MeTTa as a Meta-Language

The "Meta" in MeTTa stands for its ability to act as a meta-language—a language used to define and control other languages and algorithms.

Self-Reflection (Reflection)

Because MeTTa code is stored as Atoms, a MeTTa program can "read" its own code and modify it.

Examples of Reflection

• Self-Optimization: A program can analyze its own execution trace and rewrite sections of its code to be more efficient.
• Dynamic Rule Generation: A reasoning engine can create new rules of logic base on its experiences.

Orchestration

MeTTa acts as the "glue" that connects diverse AI components in the Hyperon framework.

1. Orchestrating Neural Models

You can wrap a Python neural network (like a Transformer) and expose it as a MeTTa Atom.

;; Hypothetical code calling a neural model
(= (get-embedding $text) (py-call "model.embed" $text))

2. Orchestrating Symbol Engines

MeTTa can invoke the PLN reasoner or the MOSES program synthesizer to solve specific sub-problems and then integrate their results.

Defining Domain-Specific Languages (DSLs)

You can use MeTTa to define a small, specialized language for a specific task (e.g., a language for robotics control or for molecular biology) and then use MeTTa's core engines to execute that DSL.

Role in AGI

To achieve AGI, a system must be able to:

• Understand its own internal state (Reflect).
• Coordinate many different skills (Orchestrate).
• Adapt to new domains by creating new concepts (DSL generation).

MeTTa provides the technical foundation for all three.

Next: PRIMUS Overview