying existing content.
Large Language Models (LLMs)
- Definition: A type of Generative AI that communicates in human language.
- Chat GPT: A product by OpenAI that started as an LLM using Transformer architecture.
How it Works
- Neural Networks: Convert words into numbers, process them, and convert numbers back into words.
- Training: LLMs are trained on large datasets using a process called backpropagation.
- Reinforcement Learning: Involves human feedback for better and more accurate results.
Types of Generative AI Models
- Text-to-Text: Generates text (e.g., GPT models).
- Text-to-Image: Generates images from textual descriptions.
- Image-to-Image: Transforms or combines images.
- Image-to-Text: Describes the contents of an image.
- Speech-to-Text: Voice transcriptions.
- Text-to-Audio: Generates music or sounds.
- Text-to-Video: Generates videos.
Applications and Trends
- Multi-modal AI Products: Combine different models into a single product.
- Example: Chat GPT mobile app can interact with text, images, audio, etc.
- Emergent Capabilities: AI can now roleplay, write poetry, code, advise on strategy, among other tasks.
Exponential Growth and Impacts
- Human Intelligence vs AI: Human intellectual abilities are static, while AI capabilities are growing exponentially.
- Past Revolutions: Compared to fire, agriculture, printing press, etc., AI evolves much faster.
Mindsets Towards AI
- Denial: 'AI cannot do my job' – dangerous.
- Panic: 'AI will take my job' – unhelpful.
- Balanced Positive Mindset: AI will make you and your company more productive.
Human Roles in the Age of AI
- Continued Necessity: Human domain knowledge and judgment are still needed.
- Example Roles: Doctors, developers, lawyers, CEOs, teachers, etc., can use AI as a tool but still need to guide and manage it.
Interaction with AI Models
- Product vs Model: Users interact with products (apps, websites), not directly with AI models.
- APIs: Allow developers to integrate models into their products.
Prompt Engineering
- Example: Planning a workshop – iteratively refine prompts for better results.
- Importance: Key skill for effective use of AI.
Future Trends
- Autonomous Agents: AI entities with tools to execute tasks autonomously.
- Prompt Design: Essential for managing autonomous AI.
Key Takeaways
- Tool for Productivity: Generative AI can significantly enhance productivity.
- Imagination and Skills: The main limitations are your imagination and prompt engineering skills.
- Deliberate Practice: Improve prompt engineering skills through consistent practice.
Hope this video was helpful!