Luck3333

Mark the date. On April 1st, 2026, Qubic flips the switch on Dogecoin mining, and the entire mining architecture of the network changes with it.
How Qubic Mining Worked Before Dogecoin
If you've been following Qubic, you know the network has always been about making computation useful. This transition takes that philosophy from promising to proven. Here's the full picture.
How Qubic Mining Worked Before Dogecoin
Under the previous model, Qubic miners split their time between two tasks. Roughly 50% of compute time went toward mining Monero (XMR). The other 50% went toward training Aigarth, Qubic's own AI. CPUs toggled back and forth, and while the system worked, neither task got the full attention of the hardware running it.
What Changes With Dogecoin Mining on Qubic
Dogecoin uses the Scrypt hashing algorithm, which runs on ASIC hardware: dedicated machines built for that specific type of work. Qubic's AI training runs on CPUs and GPUs. Different hardware. Different jobs. No overlap.
That single architectural fact changes everything. Instead of splitting time, the network runs both workstreams in parallel:
ASICs mine Dogecoin, 100% of the timeCPUs/GPUs train Aigarth, 100% of the time
No more alternating. No more compromises. The old interleave model is retired for good. And older Scrypt ASICs that have been sitting in closets, machines like the Antminer L3+ that can't turn a profit on standard Doge pools, suddenly have a reason to exist again. The ASIC layer is purely additive: new revenue for the network without touching existing CPU/GPU miner rewards.
Why Qubic's Shift to Dogecoin Mining Matters
It would be easy to frame this as "Qubic now mines a different coin." The significance runs deeper.
Full resource utilization. Under the old model, AI training only had access to half the network's compute cycles. Now it gets 100%. That's a straight doubling of throughput dedicated to Aigarth.
Hardware specialization. ASICs do what ASICs are built for. CPUs and GPUs do what they're built for. The network stops forcing general-purpose hardware into a hashing role it was never optimized for.
A new revenue stream without cannibalization. Dogecoin mining introduces external value into the Qubic economy. New money flows in and feeds directly into the buyback mechanism (more on that below).
Horizontal scalability proven. If Qubic can absorb ASIC miners running Scrypt alongside CPUs running AI workloads, the door opens for future hardware categories to plug in the same way. Dogecoin marks the beginning of a new era for Qubic's mining architecture, the first proof that multiple hardware categories can plug into the network and run in parallel.
Oracle Machines get their first real-world stress test. Every Dogecoin share submitted to the network gets validated through Qubic's decentralized Oracle Machines, not by a single pool operator. That creates real on-chain transaction volume and proves that Oracle infrastructure works under production load.
Qubic Dogecoin Mining: The 3-Phase Transition Plan
The core team is not flipping a switch overnight. The move from XMR to DOGE follows a three-phase rollout designed to protect network stability. Each phase lasts roughly 1 to 2 epochs, giving computors and miners time to adjust.

Phase 1: Testing (1 to 2 Epochs)
The network keeps running XMR mining as-is while Dogecoin enters a live testing phase on mainnet.

What this means for you: Nothing changes on the revenue side. Computors earn from XMR exactly as before. Dogecoin runs in the background, proving the full pipeline works (dispatcher, pool connections, oracle validation) without affecting earnings. This is the safety net phase.
Phase 2: Migration (1 to 2 Epochs)
Computors get to choose: stick with XMR or opt into Dogecoin mining. Both options coexist, but XMR begins its phaseout.

What this means for you: The decision point. Computors who opt into Doge start receiving rewards through the new system. XMR miners can still earn, but incentives shift: top-ups move to the Doge side. The migration is voluntary, but the economics clearly favor moving over.
Phase 3: Final State
XMR mining is fully removed. The dispatcher is turned off. Dogecoin and AI training run the network.

What this means for you: The target architecture. ASICs mine Doge around the clock. CPUs and GPUs train Aigarth around the clock. The network reaches its most efficient configuration to date.
How the Qubic Dogecoin Buyback Mechanism Works
All that mined Dogecoin needs to go somewhere useful. Here's how:
ASIC miners produce DOGE through the networkThe DOGE gets sold on the marketProceeds are used to buy back QUQU is distributed to computors based on their participation
There's also an optional layer the community is shaping: computors can vote to allocate a percentage of QU emissions directly to Doge miners. The Doge buyback can top up rewards to approximately 110% of the base rate. Any remaining buyback that isn't distributed gets burned.
The result is a self-reinforcing loop. Dogecoin mining generates external revenue, that revenue flows back into QU demand, and the burn component keeps long-term supply pressure in check. For more on Qubic's tokenomics, see the halving page.
Qubic Dogecoin Mining: Current Development Progress
The team isn't theorizing. They're proving it works in the real world.
Doge Connect is the protocol bridging ASIC miners to the Qubic network. The draft protocol is ready, the repo is live on GitHub, and a test miner is available. The first successful test share already passed through the full pipeline. For a deep dive into the technical architecture, read the full Dogecoin mining explainer.
Computor documentation with technical specs for pool participation is available in the Doge Connect repository.
Workflow testing is running through the complete chain. Computors and pools are already testing in preparation for launch. Full details were covered in the March 5 All-Hands Recap.
What to Expect When Qubic Dogecoin Mining Goes Live
Computors and pools are already testing behind the scenes. April 1st is when the stats start showing up on mainnet.
If you were around for the early days of XMR mining on Qubic, you've seen this movie before. The network ramps gradually. Miners connect, configurations get dialed in, hashrate climbs day by day. Slow and steady wins the race.

The architecture is proven. The testing is done. Give it room to breathe and the growth curve will speak for itself.
How to Start ASIC Mining Dogecoin on Qubic
If you've got Scrypt ASIC hardware (or you're thinking about picking some up), here's how to get started:
Get the hardware. You need a Scrypt-compatible ASIC miner. Popular options: the Bitmain Antminer L7 (widely available secondhand), the Antminer L9 (current gen, best efficiency), and the Goldshell Mini-DOGE Pro (compact, good for home setups). Older machines like the L3+ work too. Check CoinWarz for current Scrypt miner profitability.
Set up your miner. Connect via Ethernet (most ASICs don't support Wi-Fi), access the web interface, update firmware, and configure pool settings. The official Dogecoin mining guide covers the basics.
Connect to Qubic. Follow the computor documentation in the Doge Connect repo to configure your miner for the Qubic network. Details on pool structure and connection specifics will be confirmed closer to launch.
Join the conversation. Head to the #dogecoin channel on Discord to coordinate with other miners and the core team.
Whether you're dusting off an old L3+ or buying your first ASIC, the network has room for you.
Before April 1st: Join the Live Preview on March 30th
Two days before DOGE mining goes live, the people who built it are pulling back the curtain.
Join Joetom (Core Tech Lead) and Raika (DOGE Lead Dev) for a live walkthrough of the full technical architecture, the three transition phases, and what launch day actually looks like in real time. Hosted by Stephanie (DefiMomma), Head of Marketing & Growth.
No script. No spin. Just the engineers answering your questions on the eve of one of the most anticipated launches in Qubic's history.
Monday, March 30, 2026 at 11:00 AM EDT / 3:00 PM UTC Live on X · YouTube · Linkedin
RSVP here to get a reminder
What's Next for the Qubic Network
This transition was designed in the open, built with community input, and governed by computor vote. The roadmap is clear, the code is tested, and April 1st is coming fast.
Qubic started with a simple idea: computation should be useful. Dogecoin mining is the next chapter, where the network stops choosing between AI and mining and starts doing both, fully, at the same time.
April 1st. Not a joke. But first, March 30th.
See you on mainnet.
Stay connected: GitHub
#Qubic #Dogecoin‬⁩ #AI #AGI #UPoW

The diagram above reveals how Qubic integrates Dogecoin mining into its Useful Proof-of-Work (uPoW) ecosystem — turning mining infrastructure into a coordinated distributed computing system.
Here’s the simplified flow:
1️⃣ Miners → Pool Server
ASIC miners connect through the Stratum protocol to a Qubic Pool Server.
The pool distributes tasks and sets the difficulty for mining shares.
2️⃣ Pool Server → Dispatcher
The Pool Server communicates with a Dispatcher, a custom bridge between the Qubic network and external Dogecoin mining pools.
3️⃣ Dispatcher → DOGE Pool
The Dispatcher forwards mining tasks to a Dogecoin pool server and returns valid shares from miners.
4️⃣ Decentralized Validation via Qubic Network
Instead of trusting a single mining pool operator, Qubic validates shares through its decentralized Oracle Machines. Multiple oracle nodes check whether the Doge share is valid before confirming it on-chain. (qubic.org)
Up to 13 oracle commits can be included in a single transaction, ensuring high-throughput validation while keeping the system decentralized. (qubic.org)
Why This Is Different From Traditional Mining
Most mining pools rely on centralized share validation.
Qubic introduces something new:
🔹 Decentralized validation through Oracle Machines
🔹 Parallel computation architecture
🔹 AI training + crypto mining running simultaneously
Because Dogecoin mining uses ASIC hardware, while Qubic’s AI training (Aigarth) runs on CPUs and GPUs, both workloads can operate in parallel without competing for resources. (qubic.org)
This means:
ASIC hardware mines $DOGECPU/GPU resources continue training decentralized AIThe network produces both economic value and useful computation
April 1, 2026 — A Major Milestone
Testing started in March and the mainnet launch target is April 1, 2026. (qubic.org)

If successful, this will be one of the first real demonstrations of a blockchain coordinating multiple types of compute workloads at once — AI training, oracle validation, and external PoW mining.
For Qubic, Dogecoin mining is not just about hashrate.
It’s a proof that Useful Proof-of-Work can scale beyond traditional mining into a multi-purpose decentralized compute infrastructure.
📖 Full technical breakdown:
https://qubic.org/blog-detail/qubic-dogecoin-mining-how-it-works
💥On Binance: Dogecoin Mining on Qubic: How It Works and Why It Matters
#Qubic #DOGE #Aİ #DePIN #CryptoMining

In crypto, some people follow trends.
Others… create them.
Come-from-Beyond (CFB) — also known as Sergey Ivancheglo — belongs to the latter.
🚀 A Journey of Quiet Innovation
2013 — NXT
One of the first blockchains to implement a full Proof of Stake system.2015 — IOTA
Introduced the DAG (Tangle) architecture — an alternative to traditional blockchains.2019 → Present — Qubic
A decentralized compute network combining AI, oracle systems, and Useful Proof of Work.
🧩 A Pattern Across Everything He Builds
Look closely, and a pattern emerges:
PoS → energy efficiencyDAG → scalabilityQubic → useful computation
👉 One consistent vision:
Maximize the value of computation.
🧠 A Controversial Builder
CFB isn’t your typical polished founder:
Left IOTA after major internal conflictsOften holds unconventional, polarizing viewsPrefers building over marketing
And yet…
👉 People like this tend to create breakthroughs.
🕵️‍♂️ Could CFB Be Satoshi?
There’s a theory in parts of the community:
👉 CFB might be Satoshi Nakamoto
There’s no proof.
But the speculation exists because:
Deep early understanding of cryptographyActive since crypto’s earliest daysMaintains a low-profile, elusive presence
Whether true or not, one thing stands out:
👉 His mindset feels very “Satoshi-like” — build systems, not personal brands.
🔥 Qubic — His Biggest Vision Yet
Qubic isn’t just a blockchain.
It’s:
An AI training networkA decentralized oracle layerA compute marketplaceA new form of Proof of Work
👉 A step toward:
Decentralized Artificial General Intelligence
⏳ The Next Step Is Happening Now
📅 April 1st
Qubic begins Dogecoin mining
Less than 4 days away.
This isn’t just mining.
👉 It’s a shift:
from experimental techto a real revenue-generating engine
🎯 Final Perspective
CFB has already:
Built PoS before it was mainstreamIntroduced DAG before the market understood it
And now…
He’s attempting something even bigger:
👉 Turning global compute power into an economy.
🔥 Conclusion
If Qubic succeeds:
👉 This won’t just be another crypto project
👉 It could mark the birth of an entirely new model:
The Compute Economy. 🚀

#Qubic

#CFB

#CryptoInnovation

#DecentralizedAI

#ComputeEconomy

Written by Qubic Scientific Team

How Information Flows in Traditional Artificial Neural Networks
In the artificial intelligence models we know, information enters, is encoded, is transformed through algebraic matrices, and produces outputs. Even in the most advanced architectures such as transformers, the principle is the same: the signal passes through a series of well-defined operations within a structured system. The model functions as a directed processing circuit, from left to right, input-output, or from right to left, through backpropagation for adjustments and training.
The results, as we well know, are spectacular. By working over millions of language parameters, AI is capable of giving magnificent answers, along with some hallucinations, however. But if the goal is not to process inputs and produce outputs, but to build systems capable of maintaining an internal dynamics, adapting continuously, reorganizing themselves, regulating their learning, and sustaining intelligence as a property of the tissue, current AI falls short.
Although people sometimes speak of language models as imitations of the brain, in reality this is more of a comparative metaphor than a simulation of computational neuroscience. Biological systems do not handle information from left to right and vice versa. Information propagates through a network, feeds back on itself, and also oscillates, is dampened, or is reinforced depending on the context.

Fig 1. Left-right information flow in traditional artificial neural networks
Not Only Neurons: The Role of Astrocytes in Brain Function and Synaptic Plasticity
We usually associate cognition and intelligence with the functioning of neurons, their receptors, and neurotransmitters. But they are not the only cells in the nervous system. For a long time, astrocytes were considered nervous system cells devoted to support, cleaning, nutrition, and stability of the environment. Today we know that they actively participate in regulation; in fact, a term is used: tripartite synapse, in which they actively participate by detecting neurotransmitters, integrating signals from multiple synapses, modulating plasticity, and modifying the functional efficacy of the circuit.
A living network is not composed only of neurons that fire, but also of astrocytes that regulate how, when, and how much the system changes. In biology, computing is not only about emitting a signal but also about modulating the terrain where that signal will have an effect. Recent research has demonstrated that astrocytes can perform normalization operations analogous to self-attention mechanisms found in transformer architectures — linking astrocyte–neuron interactions directly to attention-like computation in artificial intelligence systems.

Fig. 2 Biological astrocytes and tripartite synapse 
Astrocytic Gating in Neuraxon: Bio-Inspired Neural Network Architecture
Neuraxon is an architecture that tries to recover and emulate the functioning of the brain and to compute functional properties that classical artificial networks have oversimplified.
As we have explained in previous volumes of this academy, Neuraxon does not work only with input, output, and hidden neurons in the conventional sense. It introduces units with states that emulate excitatory, inhibitory, or neutral potentials (-1, 0, +1). In addition, it does so within a continuous TEMPORAL dynamics where we take into account context and the recent history of activation. The network is no longer a sum of layers but resembles more a system with internal physiology. For deeper context on how these foundational elements work, see NIA Volume 1: Why Intelligence Is Not Computed in Steps, but in Time and NIA Volume 2: Ternary Dynamics as a Model of Living Intelligence.
We have explained how Neuraxon models transmission through fast, slow, and neuromodulatory receptors — a mechanism explored in depth in NIA Volume 3: Neuromodulation and Brain-Inspired AI. But now we also model the regulation of plasticity through astrocytic gating.
How Astrocyte-Gated Multi-Timescale Plasticity (AGMP) Works
Astrocytic gating introduces a gate inspired by the role of astrocytes in the tripartite synapse. The idea is to introduce a local, slow, and contextual filter that determines when a synaptic modification should be opened, dampened, or blocked. It is as if the system can consider whether there is permission for a change. This approach directly addresses the stability-plasticity dilemma, one of the most fundamental challenges in continual learning for neural networks.
Eligibility Traces and Local Synaptic Memory
How does it work? Through a kind of eligibility trace. It is a local memory that says, "something relevant has happened at this synapse." It is updated with a decay over time and with a function between presynaptic and postsynaptic activity. That is: the synapse accumulates local evidence of temporal coincidence or causality. From there, there is a global broadcast-type signal, such as an error, a possible reward, or something dopamine-like. The astrocytic gate selects whether the neuron is in a learning state. In future versions, astrocytes could modulate thousands of synapses if this provides a computational advantage.
This approach is consistent with recent advances in neuromorphic computing, including the Astrocyte-Gated Multi-Timescale Plasticity (AGMP) framework proposed for spiking neural networks, which similarly augments eligibility-trace learning with a slow astrocyte state that gates synaptic updates — yielding a four-factor learning rule (eligibility × modulatory signal × astrocytic gate × stabilization).
Endogenous Regulation: Why Neuraxon Is More Than a Conventional Neural Network
Neuraxon within QUBIC does not compete in scale or task performance. It works through an architecture with endogenous regulation. By incorporating astrocytic principles, it begins to behave like a network with internal ecology. That is: a system where it matters not only which units are activated, but which domains of the tissue are plastic, which are stabilized, which areas are damping noise, which are consolidating regularities, and which are preparing to reorganize themselves. For a comprehensive overview of how biological and artificial neural networks compare, see NIA Volume 4: Neural Networks in AI and Neuroscience.
For Aigarth and QUBIC, the goal is not to accumulate more parameters, but to introduce more levels of functional organization within the system.
Why Astrocytic Gating Matters for Aigarth and Decentralized AI
Aigarth is not a static model but an evolutionary tissue through an architecture capable of growing, mutating, pruning, generating functional offspring, and reorganizing its topology under adaptive pressures. In that context, Neuraxon contributes something: a rich computational microphysiology for the units that inhabit that tissue.
This has implications for robustness, adaptability, and memory. Also for scalability. In large architectures, the problem is not only that there are many units, but how to coordinate which parts of the system are available for reconfiguration and which must maintain stability.
In roadmap terms for QUBIC, the goal is to build systems where intelligence emerges not only from neuronal computation, but also from the coupling between fast processing, slow modulation, and structural evolution. You can explore these dynamics firsthand with the interactive Neuraxon 3D simulation on HuggingFace Spaces, where you can build, configure, and simulate a Neuraxon 2.0 network from scratch.
Fig 3. Neuraxon astrocytes gating - AGMP formulation
Scientific References
Allen, N. J., & Eroglu, C. (2017). Cell biology of astrocyte-synapse interactions. Neuron, 96(3), 697–708.Halassa, M. M., Fellin, T., & Haydon, P. G. (2007). The tripartite synapse: Roles for gliotransmission in health and disease. Trends in Molecular Medicine, 13(2), 54–63.Kofuji, P., & Araque, A. (2021). Astrocytes and behavior. Annual Review of Neuroscience, 44, 49–67.=Perea, G., Navarrete, M., & Araque, A. (2009). Tripartite synapses: Astrocytes process and control synaptic information. Trends in Neurosciences, 32(8), 421–431.Woodburn, R. L., Bollinger, J. A., & Wohleb, E. S. (2021). Synaptic and behavioral effects of astrocyte activation. Frontiers in Cellular Neuroscience, 15, 645267.=Vivancos, D. & Sanchez, J. (2026). Neuraxon v2.0: A New Neural Growth & Computation Blueprint. ResearchGate Preprint.
Explore the Full Neuraxon Intelligence Academy
This is Volume 5 of the Neuraxon Intelligence Academy by the Qubic Scientific Team. If you are just joining us, explore the complete series to build a full understanding of the science behind Neuraxon and Qubic's approach to brain-inspired, decentralized artificial intelligence:
NIA Volume 1: Why Intelligence Is Not Computed in Steps, but in Time — Explores why biological intelligence operates in continuous time rather than discrete computational steps like traditional LLMs.NIA Volume 2: Ternary Dynamics as a Model of Living Intelligence — Explains ternary dynamics and why three-state logic (excitatory, neutral, inhibitory) matters for modeling living systems.NIA Volume 3: Neuromodulation and Brain-Inspired AI — Covers neuromodulation and how the brain's chemical signaling (dopamine, serotonin, acetylcholine, norepinephrine) inspires Neuraxon's architecture.NIA Volume 4: Neural Networks in AI and Neuroscience — A deep comparison of biological neural networks, artificial neural networks, and Neuraxon's third-path approach.
Qubic is a decentralized, open-source network for experimental technology. To learn more, visit qubic.org
#Qubic #AGI #Neuraxon #academy #decentralized

In many blockchain ecosystems, running infrastructure is usually limited to validators with powerful hardware. But with Qubic, the architecture is being designed differently.

That’s where Qubic Guardians comes in.
Guardians is a community-driven program that encourages users to run nodes that help support the Qubic network, improving decentralization, data accessibility, and overall stability.
And the most interesting part?
You don’t need an ultra-powerful server with terabytes of RAM like Computor nodes to participate.
Guardians significantly lowers the infrastructure barrier, allowing more community members to help operate the network.
Two Types of Nodes in the Guardians System
Participants can run two main types of nodes.
1️⃣ Bob Node
Bob Nodes function as indexers for the Qubic network.
Their role is to process and provide blockchain data through APIs, enabling:
wallets to check balancesapplications to read transactionsWeb3 services to integrate blockchain data
In simple terms, Bob Nodes make it easier and faster for applications to read blockchain data.
2️⃣ Core Lite Node
Core Lite Nodes act as a lighter version of a full Qubic node.
They can:
receive network datavalidate ticks and transactionshelp distribute network information
Although they don’t participate in consensus like Computor nodes, they still play an important role in strengthening the network infrastructure.
How the Guardians System Works
The process is straightforward:
1️⃣ Users deploy a node
2️⃣ The network detects the node automatically
3️⃣ Performance and uptime are monitored
4️⃣ Nodes receive reliability scores
5️⃣ Rewards are distributed periodically
In short:
The more stable your node is, the more it contributes — and the more rewards it can earn.
Why Guardians Is Important
In many blockchain systems, community nodes often receive little incentive.
Qubic approaches this differently by turning node operators into a real infrastructure layer of the network.
Guardians help:
expand global network infrastructureimprove data access for dAppsreduce reliance on centralized serversincrease network resilience
You can think of Guardians as the immune system of the Qubic network.
The more nodes operating across the world, the stronger the network becomes.
Looking Ahead
Qubic is not just another blockchain.
The long-term vision is to build a decentralized computational infrastructure capable of supporting AI and advanced workloads.
That means the network needs:
fast data accesshighly reliable infrastructurescalable global participation
Guardians represent the community-powered layer that helps make this possible.
One thing is becoming increasingly clear:
The real strength of blockchain does not only come from technology.
It comes from the community that runs it.
And with Qubic Guardians, the community is becoming part of the network itself.
https://guardians.qubic.org/
#Qubic #aicrypto #Decentralization #AI #blockchain 🚀

Written by The Qubic Team

Blockchains are powerful systems for verifiable computation, but they have a fundamental limitation. They can only work with data that already exists on-chain. If a smart contract needs to know the current price of Bitcoin, the outcome of a sports match, or the weather in Tokyo, it has no way to find out on its own.
Oracle Machines solve this problem. Qubic is introducing its native oracle infrastructure, giving smart contracts direct access to real-world information.
An Oracle Machine serves as middleware between Qubic Core Nodes and external data sources. It handles requests leaving the blockchain and delivers verified data back in a form the network can trust.
Think of it as a three-layer system:
Qubic Core Nodes - where smart contracts live and executeOracle Machine Node - the middleware layer that handles routing, caching, and validationExternal Oracle Services - price feeds, weather APIs, event data providers
When a smart contract needs external data, it sends a query to the Oracle Machine. The Oracle Machine checks its cache, forwards the request to the appropriate external service if needed, and returns the result to the blockchain in a standardized format.
This architecture keeps external complexity isolated from the core protocol, while enabling smart contracts to access real-world information reliably.

Technical Architecture
The Oracle Machine system uses a modular design with clear separation of concerns:

Core Modules:

How Data Flows Through the System
The request lifecycle follows a clear sequence:
Qubic Core Node sends OracleMachineQuery
      ↓
NodeConnection receives and validates
      ↓
RequestHandler checks cache
      ↓
InterfaceClient forwards to oracle service
      ↓
Oracle service fetches data (e.g., from CoinGecko API)
      ↓
Response cached and returned to Qubic Core node as OracleMachineReply
      ↓
Qubic Core nodes generate one OracleReplyCommitTransaction per Computor
      ↓
Quorum verifies the oracle reply based on commits of the Computors
      ↓
Verified oracle reply is revealed on the chain by a OracleReplyRevealTransaction
   
The caching layer is particularly important. Frequently requested data (like popular trading pair prices) can be served instantly from cache, reducing latency and external API load. The TTL-based system ensures data stays fresh while optimizing performance.
Oracle Interface Types
Oracle Machines support different interface types, each with its own query and reply structure. The system will launch with The Price and the Mock interface. More oracle interfaces will be added soon.
Price Interface (Index 0)
The Price interface fetches currency pair data from providers like CoinGecko.
Query Structure (Example):
Oracle: Provider identifier (e.g., CoinGecko)
Timestamp: Query timestamp
Currency1: Base currency (e.g., BTC)
Currency2: Quote currency (e.g., USD)
Note: This is an example. It may need to be revised and a precision requirement will likely be added.
Reply Structure (Example):
Numerator  Price numerator (sint64)
Denominator: Price denominator (sint64)
The numerator/denominator format preserves precision for financial calculations without floating-point errors.
Mock Interface (Index 1)
Useful for automated and manual testing.
Two Ways to Request Data
Smart contracts and users can interact with Oracle Machines in two distinct modes:
One-Time Query
You submit a request, the Oracle Machine fetches the data, and you receive your answer. This works well for situations where you need a specific piece of information, at a specific moment.
Example use case: A prediction market contract needs to know who won last night's basketball game to settle bets.
Subscription
A smart contract can subscribe to receive ongoing updates from an oracle. Instead of asking for the current price every time, the contract receives automatic updates at regular intervals.
Example use case: A DeFi protocol needs continuous price feeds to calculate collateral ratios and trigger liquidations.
Request Tracking
Every oracle request gets a unique tracking ID for correlation between queries and replies. Query status can be:

Timeouts ensure the system keeps moving. If an oracle fails to respond within the defined window, the request is marked as failed, rather than waiting indefinitely.
Fees and Economics

This structure aligns with Qubic's tokenomics - where fees are burned rather than redistributed, creating deflationary pressure while incentivizing efficient operation.
What This Enables
Oracle Machines open up categories of applications that were previously impossible to build on Qubic. Combined with Qubic's feeless transactions and high-speed execution, developers can now create:
Prediction Markets: Automatic resolution based on verified real-world outcomes. Sports results, election outcomes, and event occurrences can now settle contracts without manual intervention.
DeFi Protocols: Reliable price feeds enable lending protocols, synthetic assets, and automated market makers. Liquidations can trigger based on accurate, timely price data from providers such as CoinGecko.
Insurance Applications: Parametric insurance contracts can pay out automatically when verified conditions are met such as weather events, flight delays, or other measurable occurrences.
Gaming and NFTs: Real-world data can influence in-game mechanics. Sports NFTs could update based on actual player performance.
For more potential applications, see Qubic Use Cases.
Building New Oracle Services
The Oracle Machine system is designed for extensibility. Third-party developers can add new oracle services by implementing the BaseOracleService interface.
To create a new oracle service:
Define interface structures in Qubic Core (query/reply formats)Create service implementation inheriting from BaseOracleServiceImplement data providers for external APIsAdd configuration entriesRegister in the build system
The oracle-machine repository includes reference implementations and detailed documentation for building custom oracle services.
This modular architecture means the range of available data sources will expand as the ecosystem grows - without requiring changes to the core protocol.
How Oracle Machines Fit Into Qubic's Vision
Oracle Machines represent another step toward Qubic's goal of building truly intelligent smart contracts. Combined with Useful Proof of Work (uPoW) and Aigarth - Qubic's decentralized AI initiative, oracles give smart contracts the ability to observe and respond to the real world.
As described in Qubic's About page:
"Oracle Machines will be used to make Qubic Smart Contracts even smarter by resolving events through trustworthy data such as stock prices, sports scores, or sensor readings and much more. Also Oracles will give Aigarth the ability to observe the outer world."
This positions Qubic uniquely among Layer 1 blockchains; not just as a transaction settlement layer, but as infrastructure for AI-powered applications that interact with external reality.
Performance Specifications

The InterfaceClient maintains persistent connections to oracle services with automatic reconnection on failure, ensuring reliability even when external services experience brief outages.
*The values are for reference only and predicted under the testing environment. Actual Values may differ when Oracles are live. 
Getting Started for Developers
Developers interested in building with Oracle Machines can explore:
Qubic Documentation  -  Comprehensive technical guidesOracle Machine Repository  -  Source code and implementation detailsSmart Contracts Guide  -  How Qubic smart contracts workDeveloper Introduction  -  Getting started with Qubic developmentQubic Dev Kit  -  Set up your local testnetQubic CLI  -  Command-line tools for interacting with the networkGitHub Organization  -  All open-source repositories
For support, join the Qubic Discord community where developers actively collaborate.
Looking Ahead
Oracle infrastructure is foundational technology. Most users will never interact with Oracle Machines directly. Instead, they will use applications that rely on oracles behind the scenes.
Oracle Machines are currently in final testing on Qubic mainnet. Once testing is complete, the infrastructure will be ready for developers and applications to integrate.
Stay updated on Qubic developments through:
Qubic Blog  -  Latest news and technical updatesTwitter/X  -  Real-time announcementsTelegram & Discord  -  Community discussions
Oracle Machines are coming soon. Get ready to build something that matters.
#Qubic #Oracle #UPoW #AI #DeAI

Written by Qubic Scientific Team

A commentary on Nick Bostrom’s latest paper by Qubic Scientific Team
Reframing the Superintelligence Debate: Surgery, Not Roulette
He has just published a new working paper, Optimal Timing for Superintelligence: Mundane Considerations for Existing People (2026), in which he shifts the central question. Rather than asking whether we should develop superintelligence, Bostrom focuses on when it is optimal to do so. For anyone following the rapidly evolving intersection of AI and blockchain, his framework carries profound implications for how we design the infrastructure that will underpin artificial general intelligence (AGI).
Reframing the Superintelligence Debate: Surgery, Not Roulette
The starting point of Bostrom’s paper is both elegant and disruptive. He reframes the polarized “AI yes vs. AI no” debate entirely. Developing superintelligence, he argues, is not like playing Russian roulette. It is more like undergoing a risky surgery for a condition that is already fatal.
What is that condition? The current state of humanity itself. Consider the baseline: approximately 170,000 deaths occur each day from aging, disease, and systemic failures. An aging global population faces irreversible biological deterioration. Incurable diseases, including oncological, neurodegenerative, and cardiovascular conditions, continue to burden millions. We confront unmitigated global risks, from climate instability, to systemic institutional corruption, to the erosion of democratic quality. Pandemics, wars, and the collapse of entire systems remain ever-present threats.
Given these realities, Bostrom argues that framing the choice as “zero risk without AI” versus “extreme risk with a superintelligence” is simplistic. The more rigorous question is: Which trajectory generates greater expected life expectancy and greater quality of life for people who already exist?
By anchoring his analysis in the real, present conditions of human life, Bostrom sidesteps philosophical abstractions and theological speculation. He is talking about you, your family, and the people alive right now.
Life Expectancy, Mortality Risk, and the Case for Artificial General Intelligence
When we are young, the annual risk of dying is extremely low. Biologically, we are far from death in most cases. But as we age, the probability of dying climbs relentlessly due to biological deterioration.
If superintelligence could radically reduce or even eliminate aging, as Bostrom proposes, your annual mortality risk would stay at the level of a healthy young person. Your mortality would stop increasing over time. In that scenario, life expectancy becomes extraordinarily long.
From this vantage point, the expected value of superintelligence compensates for its high risks. But what happens if we delay until the technology becomes perfectly “safe”? What if we accumulate the probability of dying with each passing year? The question becomes: is it more rational to accept the probability of catastrophe from early deployment, given that AI safety progress is exponential, or to accept the certainty of accumulated deaths from delay?
Temporal Discounting and the Cost of Waiting
Bostrom introduces the concept of temporal discounting (ρ), a well-studied principle in decision theory. Humans systematically value present outcomes more than future ones. This is why we stay in unsatisfying jobs, relationships, and patterns: the effort of change feels large, and the reward feels distant.
But here an interesting inversion occurs. If life after AGI is not merely longer but dramatically better, with radical improvements in health, cognitive capacity, and quality of life, then temporal discounting actually punishes waiting. Every year of delay is a year spent in a qualitatively worse condition when a far superior state is accessible.
Quality of Life and Risk Aversion in AGI Deployment
Bostrom’s model does not assume longevity alone. It incorporates substantial improvements in well-being. If quality of life doubles after the transition to superintelligence, the balance shifts decisively toward earlier deployment. He then layers in risk aversion metrics (CRRA and CARA), acknowledging that if we are more sensitive to extreme losses, the window where “launch now” remains advisable narrows and optimal delays lengthen.
This is not reckless accelerationism. It is calibrated decision-making under uncertainty, the kind of analysis that should inform how we govern the path to artificial general intelligence.
Two-Phase Deployment: Swift to Harbor, Slow to Berth
One of the paper’s strongest contributions is its division of the AGI transition into two distinct phases:
Phase 1: Reaching AGI capability. Move as quickly as is responsible toward building a system that demonstrates general intelligence.
Phase 2: A strategic pause before full deployment. Once the system exists, introduce a controlled delay to study it, test it under real conditions, and solve technical safety problems that were previously only theoretical.
Bostrom’s hypothesis is that once an AGI system actually exists, a “safety windfall” occurs. Researchers can observe real behavior rather than speculate about it. Safety progress accelerates dramatically because the problems become empirical rather than abstract. The motto he coins: swift to harbor, slow to berth.

Who Benefits Most from an Earlier Transition to Superintelligence?
Bostrom does not treat optimal timing as universal. Older people, the seriously ill, and those living in precarious conditions have fewer expected years remaining. For them, the potential benefit of a rapid transition to superintelligence is far greater. Younger people with decades ahead can tolerate more waiting.
If you apply a prioritarian logic, giving greater weight to those who are worse off, the optimal timeline shifts forward. Bostrom also explicitly rejects the common assumption that beyond a certain age, additional life adds no value. That judgment, he argues, is rooted in our experience of current aging and deterioration. It does not account for a scenario of genuine rejuvenation, one of the central promises of a superintelligent future.
Institutional Risks: Why AI Governance Infrastructure Matters
In the final sections of his paper, Bostrom introduces critical institutional warnings. The most reasonable scenario, he suggests, is one in which the technological leader uses its advantage for safety. But he also flags the dangers of national moratoria, international prohibitions, and the competitive dynamics that arise when multiple actors race toward AGI under geopolitical pressure.
His analysis implicitly assumes an ecosystem where computational power tends to concentrate. In such an environment, the risks compound: militarization of compute resources, compute overhang (massive reserves ready to be activated under competitive pressure), and the perverse incentives of extreme centralization. These are not abstract concerns. The current trajectory of AI development, dominated by a handful of hyperscale cloud providers and corporate laboratories, creates precisely this concentration.
Implications for Qubic: Why Decentralized AI Infrastructure Reduces Existential Risk
If we take Bostrom’s framework seriously, the foundational question shifts from “when to launch AGI” to what kind of infrastructure reduces the risks associated with that launch. This is where Qubic’s architecture becomes directly relevant to the global conversation about superintelligence safety.
The Centralization Problem in Current AI Development
If superintelligence is built on centralized infrastructures, dependent on enormous data centers, opaque training pipelines, and corporate control, the risk profile expands beyond the purely technical. It becomes geopolitical. Concentration of compute makes the kind of adaptive governance Bostrom considers essential during the critical pre-deployment phase far more difficult. It also creates exactly the type of compute overhang he warns about: massive computational reserves ready to be activated at once under competitive pressure.
How Qubic’s Distributed Compute Architecture Addresses These Risks
Qubic dilutes that structural bottleneck. Its architecture distributes computational power across a global network rather than concentrating it in a single node. Qubic does not depend on an LLM-type architecture trained opaquely in mega data centers. Instead, it leverages Useful Proof of Work (uPoW), where miners contribute real computation to the training of its AI core, Aigarth, rather than solving arbitrary hash puzzles.
This design choice has direct implications for Bostrom’s analysis. A less centralized infrastructure reduces the probability of the abrupt, competitive deployment scenarios he warns against. Distributed compute means power is not located in a single facility that can be militarily captured, nor in a corporate laboratory under unilateral control. That structural resilience expands the space for Bostrom’s Phase 2: the strategic pause where real testing, incremental improvement, and adaptive governance can occur before full deployment.
For a deeper understanding of how Qubic’s approach to AI differs from mainstream models, explore Neuraxon: Qubic’s Big Leap Toward Living, Learning AI and the recent analysis That Static AI Is a Dead End. Google Confirms.. These posts illustrate how Qubic is building intelligence through a fundamentally different paradigm: one designed for continuous learning, distributed resilience, and real-world adaptation on a decentralized network.
Decentralized AI and Blockchain: Structural Alignment with AGI Safety
From Bostrom’s perspective, Qubic’s potential does not lie simply in being “decentralized” as a branding exercise. It lies in modifying the structural variables that determine optimal timing for superintelligence deployment. By distributing compute, by building consensus protocols that align miner incentives with genuine AI training, and by making the entire process open-source and auditable, Qubic creates the kind of infrastructure that makes the transition to AGI structurally safer.
If you’re interested in how Qubic’s CPU mining model and distributed compute network are evolving, the Dogecoin Mining on Qubic deep dive explains the latest expansion of Useful Proof of Work, and Qubic’s 2026 Vision details the broader infrastructure roadmap now underway.
The Hardest Problem: Building AGI That Learns from the World
Imagining utopian and dystopian scenarios is valuable. It is, in fact, the best path to creating futures aligned with human needs and values. But looking away, waiting aimlessly, or accelerating without restraint all fail to provide the necessary reflections.
Perhaps the most difficult challenge right now is not so much weighing the risk of accelerating the transition and modeling it. For now, the hardest task is building a general artificial intelligence capable of learning by itself from different dynamic environments, creating representations of the world, and acting within it. That is precisely the challenge Qubic’s Neuraxon framework is designed to address, not by training on static datasets behind closed doors, but by evolving in the open, learning from real-world complexity on a decentralized network anyone can participate in.
References and Sources
1. Bostrom, N. (2026). Optimal Timing for Superintelligence: Mundane Considerations for Existing People. Working paper, v1.0.
https://nickbostrom.com/optimal.pdf
2. Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press.
3. Bostrom, N. (2003). Astronomical Waste: The Opportunity Cost of Delayed Technological Development. Utilitas, 15(3), 308–314.
4. Yudkowsky, E. & Soares, N. (2025). If Anyone Builds It, Everyone Dies.
5. Hall, R. E. & Jones, C. I. (2007). The Value of Life and the Rise in Health Spending. Quarterly Journal of Economics, 122(1), 39–72.
6. Qubic Scientific Team. Neuraxon: Qubic’s Big Leap Toward Living, Learning AI.
https://qubic.org/blog-detail/neuraxon-qubic-s-big-leap-toward-living-learning-ai
7. LessWrong community discussion: Optimal Timing for Superintelligence
https://www.lesswrong.com/posts/2trvf5byng7caPsyx/optimal-timing-for-superintelligence-mundane-considerations
#Qubic #AGI #UPoW #Dogecoin‬⁩ #DeAI

Written by The Qubic Team

Introduction
The Qubic network has built its reputation on speed, achieving 15.5 million transactions per second verified by CertiK. Behind this performance sits a network of high-powered machines running the protocol directly on bare metal hardware. While effective, this architecture presents a challenge: the hardware requirements have limited who can participate in supporting the network.
Qubic Network Guardians is designed to change that. By introducing lightweight node options with lower hardware requirements, the initiative removes barriers to entry and makes network participation accessible to everyone. More participants means a stronger, more decentralized network.
The Problem: High Barriers to Network Participation
Running a full Qubic node currently demands significant resources. The official requirements include bare metal servers with at least 8 high frequency CPU cores (>3.5Ghz) featuring AVX2 support (with AVX-512 recommended, will be mandatory latest 2027), 2TB RAM, and dedicated hardware setups. These specifications ensure the network maintains its exceptional throughput, but they also create practical barriers.
Fewer operators mean reduced redundancy. When nodes are concentrated among a smaller group of participants, the network becomes more vulnerable to outages and potential centralization. This is a recognized tension in blockchain design: performance requirements can work against the decentralization that makes distributed networks valuable.
The hardware requirements for Computors exist for good reason. These machines must process transactions, execute smart contracts, and reach consensus at speeds that justify Qubic's performance claims. Lowering those specifications would compromise the network's throughput. The solution isn't reducing Computor requirements. It's creating additional ways to contribute.
The Solution: Incentivizing Lightweight Nodes
Network Guardians introduces economic rewards for running bob nodes and core lite nodes. These lighter alternatives provide meaningful network benefits without requiring the extreme hardware of a full Computor setup.
What Are Bob and Core Lite Nodes?
Bob Node: A high-performance indexer for the Qubic blockchain that provides a JSON-RPC 2.0 API (similar to Ethereum's) and WebSocket subscriptions for real-time data streaming. It's designed for exchange integration and dApp development, offering features like balance queries, transaction tracking, log filtering, and smart contract queries. Bob nodes are customizable for unique applications and serve as builder-centric infrastructure
Core Lite Node: A lightweight node that connects to the Qubic core network to receive and verify blockchain data (ticks, transactions, logs) without participating in the consensus process as a computor. Unlike full computor nodes that perform heavy computation and voting, a lite node focuses on indexing and serving chain data, making it ideal for running APIs, wallets, and exchange integrations.
Both node types contribute to network health by improving data availability, increasing redundancy, and providing additional access points for network queries.

How Network Guardians Works
The program operates through a straightforward cycle of monitoring, scoring, and rewarding.
Step 1: Node Registration and Discovery
Operators configure their bob or core lite node with an operator identity and optional display name. The system automatically discovers participating nodes through network crawling and node announcements. No manual registration process is required beyond proper node configuration.
Step 2: Continuous Monitoring
Once discovered, nodes enter continuous monitoring. The system evaluates performance across multiple dimensions to ensure operators are genuinely contributing to network health rather than simply running idle software.
Step 3: Scoring System
Points accumulate based on weighted criteria that reflect actual network value:

This weighting emphasizes reliability above all. A node that stays online and synchronized provides more value than one with perfect data accuracy but sporadic availability.
Note: The scoring framework is currently under development. The values provided above are illustrative and subject to change. Finalized values will be communicated later.
Step 4: Public Leaderboard
All participating operators appear on a transparent leaderboard ranked by their cumulative score. Anyone can verify who contributes and how much. This visibility creates accountability and allows the community to recognize top performers.
Step 5: Epoch-Based Rewards
QU rewards are distributed at the end of each epoch (Qubic's weekly cycle) proportional to operator scores. Higher-ranked operators receive larger shares of the reward pool. This aligns with how Computor rewards already function in the main network, extending a familiar model to lightweight node operators.
Technical Requirements
The hardware specifications for Network Guardians participation sit well below full node requirements while still demanding capable machines.

Bob Node Requirements

Core Lite Node Requirements

For comparison, running a full Qubic node requires bare metal hardware with 8+ cores, AVX-512 support (mandatory by 2027 latest), 2TB RAM,  and dedicated server infrastructure. The lightweight alternatives reduce the entry point considerably.
Preventing Abuse
Any reward system faces gaming attempts. Network Guardians plans several countermeasures:
Relay and Proxy Detection: Mechanisms to identify nodes that appear to be running but are actually routing requests through other infrastructure rather than providing genuine service.
Identity Limitations: Restrictions on how many nodes a single operator identity can register, preventing one participant from claiming disproportionate rewards by spinning up numerous low-effort instances.
The specific implementation details for these measures will develop alongside the program as real-world patterns emerge.
Long-Term Vision: Moving On-Chain
The initial Network Guardians phase operates without a smart contract. Reward calculations happen through existing infrastructure, and distributions follow established processes.
The roadmap targets full on-chain operation through several planned developments:
Smart Contract Deployment: A dedicated contract managing the reward pool and distribution logic.Oracle Machine Integration: Network statistics delivered through Qubic's Oracle Machines, which connect smart contracts to real-world data through the Qubic Protocol Interface.Automated Distribution: Reward calculations and payments handled entirely by contract logic, removing manual processes and increasing transparency.
This transition would align Network Guardians with Qubic's broader smart contract architecture, where contracts operate through community governance and provide shareholders with passive income from fees.
Why Decentralization Matters
The 676 Computors that validate the Qubic network must reach quorum (451+ agreement) to finalize transactions. This Byzantine Fault Tolerant design ensures the network can function even if some validators fail or act maliciously.
Lightweight nodes don't participate in consensus directly, but they strengthen the network in other ways:
Data Redundancy: More nodes storing and serving network data means better availability during outages or attacks.
Geographic Distribution: Lower hardware requirements enable operators in more locations to participate, reducing reliance on data center concentrations.
Query Load Distribution: Additional nodes handling API requests and data queries reduce strain on Computors, letting them focus on consensus operations.
Attack Resistance: A larger node population makes targeted attacks more difficult and expensive to execute.
These benefits compound as participation grows. Each additional node makes the network incrementally more resilient.
Getting Started
Network Guardians is designed for simplicity. Both bob and core lite nodes will be available as Docker images, enabling near one-click deployment.
Why Docker?
Bob and core lite nodes aren't single executables. They're coordinated systems composed of multiple services (core node, Redis, kvrocks) that must run together and communicate reliably. Docker packages this entire stack into a single, reproducible unit.
Consistent environment: Every user runs the exact same versions with no configuration driftZero dependency management: No manual installation of Redis, kvrocks, or version matchingSimple operation: Start and stop the entire stack as one unit with Docker ComposeSafe upgrades: Switch image versions without affecting your host systemClean isolation: Node runs separately from your OS with explicit data persistence
To Prepare
Check Hardware: Confirm your machine meets bob node (16 GB RAM, 4 cores) or core lite (64 GB RAM, 8 cores) requirements.Install Docker: Ensure Docker and Docker Compose are installed on your Linux system with AVX2 CPU support.Follow Announcements: Monitor official Qubic channels for launch details and deployment guides.Configure Identity: Once live, set up your operator identity and optional display name through the provided configuration.
Roadmap: Building Together

The journey itself is part of the campaign. Feedback from early participants will shape the final implementation, scoring weights, and reward mechanics. This isn't a system being handed down. It's infrastructure being built together.
Join the Discussion
Have questions about Network Guardians or want to connect with other node operators? The Qubic community is active across several platforms:
Discord  -  https://discord.gg/qubicX (Twitter)  -  https://x.com/_Qubic_Learn More: - github.com/qubic/network-guardians
#AGI #UPoW #Qubic