$QUBIC #AIgarth #NNN #Oracle #AI

boot Anna.exe mutate predict grow 50 seconds of what a blockchain looks like when its mining actually builds a mind. $QUBIC #Aigarth

Mainstream AI research is finally waking up to the fact that throwing massive, expensive GPUs at everything is a total dead end. This new 'Memory Attention' paper proves you can offload a ton of model capacity to cheap, efficient CPU lookups instead of burning through absolute power grids on GPUs. qubic-network:native

Wall Street is running the exact same playbook that tanked the economy back in the 1870s railroad bubble. These legacy giants are blowing trillions on massive infrastructure, blindly pumping cash into crazy $10.3T data centers and nuclear plants just because their basic coding has officially hit a brick wall. They think whoever hoards the biggest power grid wins the game, but they’re completely out of the loop. The absolute wild part? The whole AGI-ASI compute race has already been quietly finished by a next-level tech paradigm the mainstream world hasn’t even seen or heard of yet. qubic-network:native

I would rather buy something that will 10,000x $QUBIC

Today the AI you use at work is like electricity in a building: you pay, you plug in, and the landlord can cut the power. New price, new rule, tool taken away. Your work stops, and you have no say. qubic-network:native is aiming for AI that feels closer to a shared garden than a subscription. The network runs the machine and grows it, not through one company, but through a multitude of ordinary people training the network. A sovereign collective intelligence.

12 out ot 80 tomes of the Encyclopedia of Lost Minds: Echoes on AI are now available. 240 minds, from Gilgamesh to al-Mutanabbī, 2700 BCE to 915 CE: 3,600 years of thinking, each mind reconstructed from what actually survives of them and asked one question: If you were alive today, how would you build an AGI and a humanoid robot? Each tome is 20 minds, in the order history met them, and each tome asks one thing: 📜 I · The first names (2700–800 BCE): mortality, precedent, the inviolable gate 🌅 II · The axial dawn (800–551 BCE): the mind folding back on itself ⚖️ III · The classical turn (550–480 BCE): truth anchored where a liar cannot rewrite it 🏛️ IV · The Athenian peak (470–340 BCE): what a capable mind is for, and how it stays correctable 📐 V · The Hellenistic mind (334–179 BCE): engineering upward from a small auditable base 🪶 VI · The Roman witness (145 BCE–23 CE): what a mind owes to the record it leaves 🔬 VII · The tested world (27–192 CE): how a claim earns the right to be believed 🕸️ VIII · The shaped mind (200–470 CE): soundness that depends on no single node or sovereign 🔐 IX · The entrusted mind (476–575 CE): what may be done with what is held in trust ⚓ X · The anchored mind (581–711 CE): where a mind acts from when nothing it holds fits the case 🔏 XI · The warranted mind (712–810 CE): by what route a claim arrived, and what can strike it out 🌉 XII · The carried mind (810–915 CE): what the passage does to what it carries Why it matters? The problems we call new in AI, hallucination, sycophancy, provenance, delegation, alignment, are old, and these thinkers faced them with real stakes. Every chapter turns one thinker's answer into a working model you can run, compare and reuse, plus an interactive mind-map and a reading on the eight-axis E-AGI Barometer. @SchmidhuberAI has long argued that AI's memory is too short, and indeed it is. these tomes push that credit assignment back another three thousand years. Pick your field of AI research and see which ten lost minds take their seats: lostmindsai.com/whatmind This is the first stretch of a road that ends in 1905 with 1,600 minds. 🌐 The encyclopedia: lostmindsai.com 🧪 Demos and the Barometer: artificiology.com ⚙️ Every architecture, open source: github.com/DavidVivancos/Los… 📖 The series on Amazon: amazon.com/dp/B0H6F27RZR?bin… #SP Los 2 primeros Tomos también en español en iasperdidas.es #AGI #ArtificialIntelligence #Robotics #MachineLearning #HistoryOfIdeas #EncyclopediaOfLostMinds #LostMindsAI #Humanoids #

#NFT season is back! Are you holding at least one #Qbros, right? You can't call yourself a $Qubic OG if you're not part of the #Qbros family, the first-ever NFT collection. Available exclusively at qubicbay.io/marketplace/coll…

7️⃣8️⃣ OF 9️⃣9️⃣ 🫧 qubic-network:native Digital Tsunami 🌀 Satoshi Exposed 🪬 Alive & Building AI 🎬 Season 3 🕸️ Bloody Wizards Web in Bio #Qubic ---------------------♾️---------------------

Noice 👍🏻 ZK 4 $QUBIC

Anna was the first task it learned. It is the soil that Qubic's AI grows in. Read More: f.mtr.cool/zboffskb29

We have talked about Anna but not what it actually runs on. It is called Aigarth Intelligent Tissue, and the team made it open source. Think of it less as an AI model and more as a Petri dish.

Latest #qubic development.. zero knowledge built directly into the core… Trustless Useful Proof-of-Work (UPoW): For evolutionary neural networks like Aigarth and Neuraxon, proving the legitimacy of off-chain training data and fixed neural wiring topology is critical. By verifying SNARKs natively via QPI, the protocol can definitively and trustlessly tie off-chain compute to on-chain payouts. Miners can prove they executed complex AI workloads correctly, and the network can verify the receipt without replicating the heavy compute. A Zero-Knowledge (ZK) Proof Verifier for Qubic's QPI is a cryptographic verification engine embedded directly into the core node. Instead of executing heavy computational logic on-chain, Qubic smart contracts can receive a compact cryptographic proof (such as SNARK) and use this verifier module to execute a mathematical check. It ensures that off-chain computations were performed correctly against a known public state or circuit, without exposing the underlying private inputs. Technical Use Cases are broad: - Verifiable Off-Chain Compute (Verifiable Oracles): Confirming that complex data processing executed outside the node was done correctly by checking the cryptographic execution receipt. - Private Transactions and Mixing Pool with AML compliance - and many more... We plan to add BN254+Groth16 to the core in the next few months. If you have any request or question, please ask

While @Grayscale flows capital into the socially safe "AI blue-chip," they are completely blind to a massive thermodynamic reality. #TAO is a marketplace wrapper. qubic-network:native is a native biological superorganism. 🧵👇 1/ The Marketplace vs. The Supercomputer. #TAO does not train a unified intelligence. It hosts a network of separate subnets running pre-existing models that grade each other for token rewards. qubic-network:native behaves as a singular global supercomputer. Raw energy is directly transformed via Useful Proof of Work (uPoW) into actual neural synapses for Aigarth—a self-evolving artificial neural network. 2/ Software Abstraction vs. Bare-Metal Assembly. #TAO subnets rely heavily on heavy abstraction layers (Python, PyTorch, Linux nodes), carrying massive processing overhead and latency. qubic-network:native interacts directly with the processor chip in pure Assembly code. No operating system. Sub-second finality, wire-speed compute execution, and completely feeless. 3/ The Binary Ceiling vs. Ternary Evolution. #TAO operates on traditional 0/1 binary logic, meaning it faces the exact same scaling walls and power chokepoints as OpenAI, Anthropic, or Google. qubic-network:native runs on Balanced Ternary (-1, 0, +1), matching Euler's constant to maximize efficiency. Its algorithms dynamically construct and adapt hypotheses just like human reasoning. The market treats Bittensor #TAO as the AI endgame, but it has been completely stunned by qubic-network:native's raw architectural supremacy. The cognitive race ended before the legacy institutions even realized they were in it. qubic-network:native's technology structurally outclasses Bittensor #TAO 👽🛸

We have identified interesting features of #Aigarth's #AI training algo: 1. It creates hypotheses, verifies them, drops wrong ones, returns to put aside ones; 2. It uses the same pattern for different phenomena if they have similarities, applies little modifications to the pattern if necessary; 3. It chains simple calculations into complex ones, rearranges them. All this looks similar to how hoomans reason.

Aigarth to Ai is like the Manhathan project to nuclear bomb

This is Wall Street's greatest irony. They have mapped the future with absolute precision, yet they failed to secure their position because the foundational infrastructure post-ASI has already been captured by qubic-network:native. This is a race toward organic intelligence that was finished before they even began.

AI compute is about to trade like oil. When we look beyond standard crypto tickers and strip away speculative noise, qubic-network:native is not just a cryptocurrency; it is raw, programmable cognitive real estate. By fusing its bare-metal Assembly design with a Balanced Ternary computational structure, qubic-network:native forms a globally distributed synthetic brain tissue. Each individual token acts as a single, absolute Digital Neuron within this network. Traditional AI systems (like Silicon Valley's centralized LLMs) operate like monolithic, static software servers. Qubic's Aigarth ecosystem operates like a biological organism. 1 qubic-network:native = 1 Digital Neuron Unit.

#qubic #BOB NODE

You are welcome. I look after #Kaspa because I helped to shape its fate. If not me you would get it launched a couple of years earlier but with inferior tech.