🔮 Introduction -

Prompt: If humans can learn quickly with little data, and if we already know the components of AI, why hasn’t anyone built a truly human-like AI yet? What’s stopping us..?

This page explores -

• The core limitations of current AI
• My proposed counter solutions to each issue
• A blueprint for future human-like AI
• Why this might be the right time for indie creators to build it

🧩 Problem 1 - Integration Is Hard

Challenge -

Different AI models ( vision, language, memory, reasoning ) are built in isolation and don't work well together.

🧠 My Solution -

Analogy - Like a prism that takes white light in and splits it into usable color spectrums, we can build a converter layer between models.

🔧 Prism Layer = Converts the output of one model to be usable by another.

Why it works -

• Converts incompatible data formats
• Maintains semantic meaning between systems

Key Insight -

Integration isn’t impossible it just needs a shared interface and smart adapters.

🌍 Problem 2 - Lack of Real-World Environment

Challenge -