Luck3333

Kā AI apstrādā nenoteiktību (binārs pret trīskāršu)
Mākslīgā vispārējā intelekta (AGI) meklējumos tehnoloģiju nozare ir obsesīvi piegādājusi arvien vairāk datu un jaudas tradicionālajām binārajām sistēmām. Bet īstais intelekts nav tikai par to, lai būtu visas atbildes—tas ir par intelektuālu pietāti atzīt, kad nezini.
Tas ir mūsdienu AI pamata filozofiskais un arhitektoniskais trūkums. Un tieši šis trūkums Qubic, caur savu evolūcijas AI projektu #Aigarth, risina, ieviešot trešo stāvokli savā neiro arhitektūrā: "Nezināms" (0).

Tehnoloģiju pasaulē T3chFest nav vieta tukšām hype. Rīkotājs Carlos III universitātē Madridē, tas kalpo kā viens no visrigoriskākajiem tehniskajiem "litmus testiem" projektiem, ko pārbauda vairāk nekā 1,800 izcilu izstrādātāju un sistēmu arhitektu. Starp desmitiem runātāju Qubic ir izcēlies kā visvairāk gaidītais vārds—ne tikai tāpēc, ka tam ir milzīga kopienas atbalsts, bet arī tāpēc, ka tam ir arhitektūras ietvars, kas spēj pārdefinēt Blockchain un Mākslīgā intelekta krustojumu.

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

Uzrakstījusi Qubic Scientific Team

Komentārs par Nika Bostroma jaunāko rakstu no Qubic Scientific Team
Pārfotējot superinteliģences diskusiju: operācija, nevis ruletes
Viņš ir tikko publicējis jaunu darba papīru, Optimālais laiks superinteliģencei: ikdienišķas apsvērumi esošajiem cilvēkiem (2026), kurā viņš maina centrālo jautājumu. Nevis jautājot, vai mums vajadzētu attīstīt superinteliģenci, Bostrom koncentrējas uz to, kad to vislabāk darīt. Ikvienam, kurš seko strauji attīstošajai AI un blokķēdes krustojumam, viņa ietvars nes dziļas sekas tam, kā mēs projektējam infrastruktūru, kas atbalstīs mākslīgo vispārējo intelektu (AGI).

Uzrakstījusi Qubic komanda

Qubic tīkla nostiprināšana, izmantojot vieglo mezglu atlīdzības
Ievads
Qubic tīkls ir izveidojis savu reputāciju ātruma ziņā, sasniedzot 15,5 miljonus darījumu sekundē, ko apstiprinājusi CertiK. Aiz šīs veiktspējas slēpjas augstas jaudas mašīnu tīkls, kas tieši palaidnē protokolu uz bare metal aparatūras. Lai gan efektīva, šī arhitektūra rada izaicinājumu: aparatūras prasības ir ierobežojušas to, kas var piedalīties tīkla atbalstīšanā.
Qubic tīkla sargi ir izstrādāti, lai to mainītu. Ieviešot vieglo mezglu iespējas ar zemākām aparatūras prasībām, iniciatīva noņem ieejas barjeras un padara tīkla dalību pieejamu visiem. Vairāk dalībnieku nozīmē spēcīgāku, decentralizētāku tīklu.

Over the past few years, AI and crypto have begun to converge into one of the most powerful narratives in technology.
Projects promise:
decentralized AI infrastructureautonomous agentsdistributed machine learningtokenized data economies
Names like SingularityNET, Fetch.ai, and Bittensor are frequently mentioned as pioneers of decentralized AI.
But if we look deeper, most of these projects are not fundamentally reinventing artificial intelligence.
They are building economic or infrastructure layers around existing AI models.
One project, however, is attempting something much more radical.
Qubic is trying to rethink how intelligence itself should be built.
At the center of that vision lies a new architecture called Neuraxon.
If their ideas prove viable, the implications could extend far beyond crypto — potentially touching the future path toward Artificial General Intelligence (AGI).
The Two Competing Paths Toward AGI
Right now, the global AI industry appears to be converging on two very different philosophies of intelligence.
Path 1: Scaling Intelligence
This is the approach followed by major AI labs:
OpenAIGoogle DeepMindAnthropicMeta
The strategy is simple:
Scale everything.
more datamore computemore parameters
This approach has produced astonishing results:
GPT modelsGeminiClaude
These systems can write, code, reason, summarize, and converse with remarkable fluency.
But despite their power, they share a fundamental limitation.
They are frozen intelligence.
The Problem with Frozen AI
Modern AI systems follow a familiar lifecycle:
Train → Freeze → Deploy
During training:
massive datasets are ingestedbillions of parameters are optimized
After training ends:
the model is deployedthe weights are fixed
From that point onward, the system performs inference only.
It no longer learns from its experiences.
In other words:
The AI you interact with today is a snapshot of intelligence frozen in time.
No matter how many conversations it has, it does not accumulate experience in the way biological intelligence does.
If a human brain stopped learning the moment it began interacting with the world, we would not call it intelligent.
We would call it dysfunctional.
Why Continuous Learning Matters
Biological intelligence is fundamentally different.
Humans and animals learn continuously through:
experienceexplorationenvironmental interaction
Every moment reshapes neural connections through synaptic plasticity.
Learning and living are not separate processes.
They are the same process.
Many researchers believe that true AGI will require similar properties, including:
lifelong learningadaptive memoryenvironmental interactionself-directed exploration
This is where a different paradigm begins to emerge.
The Second Path: Evolutionary Intelligence
Instead of building bigger models, some researchers are exploring whether intelligence might emerge from adaptive systems that evolve over time.
In this paradigm:
AI is not a finished product.
It is a continuously evolving system.
Multiple agents interact, adapt, and compete, gradually improving through experience.
Rather than a static model, intelligence becomes something closer to an ecosystem.
This idea is much closer to how biological intelligence emerged on Earth.
And it is the philosophical foundation behind Qubic's AGI research direction.
What Makes Qubic Different
Most AI-crypto projects focus on creating markets or infrastructure for AI services.
Qubic takes a different approach.
Instead of asking:
How can we monetize AI?
Qubic asks a deeper question:
How should intelligence itself be built?
The Qubic ecosystem explores three major components:
1. Distributed Compute
A decentralized network of nodes provides computational resources that can run AI systems continuously.
Instead of relying on centralized GPU data centers, computation can be distributed across a network.
2. Evolutionary AI Frameworks
Within the ecosystem, frameworks like Aigarth explore evolutionary AI concepts.
Multiple AI agents can:
interactcompeteevolve
In some ways, this resembles natural selection in digital form.
3. Neuraxon
The most intriguing component of the ecosystem is Neuraxon, a bio-inspired neural architecture designed to support continuous learning and adaptive intelligence.
Instead of mimicking conventional neural networks, Neuraxon attempts to model aspects of biological neural systems.
Neuraxon: A Different Kind of Neural Architecture
Traditional neural networks are essentially static computational graphs.
Weights are adjusted during training but remain fixed afterward.
Neuraxon proposes a more dynamic approach inspired by neuroscience.
Tri-State Neurons
Most artificial neurons operate in a binary-like activation pattern.
Neuraxon introduces three possible states:
+1 — Excitatory0 — Neutral−1 — Inhibitory
This structure mirrors biological neural activity, where neurons can either stimulate or suppress activity within a network.
The neutral state also allows the system to represent hesitation, uncertainty, or dormant potential activity.
Continuous Neural Dynamics
Traditional AI operates through discrete computations:
Input → Compute → Output

Neuraxon instead maintains a continuous internal neural state.
Even when no external input arrives, the system’s internal state continues evolving over time.
This mirrors the behavior of biological brains, where neural activity never truly stops.
Instead of isolated computations, the system behaves more like an ongoing cognitive process.
Synaptic Plasticity
One of the defining characteristics of biological intelligence is plasticity.
Connections between neurons strengthen or weaken depending on experience.
Neuraxon introduces mechanisms where synapses can:
strengthen through repeated activationweaken when unusedreorganize network structures
This allows the system to adapt dynamically during operation rather than only during training.
Multi-Timescale Learning
Neuraxon also explores learning across multiple timescales.
Short-term adjustments can coexist with slower structural changes.
This is similar to biological systems where:
the hippocampus supports short-term learningthe cortex stabilizes long-term knowledge
Such mechanisms may help balance the classic problem of AI learning:
plasticity vs stability.
Neuromodulation
Another feature inspired by biology is neuromodulation.
In the human brain, chemicals like dopamine and serotonin regulate when neural circuits become more plastic or more stable.
Neuraxon explores similar mechanisms that determine when learning should occur.
This may help address one of the biggest challenges in continuous learning systems:
catastrophic forgetting.
Comparing Major AI-Crypto Projects
To better understand Qubic’s position, it helps to compare it with other major projects.

What stands out is that Qubic is one of the few projects attempting to design a new architecture for intelligence itself.
Dead AI vs Living AI
One way to think about this shift is the difference between Dead AI and Living AI.
Dead AI
Most modern systems fall into this category.
They are:
trained oncedeployedfixed afterward
They are incredibly powerful but fundamentally static.
Living AI
Living AI refers to systems that:
operate continuouslylearn from experienceadapt their internal structure over time
Instead of static models, they behave more like organisms.
If architectures like Neuraxon succeed, AI could gradually transition from software tools to adaptive cognitive systems.
The Hidden AGI Race
The AI race we usually hear about involves companies like OpenAI and Google.
But beneath that visible competition lies a deeper question:
Where does intelligence actually come from?
Is it the result of:
bigger modelsmore datamore compute?
Or does it emerge from:
adaptationinteractionevolutionary dynamics?
If the second view turns out to be correct, the path toward AGI might not come from ever-larger language models.
It might come from systems capable of continuous learning and evolution.
A Possible “Cambrian Explosion” of AI
In biological history, the Cambrian Explosion marked a period where life diversified rapidly into countless new forms.
Some researchers believe that if AI systems gain the ability to:
evolvelearn continuouslyinteract with complex environments
we could witness something similar in artificial intelligence.
Instead of a few dominant models, we might see an explosion of diverse AI systems evolving across decentralized networks.
The Big Question of the Next Decade
The future of AI may ultimately depend on one question:
Does intelligence emerge from larger models… or from adaptive systems that evolve over time?
If the answer lies in evolution and continuous learning, projects like Qubic and Neuraxon could represent early experiments in a completely new direction for artificial intelligence.
It is far too early to know whether this approach will succeed.
But the ideas being explored raise one of the most fascinating possibilities in modern technology:
AI that does not merely run algorithms, but evolves through experience.
Further Reading
Readers interested in exploring these concepts further can consult the following resources:
#Qubic Ecosystem
https://github.com/qubic
#Neuraxon Research Paper
https://www.researchgate.net/publication/397331336_Neuraxon
Qubic #AGI Journey
https://www.researchgate.net/publication/387364505_Qubic_AGI_Journey_Human_and_Artificial_Intelligence_Toward_an_AGI_with_Aigarth
Neuraxon GitHub Repository
https://github.com/DavidVivancos/Neuraxon
Neuraxon Interactive Demo
https://huggingface.co/spaces/DavidVivancos/Neuraxon
Research Website
https://vivancos.com
#artificialintelligence
#CryptoAi

The global technology sector is crashing into a brutal structural barrier. With NVIDIA’s latest Rubin GPUs demanding a staggering 260% increase in high-bandwidth memory (HBM4) compared to the H100, we are no longer facing a simple "chip shortage." We have entered the era of the "Memory Wall."
The math is ruthless: the spot price of 16GB DDR4 RAM has skyrocketed from $5 to $77 in just eight months. Every HBM4 module produced for a centralized data center is a memory chip stripped from the consumer supply chain. As hardware costs spiral out of control, the traditional method of training Artificial Intelligence—throwing massive amounts of RAM and compute at inefficient algorithms—is becoming economically unsustainable.
Amidst this crisis, Qubic stands out not just as a blockchain project, but as a foundational infrastructure revolution. By combining Trinary Logic, Bare Metal execution, and Useful Proof-of-Work (uPoW), Qubic is redefining how machines think.
1. The Dead End of "Binary Brute Force"
Today’s centralized AI models rely on binary logic (0s and 1s) and massive datasets. To compensate for the inherent limitations of binary architecture, tech giants use "Brute Force"—scaling up GPU clusters and memory pools to astronomical sizes.
However, when memory becomes the ultimate bottleneck, this approach fails. Qubic tackles this problem at its root: We don't need more memory; we need smarter computation.
2. Trinary Logic: The IEEE-Validated Strategic Weapon
The core DNA of Qubic is its shift from Binary to Trinary Logic (-1, 0, 1).
Academic Validation: This isn't just a crypto whitepaper concept. The recent acceptance of Qubic’s Trinary Logic research paper by the IEEE for the AMLDS 2026 conference in Japan proves that Neuraxon (Qubic's AI) is a serious computer science breakthrough.Brain-Like Efficiency: Trinary logic closely mimics human neural patterns (Excitation, Inhibition, Neutral states). This allows Neuraxon to process complex information—like the newly released 1.12TB Neuraxon2LifeTS dataset—with a significantly smaller memory footprint than traditional binary models.
3. The Power of "Bare Metal" Execution

Running an AI on Windows or Linux is like running a marathon in a heavy winter coat. Operating Systems (OS) act as middlemen, consuming precious memory bandwidth and processing power just to keep themselves running.
Qubic removes the middleman entirely by running on Bare Metal.
100% Hardware Utilization: By executing directly on the hardware without an OS, Qubic maximizes the bandwidth of every RAM stick and GPU.Zero Latency & Physical AI: This ultra-low latency environment is exactly what allowed Qubic to successfully demonstrate Neuraxon controlling a physical robot (Sphero Mini) in real-time. We are bridging the gap between digital simulation and the physical world.
4. Critical Q&A: Addressing the Skepticism
To truly understand Qubic's hegemony, we must address the hardest questions from the community:
Q1: "If Trinary Logic is so superior, why aren't Google, NVIDIA, or Intel using it?"
Answer: The Legacy Cost. The entire $10 trillion global tech ecosystem is built on 70 years of Binary infrastructure. For a tech giant to switch to Trinary, they would have to scrap everything from software compilers to silicon foundries and start over. Qubic has the "First Mover Advantage" because we built a Trinary ecosystem from the ground up, unchained by legacy debt.
Q2: "Doesn't running Bare Metal hurt decentralization since it's harder for average users to set up?"
Answer: It actually protects decentralization. As RAM prices explode, average consumer PCs will soon struggle to run complex AI models inside a bloated OS. Qubic’s Bare Metal optimization strips away the software bloat, allowing older or consumer-grade hardware to punch above its weight and remain competitive in the network.
Q3: "Is the Dogecoin ASIC mining integration just a hype gimmick?"
Answer: It is a strategic economic engine. Mining is a business, and miners need stability. By integrating Dogecoin ASIC mining (Mainnet launching April 1, 2026), Qubic creates a "Dual-Engine" economy. ASIC hardware secures the network and provides steady revenue to miners, while our uPoW consensus directs GPU/CPU power toward training the AI. This ensures our infrastructure survives bear markets and hardware price shocks.
Q4: "How can a decentralized network ever beat OpenAI's massive supercomputers?"
Answer: Efficiency beats Scale in a resource-constrained world. OpenAI wins by having the most resources. Qubic is designed to win by having the most efficient architecture. Through Trinary Logic and Bare Metal, we achieve neural complexity using a fraction of the hardware. We aren't trying to out-spend the giants; we are out-thinking them.
The Verdict
The 2026 memory crisis will act as a brutal market filter. It will wipe out the "AI wrappers" and GPU-rental platforms that lack fundamental innovation. As capital flees the hype, it will seek purpose-built, full-stack infrastructure.
With its IEEE-validated Trinary core, Bare Metal execution, and self-sustaining uPoW economy, Qubic is building the ultimate sanctuary for the future of Decentralized Intelligence.
Dive into our open-source infrastructure here: https://github.com/qubic
Read the latest Qubic All-Hands recap
#Qubic #DeAI #trinary #IEEE #UPoW

Nesenajā CoinDesk rakstā, "Decentralizētā AI ir kritumā, bet īstās iespējas parādās," lieliski atspoguļota pašreizējā riska kapitālistu noskaņa: uzbudinājums izzūd, un investori tagad pieprasa saturu nevis tikai modes vārdus. Kamēr daudzi DeAI projekti cīnās, lai pierādītu savu lietderību, Qubic’s March 2026 All-Hands updates sniedz meistarklasi par to, kā pāriet no "kriptovalūtu uzbudinājuma" uz "industrijas kvalitātes AI infrastruktūru."
Šeit ir, kā Qubic risina galvenās bažas, ko pauduši globālie riska kapitālisti:

2026. gada martā notikušā vispārējā sanāksme izcēla milzīgu lēcienu Qubic tīklā AI, Core Tech un pētījumu jomā.
1. AI & Zinātne: No simulācijas uz realitāti 🤖
Fiziskā AI: Zinātniskā komanda demonstrēja Neuraxon kontrolējot fizisku robotu (Sphero Mini). Tas pierāda, ka Qubic’s AI var pārvarēt plaisu starp digitālajām neirālajām tīklām un reālās pasaules aparatūru.
Milzīgs datu kopums: Izlaists Neuraxon2LifeTS (1.12 TB), datu kopums, kas ir 190 reizes lielāks nekā iepriekšējās versijas, veicinot nākamo decentralizētās AGI pētījumu fāzi.

Từ đầu năm 2026, thị trường crypto tại Việt Nam đang bước vào một giai đoạn rất đáng chú ý: từ tăng trưởng tự phát sang phát triển có định hướng và quản lý rõ ràng hơn.
📊 Việt Nam vẫn là một trong những cộng đồng crypto lớn nhất thế giới
Theo báo cáo Global Crypto Adoption Index, Việt Nam hiện nằm trong TOP 4 quốc gia có mức độ chấp nhận crypto cao nhất thế giới.
Một số thống kê đáng chú ý:
Hơn 20 triệu người Việt Nam sở hữu crypto
Khoảng 21% dân số tham gia thị trường tài sản số
Khối lượng giao dịch crypto tại Việt Nam giai đoạn 2024–2025 đạt khoảng 220–230 tỷ USD
Điều này cho thấy crypto không còn là một thị trường ngách mà đã trở thành một phần của nền kinh tế số đang phát triển rất nhanh tại Việt Nam.
⚖️ 2026: bước ngoặt pháp lý cho thị trường crypto
Một trong những sự kiện quan trọng nhất là Luật Công nghiệp Công nghệ số có hiệu lực từ năm 2026, lần đầu tiên đưa khái niệm crypto assets và virtual assets vào khung pháp lý chính thức.
Ngoài ra, chính phủ Việt Nam cũng triển khai:
Chương trình sandbox 5 năm cho thị trường crypto (2025–2030)
Cơ chế cấp phép sàn giao dịch tài sản số
Các tiêu chuẩn về AML/KYC và quản lý rủi ro
Những thay đổi này có thể mở ra một giai đoạn mới:
👉 Crypto được quản lý rõ ràng hơn
👉 Nhà đầu tư được bảo vệ tốt hơn
👉 Các nền tảng lớn có thể mở rộng hoạt động hợp pháp tại Việt Nam.
🚀 Vai trò của cộng đồng Binance tại Việt Nam
Trong bối cảnh đó, các nền tảng toàn cầu như Binance đang đóng vai trò quan trọng trong việc:
cung cấp hạ tầng giao dịch an toàn
thúc đẩy giáo dục và chia sẻ kiến thức crypto
phát triển cộng đồng creator và builder
Các chương trình như CreatorPad Vietnam đang khuyến khích người dùng Việt Nam không chỉ giao dịch mà còn trở thành người tạo nội dung và lan tỏa kiến thức Web3.
Điều này rất quan trọng vì Việt Nam là thị trường “community-driven” – nơi cộng đồng đóng vai trò quyết định trong sự phát triển của hệ sinh thái crypto.
🔎 Nhận định
Nếu xu hướng hiện tại tiếp tục:
Việt Nam có thể trở thành trung tâm crypto lớn của Đông Nam Á
cộng đồng creator và developer Việt Nam sẽ ngày càng có ảnh hưởng trong Web3
các nền tảng lớn như Binance sẽ tiếp tục là cầu nối giữa người dùng Việt Nam và thị trường toàn cầu
Crypto tại Việt Nam không chỉ là trading nữa —
mà đang dần trở thành một phần của nền kinh tế số tương lai.
💬 Cộng đồng nghĩ sao về tương lai crypto tại Việt Nam trong 3–5 năm tới?
@Binance Vietnam
#CreatorpadVN
$BNB

Tin tức Binance dự định xin thêm 5 giấy phép hoạt động tại châu Á cho thấy một xu hướng rất rõ ràng: khu vực châu Á – Thái Bình Dương đang ngày càng đóng vai trò trung tâm trong sự phát triển của thị trường crypto toàn cầu.
Theo nhiều báo cáo gần đây, khối lượng giao dịch crypto tại khu vực này đã đạt khoảng 2,36 nghìn tỷ USD, tăng trưởng mạnh so với năm trước. Đặc biệt, nhiều quốc gia có mức độ chấp nhận crypto cao nhất thế giới đều nằm ở châu Á, trong đó Việt Nam luôn nằm trong nhóm dẫn đầu.

Từ góc nhìn của cộng đồng Binance Việt Nam, đây là một tín hiệu rất tích cực. Việc Binance tiếp tục mở rộng giấy phép và tăng cường tuân thủ pháp lý cho thấy sàn đang hướng tới sự phát triển bền vững, minh bạch và lâu dài trong khu vực.
Điều này cũng mở ra nhiều cơ hội hơn cho người dùng trong khu vực: từ việc tiếp cận các sản phẩm tài chính số, tham gia vào hệ sinh thái Web3, cho tới việc đóng góp nội dung và tri thức cho cộng đồng.
Cộng đồng crypto tại Việt Nam vốn đã rất năng động. Khi khu vực châu Á ngày càng trở thành động lực tăng trưởng chính của thị trường, vai trò của cộng đồng Việt Nam chắc chắn sẽ ngày càng rõ nét hơn.
Có thể nói rằng tương lai của crypto không chỉ là toàn cầu – mà đang ngày càng mang đậm dấu ấn của châu Á.
#CreatorpadVN @Binance Vietnam $BNB 🚀

Qubic is bringing Dogecoin mining into its network. Not as a side feature or an afterthought, but as a fundamental expansion of what the protocol can do. The architecture is finalized. Testing begins in March. Mainnet launch target is April 1, 2026.This is the full picture of how Dogecoin mining will work on Qubic, what it means for the network, and why existing miners should be paying attention.
What Is Qubic’s Mining Model?
Qubic doesn’t mine for the sake of mining. The network runs on a concept called Useful Proof of Work, where computational power serves a real purpose: training Aigarth, Qubic’s AI research initiative. Miners contribute processing power to advance AI models, and the network rewards them with QUs for that work.
Until now, the network has also mined Monero (XMR) during idle cycles, alternating between AI training tasks and XMR hashing. That model worked well as a proof of concept. It demonstrated that a blockchain could extract real-world value from its mining infrastructure beyond just securing a ledger.
Dogecoin changes the equation entirely.
Parallel Mining, Not Alternating: How Dogecoin and AI Training Coexist
The single biggest technical shift with Dogecoin integration is this: $DOGE mining will run parallel to AI training. Not in alternating blocks. Not in time-sliced cycles. Simultaneously.
Here’s why that’s possible. Dogecoin uses the Scrypt algorithm, which requires ASIC hardware. Qubic’s AI training runs on CPUs and GPUs. These are fundamentally different pieces of hardware doing fundamentally different jobs. So, instead of competing for the same resources, they operate simultaneously.
ASIC miners handle Dogecoin. CPUs and GPUs continue training Aigarth. Both contribute to the network. Neither displaces the other.
This is a departure from the XMR model, where CPU time had to be split between AI work and Monero hashing. With Dogecoin, that tradeoff disappears. The network’s full computational resources stay dedicated to AI training while a new class of hardware contributes Doge hashrate on top.
Qubic’s Dogecoin Mining Architecture: A Technical Breakdown
The Qubic team, led by tech lead Joetom, walked through the full architecture during the February 19, 2026 All Hands AMA (Watch the full replay here). The system consists of four main components working together.
Think of it like a postal system with built-in fraud detection.
Miners connect through the Stratum protocol (TCP) to a Pool Server. This server acts like a local post office: it hands out work assignments, sets the difficulty bar for what counts as a valid “stamp,” and checks incoming mail. The Pool Server then talks to a Dispatcher, a custom-built bridge that sits between the Qubic network and the Doge network. The Dispatcher is the sorting facility. It takes tasks from an external Doge Pool Server, translates them for Qubic miners, and routes completed work back to the Doge mining pool for share submission.
When a miner finds a valid share that clears the Qubic network’s difficulty threshold, the Pool Server forwards that share through the Dispatcher into the Qubic network. This is where the process diverges from traditional mining pools.
Instead of trusting a single pool operator to confirm that a share is legitimate, the Qubic network runs that verification through Oracle Machines. The network sends an oracle query asking a simple question: is this Doge share valid? Oracle Machines, operated independently by computors across the network, respond with a yes or no. Up to 13 of these oracle commits can be bundled into a single transaction, which keeps the validation pipeline fast enough for high-throughput mining.
Picture a room full of independent auditors each checking the same receipt. If the majority agree it’s real, it passes. No single auditor can rubber-stamp a fake.
This is the first real-world external use case for Qubic’s Oracle Machines, which went live on mainnet February 11, 2026. As of the last AMA, over 11,000 successful oracle queries had already been processed with zero unresolvable requests.

Breathing Life Into Retired ASIC Mining Hardware
One of the more practical aspects of this integration is what it means for older Scrypt ASICs. Machines like the Antminer L3+ that have been collecting dust on a shelf because they can’t turn a profit on standard Doge pools get a second life here.
Qubic’s founder, Come-from-Beyond (CFB), explained the logic: these ASICs can contribute hashrate to the network, with all mined Dogecoin flowing through the dispatcher. The ASIC layer is entirely additive. It generates new revenue that didn’t exist before without cutting into existing CPU/GPU miner rewards.
How that revenue gets distributed is still being shaped. A dedicated group of community pools and computors is actively designing the economic framework: reward splits, fund allocation, and the relationship between ASIC-generated value and the broader QU economy. The goal is to create a model where QU incentives make otherwise unprofitable mining hardware worthwhile again. Computor documentation with technical specs for pool participation is scheduled for release by mid-March.
Oracle Machines: The Decentralized Validation Backbone
It is worth zooming in on why Oracle Machines matter here. In most mining setups, share validation is handled off-chain by the pool operator. You trust the pool and that’s the model.
Qubic takes a different approach. By routing Doge share validation through Oracle Machines, the network creates a decentralized verification layer. Computors running Oracle nodes independently confirm whether submitted shares are legitimate. This removes single points of failure from the validation process and ties Dogecoin mining directly into Qubic’s on-chain infrastructure.
It also generates real transaction volume. Every validation cycle creates on-chain network activity. Dogecoin mining doesn’t just introduce a new revenue source; it drives protocol usage in a way that strengthens the network’s fundamentals.
Starting in late March, Oracle Machine participation will directly affect computor revenue calculations. Running an Oracle node becomes a contributor to a computor’s earning potential rather than just a voluntary service.
The Community-Driven Business Model
The technical architecture is locked. The business model is where the community is stepping in.
A community-driven business consolidation group is defining the economic framework: how Doge mining revenue gets distributed, what percentage flows to ASIC miners versus the broader network, and how the model scales as more hardware comes online. This work runs as a parallel workstream alongside the technical implementation.
The approach reflects Qubic’s broader governance philosophy. The Governance & Funding Framework was approved by computor vote at Epoch 200 on February 14, 2026, with 614 yes votes and zero no votes. Decisions about how new revenue streams integrate into the network are made through community participation, not top-down mandates.
Dogecoin Mining on Qubic: Timeline and What Comes Next
The project has moved past design into active implementation. Here’s where things stand:
The main architecture and share validation logic are complete. The Dispatcher is currently in development. Testing begins early March. Computor documentation will be published by mid-March. The mainnet launch target date is April 1, 2026, with full production by April 30. That said, the team has been clear: network stability takes priority over hitting dates. If testing reveals issues, the timeline will be extended.
Why Dogecoin Mining Matters Beyond the Hashrate
Dogecoin integration is a milestone, but the significance runs deeper than adding another coin to mine.
It proves that Qubic’s infrastructure, Oracle Machines, smart contracts, and the computor network, can support external use cases at scale. Doge mining is the first application built on top of Oracle Machines. It won’t be the last. The same validation framework can serve price feeds, cross-chain data, and any external information that smart contracts need to act on.
It also demonstrates that Useful Proof of Work can expand horizontally. CPU/GPU resources train AI. ASIC resources mine Dogecoin. Future hardware categories could plug into additional workstreams. The network grows by absorbing more types of useful computation, not by requiring existing participants to do less.
Qubic set out to build a decentralized AI infrastructure where computation serves a purpose. Dogecoin mining is the next proof point that the model works, and that the network can scale the concept into entirely new territory.
Stay in the Loop
$DOGE mining is one piece of a much bigger picture. Oracle Machines, Neuraxon 2.0, the new Governance Framework, core optimizations, March and April are packed with milestones.
For the full breakdown of everything the team covered in the latest session, read the Qubic All-Hands Recap: February 19, 2026.
New to Qubic? Start with What is Qubic to understand the network from the ground up, or dive into the technical documentation to explore Oracle Machines, smart contracts, and the mining architecture firsthand.
Got questions? The community is active on Discord and X. Jump in.
#Qubic #MiningCrypto #Dogecoin‬⁩ #UPoW #AI

Chào cộng đồng @Binance Vietnam ! Là một người mới gia nhập đại gia đình Binance Square, tôi rất hào hứng khi được chia sẻ góc nhìn chuyên sâu của mình về xu hướng bùng nổ nhất hiện nay: Sự giao thoa giữa Trí tuệ nhân tạo (AI) và Blockchain. Trong bài viết đầu tiên thuộc chiến dịch #CreatorpadVN này, chúng ta sẽ cùng phân tích bệ phóng mà $BNB đang tạo ra cho kỷ nguyên AI.

1. Bước tiến chiến lược của BNB Chain với MCP
Mới đây, hệ sinh thái BNB Chain đã thực hiện một bước đi đột phá khi hỗ trợ các AI Agent thông qua giao thức MCP (Model Context Protocol). Giờ đây, các đặc vụ AI không còn là những dòng code vô tri, chúng đã được trang bị các "kỹ năng" thực thụ:
Đọc dữ liệu chuỗi: AI có thể phân tích hợp đồng thông minh và dữ liệu on-chain theo thời gian thực.Thực thi giao dịch: AI có khả năng quản lý ví và tự động thực hiện các lệnh swap hoặc chuyển tiền.Định danh On-chain: Với tiêu chuẩn ERC-8004, mỗi AI Agent sẽ có một danh tính riêng biệt trên mạng lưới.
Điều này biến $BNB trở thành một lớp thanh toán và thực thi lý tưởng cho các ứng dụng AI hiện đại.
2. Từ AI "Lắp ghép" đến AGI "Bản địa"
Trong khi BNB Chain cung cấp công cụ kết nối tuyệt vời, thế giới khoa học cũng đang chứng kiến những bước tiến khổng lồ về hạ tầng AI lõi. Một minh chứng điển hình là bài báo khoa học "The Neutral Buffer State: Trinary Logic Advantage in Branching Ratio Stability for Continuous-Time Networks" vừa chính thức được chấp nhận để công bố và trình bày tại Hội nghị Quốc tế AMLDS 2026 tại Osaka, Nhật Bản.
Đây là một phần thiết yếu trong nghiên cứu về Neuraxon và Aigarth. Việc sử dụng Logic Tam phân (Trinary Logic) thay vì nhị phân truyền thống giúp mô phỏng não bộ sinh học chính xác hơn, tạo tiền đề cho sự ra đời của AGI (Trí tuệ nhân tạo tổng quát) thực thụ.
3. Tầm nhìn 2026: Khi BNB Hội Ngộ cùng AGI
Sự kết hợp giữa một blockchain mạnh mẽ, phí rẻ như BNB Chain và những đột phá về AI mã nguồn mở (Open Science) sẽ tạo ra một hệ sinh thái không thể ngăn cản. Binance không chỉ là nơi giao dịch, mà còn là bệ phóng cho những công nghệ thay đổi nhân loại.
Hãy cùng tôi cập nhật những xu hướng công nghệ mới nhất và tận dụng cơ hội từ hệ sinh thái Binance ngay hôm nay!
👉 Khám phá ngay tại: Beyond Binary
#CreatorpadVN #Binance #Qubic #BinanceVietnam