Introducing Qubic: Decentralized Computing and AI

Qubic represents a revolutionary approach to decentralized computing and blockchain technology, developed by Sergey Ivancheglo (known as Come-From-Beyond or CFB). It combines high-speed transaction processing, feeless operations, and a unique consensus mechanism that transforms mining energy into artificial intelligence development.

General
Release Date	April 2022
Author	Sergey Ivancheglo (CFB)
Type	Layer 1 Blockchain with AI Integration
Network Speed	15.5M TPS (CertiK Verified)
Founder Background	Co-founder of IOTA and NXT

Introducing Qubic

Sergey Ivancheglo, the visionary creator of Qubic, initiated the project in 2019 as an evolution of decentralized computing concepts. Qubic represents a paradigm shift in how blockchain networks operateâ€”merging the principles of secure transaction validation with meaningful computational work that advances artificial intelligence.

At its core, Qubic introduces a groundbreaking consensus mechanism called Useful Proof-of-Work (UPoW), which redirects the computational energy typically wasted in traditional blockchain mining into productive AI model training. This approach addresses a fundamental inefficiency in cryptocurrency networks while simultaneously advancing the field of machine learning and artificial intelligence.

Key Highlights of Qubic:

Feeless Transactions: Qubic offers fast, feeless transactions with instant finality. Users can send and receive funds without paying transaction fees, making it ideal for both everyday and large-scale transfers.
Exceptional Speed: Certified by CertiK with a peak throughput of 15.5 million transactions per second (TPS), making Qubic the fastest verified blockchain network.
Instant Finality: Transactions are secure and final even offline, eliminating the need to wait for block confirmations and providing unmatched reliability.
Useful Proof-of-Work (UPoW): Instead of solving arbitrary mathematical puzzles, Qubic's mining process generates billions of artificial neural networks (ANNs) that contribute directly to AI development through the Aigarth system.
Energy Efficiency: By repurposing computational power for AI training, Qubic operates more sustainably than traditional Proof-of-Work systems while maintaining robust network security.
Quorum-Based Consensus: The network uses 676 Computors (validators) where a consensus of at least 451 nodes (two-thirds) must agree on transaction validity, ensuring security and decentralization.
Smart Contract IPO Model: Qubic features an innovative IPO mechanism where smart contracts are divided into 676 shares, distributed via Dutch auctions. Share holders earn passive income from contract fees, promoting fair revenue distribution and enabling anyone to monetize smart contract deployments.

Qubic's Consensus Architecture:

Computors: 676 dedicated validator nodes that execute smart contracts and maintain consensus.
AI Miners: Distributed network of over 100,000 GPU and CPU miners that perform AI training tasks to secure the network while advancing machine learning.
Epoch-Based Rewards: The network generates 1 trillion QUBIC tokens per epoch (7-day cycle), distributed to active Computors and contributors based on their AI training performance and network participation.

The Aigarth AI System:

Aigarth is Qubic's native AI project, a decentralized artificial intelligence system that evolves through the computational work performed by the network's miners. Key features include:

Decentralized AGI Development: Aigarth aims to achieve artificial general intelligence by 2027 through community-driven, decentralized neural network training.
Ternary Logic Processing: Qubic's AI uses ternary logic (-1, 0, +1) instead of traditional binary, enabling more efficient information processing for certain computational tasks.
Self-Modifying Networks: AI networks evolve using fitness scores and asynchronous updates, similar to digital natural selection, without centralized control.
Validated Intelligence: All AI training results are validated through Qubic's quorum consensus mechanism, ensuring accuracy and transparency.

Smart Contracts and Economic Innovation:

IPO-Based Deployment: Every smart contract launched on Qubic is divided into 676 shares, distributed through Dutch auction IPOs, democratizing contract ownership.
Passive Income: Share holders receive ongoing revenue from contract execution fees, creating a passive income opportunity for network participants.
Deflation Mechanism: Smart contract fees burn QUBIC tokens, reducing circulating supply while distributing revenue to contract shareholders.
Transparent Revenue Model: Unlike traditional platforms where developers capture all fees, Qubic's model ensures fair, decentralized revenue distribution.

Qubic's Ecosystem and Integration:

Open-Source Development: Qubic provides comprehensive developer tools, including SDKs in Java, TypeScript, Go, C#, and HTTP-based libraries.
Developer Support: The platform offers a Grants Program to foster high-quality smart contract development and a Bug Bounty Program for community security contributions.
Community Governance: Decisions are made through quorum-based voting, ensuring decentralized control and community involvement.
Wallet Integration: Multiple wallet solutions available, including official Qubic wallets supporting various platforms and use cases.

Responsibility and Decentralization:

No Single Entity Control: The decentralized nature of Qubic ensures no single entity can control or manipulate the network, fostering trust among participants.
Transparent Validation: All AI training tasks and results are recorded on the blockchain, making the system fully auditable and transparent.
Community-Driven Development: With over 630,000 community members and 100,000+ miners, Qubic is governed by its participants rather than a central organization.

Availability and Access:

Mainnet Status: Fully operational since April 2022 with continuous feature development.
Official Resources: Access documentation, tools, and support at the official Qubic platform.
Mining Participation: Join over 100,000 AI miners in the network by dedicating GPU/CPU resources to AI training while earning QUBIC rewards.
Smart Contract Development: Developers can deploy contracts, participate in IPOs, and earn passive income from smart contract fees.

The Future of Blockchain and AI

Qubic stands at the intersection of blockchain technology and artificial intelligence development, offering a solution that addresses the energy inefficiency of traditional cryptocurrencies while advancing the field of machine learning. Its unique combination of high-speed, feeless transactions, innovative smart contract economics, and decentralized AI development positions Qubic as a next-generation blockchain platform designed for the AI era.

By transforming computational energy into meaningful intelligence advancement, Qubic demonstrates how blockchain technology can serve purposes beyond financial transactionsâ€”creating a network where security, efficiency, and innovation converge.

ReviewSquad: AI code review with IBM Bob

The problem Code review is one of the slowest and least reliable steps in software delivery. Pull requests wait hours for a busy reviewer, and when the review happens, it is often rushed: the tests pass, the diff looks reasonable, approved. But passing tests do not mean safe code. Hard-coded secrets, SQL injection, inverted business logic and untested code slip into production, where fixing them costs far more. Reviews are also inconsistent: each reviewer checks different things, and the team's written guidelines are rarely applied line by line. The solution ReviewSquad turns IBM Bob into a disciplined code review team. A developer opens the pull request in IBM Bob, selects the Review Lead mode and asks it to review. ReviewSquad then runs the full workflow: 1. It converts the git diff into a review brief with exact line numbers and runs the tests and fast automated checks for hard evidence. 2. The Review Lead reads the team's own code review guidelines from a PDF (document understanding). 3. It runs four specialist reviews - Security, Bugs & Logic, Tests and Team Rules - each recording structured findings with the file, line, severity, the guideline rule broken, and a fix. 4. The findings are merged into one review with a clear verdict. 5. After a human approves, a Fixer mode repairs every finding and adds tests; tests and checks run again. 6. ReviewSquad publishes a shareable report of what was found, by whom, and the before/after state. Target users are development teams where senior reviewers are a bottleneck. Developers interact entirely through IBM Bob's chat; reviewers read one report. Why it is different Most AI review tools make a single pass and leave a list of comments. ReviewSquad runs the whole workflow - understand the rules, review, decide, fix, verify, report - with clear roles and permissions: reviewer modes are read-only, and only the Fixer may edit code, only after approval. Deterministic tools do the counting; Bob does the judgment. Because the rules come from a document, every team gets reviews against its own standards, not generic advice. We also measure instead of claiming. Our demo pull request contains 11 planted problems and passes all 8 of its tests; GitHub marks it "Ready to merge". A hidden answer key, which Bob cannot read, scores the review. Impact (our recorded run) - Automated checks alone caught 7 of 11 planted problems; ReviewSquad with IBM Bob caught 10 of 11, including an inverted coupon-expiry check that no test or linter flagged. - After the Fixer: 37 of 37 tests pass (up from 8), and automated warnings dropped from 22 to 0. - The full review, fix and verification took minutes of agent time instead of a manual review cycle, with every finding traceable to a line and a team rule.

Fresno LUX: A Living City

Fresno LUX is a prototype for a living intelligence layer across an entire city. Fresno already contains enormous amounts of intelligence: residents know where problems exist, nonprofits know where help is needed, businesses know where opportunities exist, educators understand gaps in learning, researchers generate knowledge, and government maintains critical infrastructure and data. The problem is that much of this intelligence is fragmented across disconnected systems. Fresno LUX connects those pieces. The platform creates a shared city graph where people, organizations, resources, needs, projects, observations, experiments, and outcomes become connected nodes. Instead of simply collecting data, LUX continuously asks: What is happening? What do we know? What is missing? What can we test? What changed? A community problem can become an observable signal. That signal can become an experiment. The experiment produces evidence. Evidence changes the system's understanding. That updated understanding informs the next action. Observe → Connect → Understand → Act → Measure → Learn → Converge. The goal is to move Fresno from disconnected information toward collective intelligence—a system where knowledge can travel across boundaries and successful solutions can be discovered, tested, measured, and replicated. LUX is designed to make the invisible connections visible: the relationship between a neighborhood and its resources, between a student and educational opportunity, between a business and workforce capacity, between environmental conditions and community health, and between an idea and measurable real-world impact. This hackathon prototype demonstrates the beginning of a Living Fresno Graph: a city that can observe itself, learn from evidence, and coordinate toward better outcomes.

RoboDk based Quantum state simulator

The Quantum‑Enhanced Robotics Simulator (QERS) is a fully‑functional digital testbed for designing, testing and validating robotic systems without physical hardware. Our goal is to narrow the reality gap between simulation and the real world by combining deterministic macro‑physics from engines like PyBullet with a quantum‑stochastic plugin that injects realistic noise via Qiskit. The simulator supports deterministic, stochastic and quantum‑perturbed stepping modes and exposes a FastAPI REST API for running jobs, retrieving metrics and managing assets. A Celery/Redis job system queues and executes simulation runs asynchronously, while the Next.js/Three.js web application provides a real‑time dashboard with a 3D viewport, scene tree, metrics panel and controls to toggle between classical domain randomization and quantum noise. Reality profiles define configurable dynamics, sensor and actuation parameters, enabling multi‑profile evaluation of policies. QERS computes gap metrics such as Gdyn, Gperc and Gperf and includes scripts for benchmarking across profiles and generating reports. Users can import URDFs, run batch simulations and compute performance drops and rank stability. Future phases will add mesh segmentation, an AI‑driven text‑to‑algorithm pipeline for generating planner and controller skeletons, and neural‑augmented simulation informed by real data. By combining quantum computing, domain randomization, residual learning and modern web technologies, QERS demonstrates a practical path to sim‑to‑real transfer and a production‑minded robotics startup.

microstream

MicroStream - Pay-Per-Second Micropayments on Qubic MicroStream solves the micropayment problem that has plagued blockchain for years. On Ethereum, sending $0.001 costs $5 in fees - making micropayments literally impossible. MicroStream leverages Qubic's zero-fee architecture to enable viable pay-per-second streaming payments. The system features a live counter that updates every second, showing viewers exactly how much they've paid and creators how much they've earned. Payment channels allow indefinite streaming with only two on-chain transactions: opening and closing the channel. Key features include zero transaction fees, instant 2-3 second settlement, pause/resume functionality, and automatic refunds of unused deposits. The tech stack spans a C++ smart contract with 5 core functions, Node.js backend with demo mode, vanilla JavaScript frontend with real-time counter, and 4 automation workflows for creator alerts. This enables new business models: students paying per second for lectures, gamers renting servers by actual usage time, artists earning fairly per play, and developers paying per API request. Only possible on Qubic. The combination of zero fees, instant finality, and 15.5M TPS capacity makes MicroStream the first viable micropayment system in blockchain history.