Genesis 2 — Cascade MoE Neural Network

The World's First Patented Neural Architecture That Runs on CPU

Academic \$299 • Professional \$1,499 • Enterprise \$4,999 • Source + Patent Bundle \$5,000 • Interactive Reference Guide

Try the Live Demo — click the link in the Gist for the current demo URL. Model hosted on Kaggle. If the demo is unavailable, email avlarionov@hotmail.com to request a restart.

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What is Genesis 2?

Genesis 2 is a fundamentally new neural network architecture that eliminates the need for GPU, external LLMs, and massive compute resources. It uses Cascade Activation of a Shared Neuron Pool — a patented approach where experts share neurons instead of duplicating parameters.

No GPU. No Cloud. No API costs. No token limits. Runs on your laptop.

Traditional MoE:  Expert₁[500MB] + Expert₂[500MB] + ... = 50GB+, GPU required
Genesis 2:        Expert₁[route] + Expert₂[route] + ... = 3.5GB total, CPU only
                  ↑ shared neuron pool, each expert is just a list of neuron IDs

Why Genesis 2?

Traditional AI (GPT, LLaMA, etc.)	Genesis 2
$2,000+/mo GPU costs	$0 — runs on CPU
API rate limits & downtime	Unlimited — self-hosted
Data leaves your network	100% on-premise
Catastrophic forgetting	Zero forgetting — mathematically guaranteed
Minutes to fine-tune	130ms to learn a new fact
Token window limits (4K-128K)	Infinite context — no limits
Vendor lock-in	You own the code

Quick Start

# Install dependencies
pip install torch numpy requests

# Start the web server
python genesis2_web.py

# Open in browser
open http://localhost:8765

API

import requests

API = "http://localhost:8765"

# Ask a question (returns answer + executable commands)
r = requests.post(f"{API}/api/query", json={"question": "configure nginx reverse proxy"})
print(r.json()["answer"])
print(r.json()["commands"])

# Teach new knowledge (learns in 130-550ms)
requests.post(f"{API}/api/learn", json={
    "question": "how to restart Apache",
    "answer": "Restart Apache web server",
    "exec": "systemctl restart apache2"
})

# Save state
requests.post(f"{API}/api/save")

Benchmarks

Metric	Value
Trained Experts	10,800+
Shared Neurons	12,100+
Accuracy (30-query benchmark, RU+EN)	100% (30/30)
Inference latency	18-27ms
Learning speed	130-550ms per new fact
Zero forgetting (cosine similarity)	1.000000
Cross-lingual similarity (RU↔EN)	0.97
Cascade routing	0.14ms
RAM usage	3.5GB model + ~2GB runtime
GPU required	No

Test Results (30/30)

✅ привет                          → Привет! Я Genesis 2...
✅ hello                           → Hello! I'm Genesis 2...
✅ проверь диск                    → df -h
✅ check disk space                → df -h
✅ настрой NAT masquerade          → iptables -t nat -A POSTROUTING...
✅ OSPF Cisco                      → vtysh -c 'show ip ospf neighbor'
✅ nmap сканирование               → nmap
✅ fail2ban защита SSH             → fail2ban jail.local
✅ Docker ps контейнеры            → docker ps
✅ nginx настрой                   → nginx config
✅ configure nginx reverse proxy   → nginx -t
✅ установи Zabbix                 → zabbix config
✅ pg_dump бэкап PostgreSQL        → pg_dump
✅ DNS BIND сервер                 → named-checkconf
✅ Active Directory Samba          → samba-tool domain provision
✅ WireGuard VPN туннель           → apt install wireguard
✅ iptables правила                → iptables -L -n
✅ Asterisk SIP                    → asterisk -rx
✅ systemctl статус                → systemctl status
✅ установи bind9                  → apt install bind9
... and 10 more — all passing

Architecture

Genesis 2 is built on 8 patented innovations:

1. Shared Neuron Pool

All neurons live in a single shared pool. Experts don't have their own parameters — they reference neurons by ID. One neuron can serve 50+ experts simultaneously. This makes the model 100x smaller than traditional MoE.

2. Expert as Route

Each expert is just a list of neuron IDs — a "route" through the shared pool. Adding a new expert costs bytes, not megabytes. 10,000 experts fit in 3.5GB.

3. Cascade Activation (No Router)

Traditional MoE uses a trained router to pick experts. Genesis 2 uses a reverse index (neuron → experts) to find relevant experts in 0.14ms. No router training, no routing errors.

4. One-Step Learning

To learn a new fact: freeze all shared neurons, create a new expert with a micro-head. Takes 130-550ms. The new knowledge never interferes with existing knowledge.

5. Zero Catastrophic Forgetting

Each expert has its own micro-head (output layer). New experts can't modify existing ones. Mathematically guaranteed — cosine similarity = 1.000000 before/after learning.

6. Hash Neuron Embedding

Custom embedding system with 9,761 tokens across 72 types. No dependency on external models (MiniLM, BERT, etc.). Fully self-contained.

7. Infinite Context

Every learned fact becomes a permanent expert. No token window limits. 10,000 facts = 10,000 experts, all accessible instantly.

8. Native Generation via Concept Chains

Output is generated through a composer that chains related concepts from activated experts. Not template matching — actual generation.

Input → Hash Embedding (512d) → ANN Search → Seed Experts
     → Cascade Activation → Shared Neuron Pool → Composer → Output

Knowledge Domains (22)

Note: The included model is primarily trained on Russian-language data for networking, servers, and infrastructure. It understands English queries but responds best in Russian. Genesis 2 learns new facts in 130ms — you can train your own model on any language and any domain in minutes, not days.

Networking (Cisco, MikroTik)	Linux Administration	Docker & Kubernetes
Security & Hardening	WiFi Configuration	DNS/DHCP/BIND
VPN (WireGuard, OpenVPN)	Databases (PostgreSQL, MySQL)	Web Servers (Nginx, Apache)
Monitoring (Zabbix, Prometheus)	DevOps (Ansible, Terraform)	Python Scripting
Bash Automation	Packet Analysis	VoIP (Asterisk)
Windows Active Directory	macOS Administration	Virtualization
SCADA/ICS	Cloud (AWS/GCP/Azure)	Server Configuration
Mobile Protocols

System Requirements

Component	Minimum	Recommended
CPU	Any modern (ARM or x86)	4+ cores
RAM	6 GB	16 GB
Disk	4 GB	10 GB
Python	3.9+	3.11+
PyTorch	2.0+	2.3+
OS	macOS / Linux / Windows	Any
GPU	Not required	Not required

Patent

Status: Filed at FIPS Russia, 31.05.2026 Type: Utility Model, IPC G06N 3/04 Claims: 2 independent + 6 dependent (8 total) RCIS Blockchain Certificate: #1823-376-572

The Cascade MoE architecture is protected by a pending patent. The patent covers all 8 architectural innovations listed above.

OS-Aware Execution

Genesis 2 detects the host operating system and adapts:

• macOS: Strips sudo, warns about Linux-only commands, uses macOS equivalents
• Linux: Full command execution with sudo support
• Windows: Suggests PowerShell alternatives
• Safety: Blocks dangerous commands (rm -rf, mkfs, dd, shutdown)

Editions

Edition	Price	License	Includes
Academic	$299	1 person, research only	Source + model + docs
Professional	$1,499	5 users, commercial	+ 30 datasets + 12mo updates
Enterprise	$4,999	Unlimited, commercial	+ patent docs + book + lifetime updates
Source + Patent Bundle	$5,000	White-label rights	+ patent license + 5h consultation

Project Structure

genesis2-cascade-moe/
├── genesis2_core.py          # Core: neurons, cascade, shared pool, training
├── genesis2_gen.py           # Generation: concept chains, composer, boost
├── genesis2_agent.py         # Agent: learn/reason/plan/chat/self-learn
├── genesis2_web.py           # Web UI + REST API + OS detection
├── genesis2_repl.py          # Interactive terminal REPL
├── embedding/
│   └── train_embedding.py    # Custom hash embedding training
├── datasets/                 # 30 training datasets (Professional+)
├── PATENT/                   # Patent materials (Enterprise+)
└── requirements.txt

Author

Larionov Alexander Viktorovich (Ларионов Александр Викторович)

• SCADA/ICS Engineer with 10+ years of industrial automation experience
• AI Researcher specializing in novel neural architectures
• Patent holder (Cascade MoE, FIPS Russia 2026)

Contact: avlarionov@hotmail.com GitHub: larionovavi-stack Products: avlarion.gumroad.com

Also by Author

• atwSCADA — Free SCADA system in a single HTML file (IEC 61850, OPC UA, Modbus TCP)
• Network Automation with AI — 132-page practical guide ($29)

Affiliate Program

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License

This repository contains the documentation, architecture description, and demo materials. The full source code and trained model are available through Gumroad.

Patent pending. All rights reserved. (c) 2026 Larionov Alexander Viktorovich.

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No GPU. No Cloud. No Limits.
Get Genesis 2 Academic — \$299