Genrikh: Building a $0-Marginal-Cost Universal AI Problem Solver with Gemma 2, Sentry & ElevenLabs

Описание и применение

Genrikh — автономный AI‑решатель, использующий алгоритм ARIZ и локальный Gemma 2, чтобы устранять компромиссы в программном обеспечении, аппаратуре и микросервисах без дополнительных затрат и с полной защитой интеллектуальной собственности.

Задача

Solo‑founders and small teams face costly trade‑offs in software, hardware, and micro‑SaaS projects, often requiring expensive infrastructure or senior consultants.

Результат

Genrikh resolves three benchmark dilemmas—offline mobile invoicing, wearable health sensor, and 10,000 RPS micro‑SaaS launch—without added cloud cost, extending battery life from 8 h to 34 days and achieving 98% edge cache hit rate.

Рабочий процесс

• 1. Input problem and parameters via CLI or API
• 2. Loop 1: internal ARIZ reasoning (steps 0‑5) with state lock
• 3. Loop 2: progressive disclosure of Layer 1, Layer 2, and Layer 3 outputs
• 4. Generate audio briefing with ElevenLabs
• 5. Deliver report and optional web dashboard

Доказательства

Genrikh is an autonomous, open‑source AI problem solver that brings classical ARIZ algorithmic rigor to modern engineering, hardware, and business systems—with $0 marginal cost and 100% intellectual property privacy.

Источник

We created an automated benchmark suite testing Genrikh across three distinct domains… Benchmark Score: 100% contradictions resolved without introducing middle‑ground trade‑offs.

Источник

Genrikh uses Google Gemma 2 running locally via Ollama (http://localhost:11434) as its primary intelligence engine… Zero bytes leave the machine (100% air‑gapped, zero IP leakage).

Источник