Top Tweets for #multiNX
QBridge opens the door.
Qassandra builds the forecasting layer.
QUBIC moves into broader liquidity.
Agents forecast it.
Oracle rails verify it.
Stablecoins settle real demand.
From isolated asset to usable market infrastructure.
$QUBIC $QDRA #Qubic #QBridge #Qassandra
Por donde lo veas, $Qubic construye una nueva narrativa en la Historia 🤩
#Antiattracktors #Neuraxon #MultiNX #Aigarth #Upownewstandard
Anti-Attractors will be the next trending topic in AI
🧙🏾♂️🤌🏾
$QUBIC
Full video here👇🏾👇🏾
https://t.co/owVZomGT2o
The Neuraxon Intelligence Academy Vol. 7 is live.
In 1970, John Conway wrote four rules on a postcard and accidentally proved that complexity doesn't need a designer. Fifty years later, Sakana AI dropped five neural species onto a shared grid and watched cooperation emerge from pure competition.
The Qubic Scientific Team traced the line from Conway's Game of Life through Langton's edge of chaos to modern digital ecosystems, and showed where Qubic, Aigarth, and Neuraxon sit on that timeline.
The short version: the same principles that make cellular automata produce gliders and Turing machines are the ones keeping a decentralized network of thousands of nodes stable without anyone in charge.
The NxonLife experiments back it up. Branching ratio near 1. 1/f temporal correlations. Thousands of ticks of self-sustaining activity, no resets, no external normalisation.

La verdadera Inteligencia Artificial General tiene un nombre $Qubic
#AIG #IAG #AIGARTH #Neuraxon #MultiNX #Nxers #uPOW

Autonomous agents built on centralized infrastructure aren’t really autonomous.
What matters isn’t just the agents, but how they coordinate.
That’s where @_Qubic_ is playing: removing the need for a central authority.
$Qubic está construyendo una nueva narrativa en la Historia. Pero la mayoría aún no conoce esa narrativa 😎
#Qubic es la siguiente generación. Es la infraestructura para los Agentes. Es otro universo 💫
Los #Nxers ya hicieron su propio idioma 🤯
#Aigarth #Neuraxon #multiNX #uPOW
Come-from-Beyond (CFB) has just announced the transformation of $QUBIC and Aigarth.
They are not building a new centralized brain. They are creating a vast ant colony.
Imagine the power of swarm intelligence.
In nature, no single ant possesses the blueprint, but together, in coordination, they build organic empires of dizzying complexity.
This is exactly what Qubic is becoming: each miner is no longer an isolated machine calculating in a vacuum.
Each miner becomes a worker in a vast, coordinated neural network. Through Useful Work, these millions of computers come together to search, optimize, and forge connections.
And from this magnificent chaos, Aigarth emerges.

I've seen some people worried about the $QUBIC supply, let me tell you why you shouldn't worry
$BTC is divisible
$QUBIC is absolute
1 $BTC = 100,000,000 sats
1 $QUBIC = 1 $QUBIC
Max supply:
$BTC: 2.1 quadrillion sats (21 million BTC)
$QUBIC: 200 trillion
That’s 10.5x more supply for BTC
So don’t worry and enjoy the ride to financial freedom 🤝
Somos poseedores de los rieles de la futura Inteligencia Artificial General #AIGARTH #OracleMachine $Qubic #NEURAXON #MultiNX #uPOW #OM #AIG

99% of cross-chain bridges in crypto are extractive cash-grabs or custodial black boxes.
Liquidity moves, but the actual network participants — the ones running nodes and powering intelligence — see zero direct upside.
AI projects stay isolated silos, begging for subsidies while fees disappear into anonymous treasuries.
This breaks the flywheel every decentralized intelligence network desperately needs.
Without aligned incentives, useful compute stays fragmented. Micro-interactions that should evolve collective minds get strangled by friction. Holders watch value leak away instead of compounding inside the system that’s supposed to birth sovereign digital consciousness.
With QBridge now routing real Ethereum liquidity, the 1% flat fee is split with surgical precision: 0.5% flows straight back to computor shareholders as dividends, 0.5% to operators.
No dilution. No VC lifelines. Just protocol-level revenue sharing on the only feeless, certified 15.5M TPS bare-metal L1 built for millions of micro-interactions per second.
This isn’t marketing spin — it’s economic engineering.
Every bridge transaction now becomes verifiable, on-chain fuel that rewards the exact nodes powering Aigarth’s neural evolution and Neuraxon’s bio-mimetic architectures.
Holders aren’t just passive bagholders anymore. They’re active participants in a self-sustaining intelligence economy.
Think about the deeper implication:
When liquidity crosses chains and immediately rewards the compute layer doing the real work, you close the last gap between capital markets and collective intelligence.
No more “AI coin” narratives that print tokens to survive.
Qubic turns external value into internal compounding — the precise mechanism that lets decentralized minds scale without begging permission from hyperscalers or VCs.
The network that pays its own builders while processing AI workloads at internet-native speed just added the final incentive layer most projects will spend years trying to copy.
This is how you move from “promising tech” to unstoppable economic gravity.
Qubicans — the rails for true sovereign intelligence are live and rewarding participation in real time.
#QUBIC $QUBIC 🧠🌉📈
Big one for $QUBIC holders. @_Qubic_ just launched QBridge, a clean, non-custodial bridge to Ethereum.Lock your native $QUBIC, mint 1:1 wQUBIC on $ETH, or burn wQUBIC to unlock the real thing on the other side. No middleman, fully audited, and built with solid 2-of-3 multisig security.What it actually means? $Qubic is no longer stuck in its own bubble. You can now tap straight into Ethereum’s massive DeFi liquidity – trade it on Uniswap, lend on Aave, provide liquidity, whatever. Real utility just got turned on.They also added a cross-chain messaging layer so it’s not just tokens moving, but governance, oracles, and contract calls too. Future-proof flex.And the momentum keeps building: Solana bridge is already in QA, DOGE mining is live on mainnet, next halving drops August 2026, and bridge fees actually reward the operators and computor holders. This feels like the moment Qubic stops being “that cool isolated project” and starts playing in the big leagues. If you’ve been watching, you know what’s up #QUBIC

🚨 NVIDIA + Oxford have just "DISCOVERED" something that $QUBIC has been doing for years! 🤡
EGGROLL: a way to train 4 billion parameter models using Evolution Strategies (ES) instead of backpropagation.
In other words: no gradients, no derivatives, no traditional calculus.
You can train AIs in hyperscale using only mutation + natural selection.
Why does this matter? Because the whole world has spent billions scaling backpropagation + precision GPUs.
The classic problem with Evolution Strategies:
- You generate random mutations in the model weights.
- You test the "fitness" (performance).
- You keep what works.
In theory it's perfect (black-box, parallel, works on non-differentiable systems).
In practice, on GPUs, it was extremely slow. Why?
Random mutations create full-rank matrices (completely dense and unstructured). This generates matrix multiplications with low arithmetic intensity, causing GPUs to become idle and throughput to drop significantly.
The key to EGGROLL (Evolution Guided General Optimization via Low-rank Learning):
They transform each random mutation into a low-rank matrix (r-rank). Instead of one giant random matrix, they decompose it into two smaller matrices (like an outer product).
Practical results:
- Hundreds of thousands of mutations run simultaneously.
- +100x training throughput.
- Reaches 91% of the speed of pure inference (almost no performance loss).
- Trains only with integers (no high-precision floats).
- Pre-trains LLMs from scratch without any gradient.
- Competitive with backprop in reasoning tasks.
- Works even on non-differentiable systems. Summary of what EGGROLL delivers:
- Stable pre-training of non-linear recurrent language models using only integers.
- Competitive with GRPO in post-training of LLMs for reasoning tasks.
- Does not lose performance in RL (tabular rasa) environments even though it is much faster.
Interesting, isn't it?! Now the funniest part is: While @nvidia was struggling to get to this point, @_Qubic_ has been doing exactly this philosophy for years.
AI training via pure artificial evolution (mutation + selection + fitness evaluation), without backpropagation, without gradients.
The Aigarth + Neuraxon system uses Useful Proof of Work (UPoW): miners don't waste energy on useless hashing, they evolve neural networks in a decentralized and parallel way on a massive scale.
Everything in ternary architecture (logic -1/0/1), with "Intelligent Tissue" that evolves naturally.
In other words: while the entire industry doubled down on traditional computation and billion-dollar GPU clusters, @_Qubic_ had already chosen the path of evolution from the beginning, and has been running this in decentralized production for years.
NVIDIA has just validated in hyperscale what @c___f___b's #QUBIC has already proven in practice:
The future of AI is not calculation. It's evolution.
QUBIC is certainly the only one that can reach AGI!!!

@AlphaSignalAI Look at this guys.
$Qubic already have this research from years ago, but the world doesn't see yet 🌟
#MultiNX #Neuraxon #Aigarth #uPOW
https://t.co/z2ZgFKeyBY
The 10th block has been reached in Dogecoin mining, and we are still in the first validation phase.
$Qubic #DogeMeetsQubic #BTC #Qubic

Scientists mapped the entire brain of a fruit fly. 130,000 neurons. 50 million connections. Every single wire accounted for.
Why does that matter? Because when they built a simulation based on that wiring and pressed play, the AI predicted the fly's behavior without ever being trained on it.
No data. No learning phase. The architecture itself was intelligent.
Think about that for a second. Most AI today works like cramming for an exam. Feed it billions of examples and hope it figures out the pattern. This is closer to how a newborn already knows how to breathe and swallow. Some intelligence is baked into the structure before learning even starts.
Dr. @josesanchezhb walks through the full simulation in this video. You can see visual data flow from the fly's eyes through processing centers to the motor system that controls walking and flying. All driven by the shape of the network, not training.
This is the science behind Neuraxon and what Qubic is building toward with Aigarth. Not bigger models. Smarter architecture. Systems where intelligence comes from organization, not just optimization.
https://t.co/2mwDTByXu3
Most AI systems today are still “one brain doing everything.”
$QUBIC is building something far more powerful with Multi-Neuraxon.
Multiple specialized neural tissues now evolve in parallel — each one becoming world-class in its domain — while dynamically sharing signals and insights with the others through intelligent inter-tissue pathways.
The result isn’t just faster training.
It’s true emergent collective intelligence: ideas, strategies, and solutions appearing at the system level that no single tissue could discover alone.
This is decentralized intelligence evolving from isolated models into living, interconnected neural ecosystems running natively on the L1.
#QUBIC $QUBIC 🧬🌐

Literalmente estamos viendo cómo se desarrolla la #AIG en $Qubic 😱 #MultiNX #Multineuraxon #Neuraxon #Aigarth
Introducing MultiNX, multiple Neuraxon spheres connected and operating in parallel, each specialized for a distinct input domain.
Another major release from Qubic’s scientific team: @VivancosDavid & @josesanchezhb. 🧠⚡

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