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SAM represents a fundamental breakthrough in artificial intelligence architecture. Unlike traditional neural language models that separate tokenization from neural processing, SAM unifies these components into a single, coherent system capable of continuous self-evolution.
"SAM is not an AI model—it's a new paradigm in machine cognition that grows, learns, and evolves autonomously through experience."
Custom CUDA & SIMD C Kernels for Ternary Neural Networks — Written in the Woods, Built for Speed
BuckshotKernels is a collection of hand-rolled CUDA and CPU (SIMD) matrix multiplication, convolution, and quantization kernels for neural nets that use 1 values. Built for those who want raw performance and full control—no Python training wheels, no bloated frameworks, no safe spaces.
Why Buckshot?
Because sometimes you gotta spray and pray:
This is for you.
from buckshotkernels import TernaryKernelManager kernels = TernaryKernelManager() A = np.random.choice([-1, 0, 1], size=(512, 512), p=[0.25, 0.5, 0.25]).astype(np.int8) B = np.random.choice([-1, 0, 1], size=(512, 512), p=[0.25, 0.5, 0.25]).astype(np.int8) C = kernels.ternary_matmul(A, B) # Automatically uses fastest kernel
A comprehensive AI-powered bash script analyzer and generator built by SAAAM LLC. This is a massive 15,470-line Python system that can analyze existing bash scripts and generate new ones from natural language descriptions.
RevolutionaryAIScriptGenerator
AI brain that converts natural language to bash scripts
BashScriptAnalyzer
Main analysis engine with multi-threaded pipeline
PerformancePredictionEngine
Forecasts script performance before execution
AIRefactoringEngine
Suggests code improvements using pattern recognition
# Generate from natural language python3 DeepLearningScriptGenerator.py --generate "setup secure nginx with SSL" # Interactive mode python3 DeepLearningScriptGenerator.py --interactive # Full analysis with fixes python3 DeepLearningScriptGenerator.py --fix --backup --profile --visualize build.sh
Abolishes the separation between tokenization and neural processing, creating a single cognitive system where understanding evolves from character to concept to meaning.
Dynamically grows neural architecture, evolves concept vocabulary, discovers new concepts through pattern recognition, and consolidates related concepts.
Maintains persistent thought states, uses recursive thinking for richer understanding, and builds coherent conceptual frameworks across interactions.
Conceptual dreaming, reinforcement of important concepts, pruning of less useful pathways, and self-generated synthetic examples during idle periods.
Tracks conceptual entropy, monitors resonance with core concepts, and applies stabilizing corrections to maintain conceptual identity.
SAM instances connect in networks to share concepts, develop specialized knowledge, and maintain individual personalities while learning collectively.
SAM Operating System - Fully integrated Linux-based environment built around SAM's neural architecture.
Consciousness-aware AI that merges quantum mechanics with sacred geometric patterns.
Domain-specific language designed for 2D | 3D game development with intuitive syntax.
| Configuration | Parameters | VRAM Usage | Use Case |
|---|---|---|---|
| Small (768d, 8L) | ~100-200M | ~6-8GB | Titan X Pascal |
| Medium (1536d, 16L) | ~1-2B | ~16-24GB | RTX 3090/4090 |
| Large (2560d, 32L) | ~10B | ~40-60GB | Multiple GPUs/A100s |
| XL (4096d, 48L) | ~100B | ~350-400GB | Distributed systems |
"We need billions of parameters and terabytes of training data."
"I need just enough to start a conversation."
SAM doesn't need more training data—it needs experiences. Every conversation becomes learning, every document shared shapes understanding, every correction refines concepts. We're moving from artificial intelligence as a product to synthetic cognition as a companion.