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Genome Evolution System

Nawal AI uses a unique DNA-based architecture encoding system to optimize model size and performance.

How It Works

  • Compression: Architecture is encoded into a 5KB genome instead of storing 500MB model weights.
  • Genetic Algorithms: The system optimizes the layer count, hidden size, and attention heads over multiple generations to find the most efficient model structure.
  • Decentralized Storage: Evolved architectures are stored in Pakit DAG storage for decentralized access.
  • Conversion: The system automatically converts genome DNA → NawalConfig → NawalTransformer via the GenomeToNawalAdapter.

Example

from nawal.genome import create_baseline_nawal_genome, genome_to_nawal
from nawal.genome.evolution import GeneticEvolver

# Create baseline genome
genome = create_baseline_nawal_genome(
    hidden_size=768,
    num_layers=12,
    num_attention_heads=12
)

# Evolve architecture
evolver = GeneticEvolver(population_size=20, num_generations=50)
best_genome = evolver.evolve(
    fitness_fn=lambda g: evaluate_perplexity(g),
    constraint_fn=lambda g: g.num_parameters() < 200_000_000
)