Lecture Notes: Artificial General Intelligence Orientation

Date:

• Orientation Day 2

Key Topics Discussed:

Introduction

• Discussion on AGI (Artificial General Intelligence)
• Review of five levels of AGI based on recent OpenAI document

Five Levels of AGI

1. Chatbots

   • Interaction through natural language
   • Example: ChatGPT (provides high accuracy and human-like interaction)

2. Reasoners

   • Ability to reason and solve problems at a human level
   • Discussed scenarios where reasoning is applied (e.g., Nvidia's deep learning solutions)
   • Importance of reasoning in conversations

3. Agents

   • AI systems that can take actions independently from human interaction
   • Example: AI managing calendars and bookings autonomously
   • Multiple agents working together to accomplish tasks

4. Innovators

   • AI that can invent new ideas and contribute to human knowledge
   • Ability to research and develop own improvements

5. Organizations

   • AI capable of performing work of an organization independently
   • Questions raised about potential impact on human jobs

Project Strawberry and Future Developments

• Discussion about Strawberry AI and its relevance in the market
• Future predictions on AGI and how it will evolve over the next few years

Technical Insights

• API and Microservices

  • Importance of APIs in integrating different services
  • FastAPI as a preferred framework for building APIs

• Docker and Kubernetes

  • Utilization of Docker for creating development environments
  • Kubernetes for orchestration of microservices

Python Programming

• Emphasized the importance of learning Python for subsequent modules
• Overview of the resources needed for Python programming (e.g. FastAPI, PostgreSQL, etc.)

Learning Path and Course Structure

• Description of stack levels:
  • Stack Zero: Local AI Microservices Development Stack
  • Stack One: Serverless with OpenAI API
  • Stack Two: Custom AI Stack with PyTorch and Llama

General Advice

• Importance of consistency in learning and practicing new skills
• Encouragement for students to take ownership of their learning journey

Questions and Clarifications

• Discussion on if API training should include big data understanding
• Noted differences between theory and practical applications in projects

Conclusion

• Encouraged further engagement with the material and reaffirmed the importance of practice and consistency in learning.