#3 Definitions and Jargons

ℹ️ Overview

Omar Shanti emphasizes that leveraging AI effectively requires connecting advanced models to your proprietary data and systems. He demystifies AI concepts, breaking down the analytics spectrum and explaining the differences between classical machine learning and generative AI. Shanti underscores the importance of understanding these tools’ strengths to create meaningful and innovative business outcomes.

📒 Key Takeaways

1. Proprietary Data as a Core Asset:

   • Proprietary data combined with advanced AI models leads to significant business differentiation and meaningful results.
   • Businesses should integrate models with their systems to maximize impact.
     
     

2. Analytics and AI Expertise:

   • Analytics operates on four tiers:
     • What happened? – Focuses on event tracking.
     • Why did it happen? – Requires causality models.
     • What will happen? – Involves forecasting, entering the AI domain.
     • How can we make it happen? – Heavily dependent on AI capabilities.
   • As complexity increases, so does the need for AI expertise.
     
     

3. Types of Artificial Intelligence:

   • Deterministic AI: Encodes predefined rules (e.g., if/else logic, simple programs like tic-tac-toe).
   • Machine Learning: Relies on historical data for predictive and decision-making tasks (e.g., candidate success rates, fraud detection).
   • Generative AI: Focuses on creating content like text, images, and code, exemplified by tools like ChatGPT and Claude.
     
     

4. Complementary Use of Classical and Generative AI:

   • Classical machine learning remains relevant for traditional AI use cases (e.g., fraud detection, statistical models).
   • Generative AI addresses newer, creative, and innovative use cases like text completion, image generation, and code generation.
   • Combining both types of AI often yields the best results by leveraging their unique strengths.
     
     

5. Practical Applications:

   • Use discriminative/classical AI for predictive analytics and operational efficiency.
   • Employ generative AI for content creation, conversational interfaces, and novel solutions.