e1000io 🧊⚡️👽 🦾 🌐 💎🌳

@c___f___b @grok mention the cryptocoins

Interesting, what cryptocoins will remain if #AI hacks all OSes... x.com/lyq_sqsp/statu…

@AtlamArg @_Qubic_ Anthill 🐜 $QUBIC

What’s the most mind-blowing word in the @_Qubic_ vocabulary? 🤯 Drop ONE word from the $QUBIC universe. No explanations. Mine? Arbitrator 👁️ If you know… you know.

@valis_team I'm not begging... Keep doing it, I don't care at all. The energy of your posts is weir, just don't fell good

@eem3789 The irony. x.com/valis_team/sta…

DOGE Phase 1. DOGE Phase 2. DOGE Phase 3. DOGE Phase 3 + 2 months.

@TarekSaidVzla Amén 🙏

Hoy más que nunca: "Nada te turbe, Nada te espante, Todo se pasa, Dios no se muda, La paciencia Todo lo alcanza; Quien a Dios tiene Nada le falta: Sólo Dios basta. Eleva el pensamiento, al cielo sube, por nada te acongojes, Nada te turbe. A Jesucristo sigue con pecho grande, y venga lo que venga, Nada te espante. ¿Ves la gloria del mundo? Es gloria vana; nada tiene de estable, Todo se pasa. Aspira a lo celeste, que siempre dura; fiel y rico en promesas, Dios no se muda. Ámala cual merece Bondad inmensa; pero no hay amor fino Sin la paciencia. Confianza y fe viva mantenga el alma, que quien cree y espera Todo lo alcanza. Del infierno acosado aunque se viere, burlará sus furores Quien a Dios tiene. Vénganle desamparos, cruces, desgracias; siendo Dios su tesoro, Nada le falta. Id pues, bienes del mundo; id, dichas vanas, aunque todo lo pierda, Sólo Dios basta". Santa Teresa de Ávila.

@KingTunde_SZN 3️⃣6️⃣

Nobody is yet to find the number 👀 What number is missing? RT Correct answer wins $4,000 Ends 95 hrs

#Aigarth progress looks like improving a single branch of a technology tree in a strategy computer game. It's all about energy. Trinary and CPU were the easiest discoveries. Anti-attractors felt like discovery of an alien tech, we still don't fully understand how to unlock its potential. Recently we removed some things which happened to be different aspects of the same phenomenon (separation to training and testing datasets, precise representation of data). For that we looked at the whole concept pretending to be a 4-dimensional being. Now we have to find much more energy than is currently available to the #Qubic ecosystem. But why should hoomans and their computers do all the work?.. So here is the plan: 1. Implement Outsourced Computations feature to give #AI ability to affect the outer world. 2. Run #IntelligentTissue on the network. 3. Target mining power towards improvement of that #IntelligentTissue. 4. Set the main task for that thing to bringing more energy into the ecosystem.

@elcodigomental 7

Juego mental. Solo el 1% resuelve correctamente. Comenta la solución. Os leo.

@odbashWizard Send it Wiz

Send $QUBIC above 1000/B 💃 #UPoW #AI #DePIN #AGI #Crypto #Gem

@2xnmore D. $HBAR or $ONDO

Everyone has an opinion on the best RWA token. Almost nobody has the right position. Where is your RWA allocation sitting right now? A. $LINK or $HBAR B. $ONDO or $AVAX C. $ICP or $VET D. A token you did not see on my list

@CrypttoManiac_ $QUBIC

Dime una red mejor que Kaspa.

@HowToAI_ @c___f___b is this 100% aligned with your vision? Are we adding any extra consideration in Qubic/Neuraxon model?

Yann LeCun was right the entire time. And generative AI might be a dead end. For the last three years, the entire industry has been obsessed with building bigger LLMs. Trillions of parameters. Billions in compute. The theory was simple: if you make the model big enough, it will eventually understand how the world works. Yann LeCun said that was stupid. He argued that generative AI is fundamentally inefficient. When an AI predicts the next word, or generates the next pixel, it wastes massive amounts of compute on surface-level details. It memorizes patterns instead of learning the actual physics of reality. He proposed a different path: JEPA (Joint-Embedding Predictive Architecture). Instead of forcing the AI to paint the world pixel by pixel, JEPA forces it to predict abstract concepts. It predicts what happens next in a compressed "thought space." But for years, JEPA had a fatal flaw. It suffered from "representation collapse." Because the AI was allowed to simplify reality, it would cheat. It would simplify everything so much that a dog, a car, and a human all looked identical. It learned nothing. To fix it, engineers had to use insanely complex hacks, frozen encoders, and massive compute overheads. Until today. Researchers just dropped a paper called "LeWorldModel" (LeWM). They completely solved the collapse problem. They replaced the complex engineering hacks with a single, elegant mathematical regularizer. It forces the AI's internal "thoughts" into a perfect Gaussian distribution. The AI can no longer cheat. It is forced to understand the physical structure of reality to make its predictions. The results completely rewrite the economics of AI. LeWM didn't need a massive, centralized supercomputer. It has just 15 million parameters. It trains on a single, standard GPU in a few hours. Yet it plans 48x faster than massive foundation world models. It intrinsically understands physics. It instantly detects impossible events. We spent billions trying to force massive server farms to memorize the internet. Now, a tiny model running locally on a single graphics card is actually learning how the real world works.

Jensen Huang says AGI is here. We disagree. His definition? An AI that builds a billion-dollar company. Our definition? What a system does when it doesn't know what to do. Intelligence is not scale. It never was. Our Scientific Team breaks down why current AGI claims fall short and what actually matters: integration, not size.

A major update of #Aigarth is approaching. We are transforming #Qubic into a giant "anthill" where every miner will be searching for shares in a coordinated manner (like ants for food). But we are not trying to create #SwarmIntelligence, we are using it for something more ambitious.

Qubic’s DOGE mining dashboards are fully public. But most people don’t know what they’re looking at. Quick breakdown: Hashrate → Combined Scrypt power across all connected ASICs. Watch trends over days, not minutes. Sudden drops signal disconnections. Acceptance Rate → The key efficiency metric. Above 95% is healthy.  Dispatcher Status → The bridge between Qubic and Dogecoin networks. If it’s offline, nothing flows. Look for “online” + stable uptime. Blocks Found → Each one earns 10,000 DOGE. The log shows how frequently the network discovers blocks, which correlates with hashrate growth. Solution Queue + Stratum Queue → Both should sit at zero. Growing queues mean bottlenecks or stale shares. Every metric is transparent. Every block is verifiable.

@crypto_with_seb access (and congrats!)

One small simple idea is turning into a journey of a lifetime. Anyone who comments “access” will have free access to the entire system once it’s live. Inside: - alert scalping bot - next 100x scanner - Hyperliquid trading bot (link your wallet and it trades for you)

@Grayscale $QUBIC

You don't own enough ___________.

The AI agent era is coming whether enterprises are ready or not. The companies that survive it will be the ones that built verification into their infrastructure from the start. Not layered on top. Not outsourced to a vendor. Built in. And Qubic is built differently: docs.qubic.org

Si salimos campeones del mundo le dan 50 millones de dólares a la AFA, si lo reparten se le puede dar 1 millon a cada argentino y encima sobra!!!! Vamos Argentina!!!

@thetrue_notlie @Srodland This looks like classic FUD/misunderstanding (or possibly a misread transaction). Qubic's feeless + burn-on-use model is unusual, so it's easy to misinterpret how NULL_ID or burns work if you're not deep in the docs/code.

@Srodland Maybe ask your boss why its possible to send qus from burn adress 😂

Thread: Why I think $QUBIC hits top 10. Not hopium. Just architecture and math. 👇 Set your alerts.