Michael Hoskins
Independent AI Researcher | Founder, Synoptic AI
USCF 1800 Chess Player
Top 500 Worldwide Poker
Google IT Support Certified
Over a decade studying intelligence, creativity, psychology, neuroplasticity, and cognitive science.
Building breakthrough AI architectures through novel approaches to neural architecture design.
Specializing in multi-agent systems and advanced compression techniques.
AI Research Projects
μ-ALM v2
241M parameter architecture featuring ternary attention and dynamic weight generation.
Novel approach to parameter efficiency through adaptive weight synthesis during inference.
Achieves superior performance through architectural innovation rather than brute-force scaling.
Parameters: 241M | Architecture: Ternary + Dynamic
Retro-Gemma
35% sparsity controller on Gemma 2B that maintains coherent text generation.
Successfully completed training and ready for validation testing. Demonstrates
significant efficiency gains through structured sparsity mechanisms.
Base: Gemma 2B | Sparsity: 35% | Status: Testing Phase
Cybersecurity & Enterprise Solutions
Blockchain Vulnerability Detection
Comprehensive AI-powered platform for detecting vulnerabilities in blockchain protocols
and smart contracts. Automated security analysis targeting enterprise cybersecurity market.
Target: Enterprise Security | Bug Bounty Platform
Smart Contract Security Scanner
Automated bug hunting and security analysis for Ethereum and multi-chain smart contracts.
Deep pattern recognition for exploit detection and vulnerability assessment.
Platform: Multi-chain | Automated Analysis
Multi-Agent Security Architecture
Sophisticated multi-agent system for automated penetration testing and vulnerability
discovery. Leverages AI-powered analysis for comprehensive security assessment.
Type: Automated Security Testing
Research Approach
My research focuses on architectural innovation rather than brute-force scaling. By exploring
novel approaches to neural network design, I develop AI architectures that achieve superior
performance through fundamental innovations in how neural networks process and represent information.
Drawing from over a decade of studying intelligence, creativity, and cognitive science, combined
with competitive strategic game experience (chess, poker), I approach AI research with a unique
perspective on emergence, strategic thinking, and optimal decision-making under uncertainty.