We can’t communicate how AI works to regular humans and it’s a big problem
AI Summary
- Introduction
- Nostalgic reference to pre-Google internet experience.
- AI as a new means of discovery, similar to hyperlinks.
- Understanding Latent Space
- Critical issue: lack of understanding of latent space in large language models (LLMs).
- Current challenges with prompting and building applications with AIs are due to navigating latent space.
- Examples of how companies monetize the complexities of utilizing LLMs.
- Communication Gaps
- Need for clearer communication about how LLMs function.
- Most explanations are overly complex, making it hard for users to understand and engage with AI interfaces.
- Building with AI: Eight Steps
- Step 1: Ideation - Use AI for brainstorming ideas/features.
- Step 2: Architecture - Outline how the AI will work and where information is stored.
- Step 3: Data Structure - Understand data schema and structure.
- Step 4: Setup Environment - Prepare the building environment with the necessary tools.
- Step 5: Backend Implementation - Establish the database/library of information first.
- Step 6: Frontend Development - Build the UI while ensuring backend data is robust.
- Step 7: Testing - Implement tests to ensure the application functions as intended.
- Step 8: Deployment - Make the finished app accessible to users.
- Conclusion
- Emphasis on the importance of improving communication about LLMs and fostering better understanding for broader adoption and creativity in technology usage.
- Encouragement to find simpler ways to explain complex concepts of AI to enhance accessibility.