Lecture Notes: Mastering AI Chatbots

Introduction

• Host: Bogdan
• Objective: To provide a comprehensive guide on AI chatbots, covering their operation, construction, and marketability.
• Reference to Leah Motley’s AI chatbot tutorial from a year ago.
• Rapid technology updates over the past year: More capable GPT models, increased token limits, new vision tools, and audio capabilities.
• Aim: Updated version of the guide focusing on AI chatbots.

AI Business Potential

• Overview of the potential of AI in business.
• Important stats and implications for leveraging AI opportunities.

Understanding AI Chatbots

• Two types of chatbots:
  • Rule-based: Limited, manual, predefined rules.
  • AI-powered: Use large language models (LLM) for understanding and responding.
• Key Elements of AI Chatbots:
  • User Prompt: User's input/query.
  • Knowledge Base: Information database.
  • LLM: Processes input and generates responses.
• Token Limitations:
  • GPT-3.5: 4096 tokens.
  • GPT-4.0: 128,000 tokens.
• Concept of "chunking" to manage token usage efficiently.
• Use of embeddings for semantic analysis and information retrieval.

Prompt Engineering

• Importance of effective prompts in building efficient AI chatbots.
• Types of Prompt Engineering:
  • Conversational: For small tasks/personal use.
  • Single-shot: For scalable AI solutions.
• Main Components of a Good Prompt:
  • Role: Role prompting.
  • Task: Chain of thought prompting.
  • Specifics: Emulsion prompt technique.
  • Context: Combination of role and emotion prompt.
  • Examples: Few-shot prompting.
  • Notes: Final guidelines and hacks.
• Tips for prompting:
  • Implement multiple techniques for improved performance.
  • Consider prompt length and cost.
  • Choose the appropriate model.
  • Temperature settings for randomness control.

Practical Use Cases

• Benefits: Enhanced engagement, 24/7 availability, cost savings, personalized communications, data analytics.
• Automation Examples:
  • Lead qualification and customized sales funnels.
  • Product recommendation with website scraping for affiliates.

Useful Tools for Building AI Chatbots

• Chatbase: Document and website data integration, new tools like Notion, Zapier, Slack integration.
• Dante AI: Google Drive and Sheets as knowledge sources, lead generation, and meeting booking.
• Voiceflow and Botpress: Flexible chatbot builders, modular structure, require some technical knowledge.
• Integration Tools:
  • Make.com and Zapier: Workflow automation, suitable for connecting various apps.
• Custom Code: Using Node.js, TypeScript, AWS for high flexibility and reduced costs.

Tutorials

• Building a basic and advanced customer support chatbot using various tools.
• Example projects showing the potential and flexibility of custom-coded solutions.

Large Language Models Overview

• Comparison of top LLMs: Google's Gemini, Anthropic's Claude, OpenAI's GPT-4.0.
• Considerations for choosing an appropriate model based on task requirements.
• Importance of testing different models to find the best fit for specific tasks.

Conclusion

• Encouragement to utilize AI opportunities early.
• Importance of mastering the technical and sales aspects of AI solutions.
• AI Fellowship program introduction for further learning and community support.