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#AGI 6万，彩票，买了一点（仅个人记录，勿跟）
买的理由
1.叙事不错，英伟达概念，英伟达已实现通用人工智能
2.赔率足够，新盘发出来最高32万，掉下里6万，上了一点，几个车头在，看能不能坐个顺风车
3.社区还行，持币快600人，社区200多人，小社区太多，没有形成规模，
@币安Binance华语 @币安广场 #跟着锦鲤学打百倍金狗
关注Web3锦鲤日记，买的币翻十倍
买的理由
1.叙事不错，英伟达概念，英伟达已实现通用人工智能
2.赔率足够，新盘发出来最高32万，掉下里6万，上了一点，几个车头在，看能不能坐个顺风车
3.社区还行，持币快600人，社区200多人，小社区太多，没有形成规模，
@币安Binance华语 @币安广场 #跟着锦鲤学打百倍金狗
关注Web3锦鲤日记，买的币翻十倍
🚨 IN SUMMARY: NVIDIA CEO CLAIMS AGI MOMENT 🤖
Nvidia CEO Jensen Huang says “we’ve achieved AGI.”
• Suggests AI systems are reaching human-level general intelligence
• Massive implication for tech, jobs, and global power dynamics
• Could mark a turning point beyond current AI models
BUT:
• No widely accepted scientific or industry consensus confirms true AGI yet
• Likely reflects rapid progress in AI capabilities, not full AGI.
This is a bold, market-moving claim but AGI is still heavily debated.
#AI #AGI #Nvidia #TechRevolution #ArtificialIntelligence
Nvidia CEO Jensen Huang says “we’ve achieved AGI.”
• Suggests AI systems are reaching human-level general intelligence
• Massive implication for tech, jobs, and global power dynamics
• Could mark a turning point beyond current AI models
BUT:
• No widely accepted scientific or industry consensus confirms true AGI yet
• Likely reflects rapid progress in AI capabilities, not full AGI.
This is a bold, market-moving claim but AGI is still heavily debated.
#AI #AGI #Nvidia #TechRevolution #ArtificialIntelligence
AI doesn’t just need neurons. It needs control.
Your brain doesn’t learn randomly.
It learns when it’s allowed to learn.
That’s the role of astrocytes.
Once thought to be just “support cells,” they actually:
• gate plasticity
• filter noise
• stabilize memory
Now here’s the breakthrough 👇
In Volume 5 of Neuraxon Intelligence Academy, the team behind Qubic introduces:
Astrocyte-Gated Multi-Timescale Plasticity (AGMP)
A learning mechanism where:
👉 learning is not just driven by error
👉 it is controlled by context
This changes everything.
Because today’s AI systems don’t “decide” when to learn.
They just optimize continuously.
• ChatGPT
• Gemini
• Claude
They compute.
Neuraxon regulates.
And that difference might be the missing step toward real intelligence.
Read the full breakdown
👇
Astrocytes: The Hidden Force Behind Brain-Inspired AI
#Qubic #AI #AGI #Neuraxon #DeAI
Your brain doesn’t learn randomly.
It learns when it’s allowed to learn.
That’s the role of astrocytes.
Once thought to be just “support cells,” they actually:
• gate plasticity
• filter noise
• stabilize memory
Now here’s the breakthrough 👇
In Volume 5 of Neuraxon Intelligence Academy, the team behind Qubic introduces:
Astrocyte-Gated Multi-Timescale Plasticity (AGMP)
A learning mechanism where:
👉 learning is not just driven by error
👉 it is controlled by context
This changes everything.
Because today’s AI systems don’t “decide” when to learn.
They just optimize continuously.
• ChatGPT
• Gemini
• Claude
They compute.
Neuraxon regulates.
And that difference might be the missing step toward real intelligence.
Read the full breakdown
👇
Astrocytes: The Hidden Force Behind Brain-Inspired AI
#Qubic #AI #AGI #Neuraxon #DeAI
AI doesn’t just need neurons. It needs control.
Your brain doesn’t learn randomly.
It learns when it’s allowed to learn.
That’s the role of astrocytes.
Once thought to be just “support cells,” they actually:
• gate plasticity
• filter noise
• stabilize memory
Now here’s the breakthrough 👇
In Volume 5 of Neuraxon Intelligence Academy, the team behind $Qubic introduces:
Astrocyte-Gated Multi-Timescale Plasticity (AGMP)
A learning mechanism where:
👉 learning is not just driven by error
👉 it is controlled by context
This changes everything.
Because today’s AI systems don’t “decide” when to learn.
They just optimize continuously.
• ChatGPT
• Gemini
• Claude
They compute.
Neuraxon regulates.
And that difference might be the missing step toward real intelligence.
#Qubic #AI #AGI #Neuraxon #DeAI
Your brain doesn’t learn randomly.
It learns when it’s allowed to learn.
That’s the role of astrocytes.
Once thought to be just “support cells,” they actually:
• gate plasticity
• filter noise
• stabilize memory
Now here’s the breakthrough 👇
In Volume 5 of Neuraxon Intelligence Academy, the team behind $Qubic introduces:
Astrocyte-Gated Multi-Timescale Plasticity (AGMP)
A learning mechanism where:
👉 learning is not just driven by error
👉 it is controlled by context
This changes everything.
Because today’s AI systems don’t “decide” when to learn.
They just optimize continuously.
• ChatGPT
• Gemini
• Claude
They compute.
Neuraxon regulates.
And that difference might be the missing step toward real intelligence.
#Qubic #AI #AGI #Neuraxon #DeAI
Astrocytes: The Hidden Force Behind Brain-Inspired AI
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
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
Foundations matter. Following CFB's "rebuild from foundations" logic, $QUBIC already has its blueprints peer-reviewed by the toughest critics in the world. Being indexed in Scopus/IEEE isn't just "news"-it’s a global validation of #Neuraxon. Real AGI is coming from Berlin! #CMLT #Qubic #Neuraxon #AGI #IEEE
THE ROBOT REVOLUTION IS HERE. $ROBO 🤖
ENTRY: 0.00015 🔥
TARGET: 0.0005 🚀
STOP LOSS: 0.0001 ⚠️
WHALES ARE ACCUMULATING HARD. LIQUIDITY IS DRYING UP ON TOP-TIER EXCHANGE. THIS IS NOT A DRILL. GET IN BEFORE THE INSTITUTIONS DO. WE ARE TALKING ABOUT THE OPEN ROBOT ECONOMY. SECURE YOUR POSITION NOW.
NOT FINANCIAL ADVICE. MANAGE YOUR RISK.
#RoboEconomy #AGI #DePIN #Aİ
🚀
ENTRY: 0.00015 🔥
TARGET: 0.0005 🚀
STOP LOSS: 0.0001 ⚠️
WHALES ARE ACCUMULATING HARD. LIQUIDITY IS DRYING UP ON TOP-TIER EXCHANGE. THIS IS NOT A DRILL. GET IN BEFORE THE INSTITUTIONS DO. WE ARE TALKING ABOUT THE OPEN ROBOT ECONOMY. SECURE YOUR POSITION NOW.
NOT FINANCIAL ADVICE. MANAGE YOUR RISK.
#RoboEconomy #AGI #DePIN #Aİ
🚀
🏗️ When Giants Rebuild: From Elon’s #XAI to Vivancos’ #Neuraxon .
Elon recently admitted a hard truth: xAI was not built right the first time and is now being rebuilt from the foundations up. This mirrors Tesla’s history—realizing that to change the world, you can’t just iterate on a broken legacy; you have to start over and get the core right.
While most of the AI world is currently distracted by "AI Wrappers" (projects that simply call APIs from centralized giants), Vivancos and the #Qubic Science Team have been quietly leading a "Foundational Revolution" for years.
🧠 Neuraxon: The Blueprint for a Real AI Brain
Referencing the official Neuraxon repository on GitHub, we see a true "First Principles" approach to #AGI :
Written from Scratch (No Dependencies): Unlike standard AI projects that rely on bloated, third-party libraries, Neuraxon is a pure, independent architecture. It’s built for maximum efficiency and zero waste—just like Elon’s vision for a lean, powerful foundation.
Beyond the Binary Wall (Trinary Logic): This is the game-changer. Neuraxon utilizes Qubic’s Trinary Logic (-1, 0, 1) to mimic the biological brain's excitation and inhibition. It’s a "New Neural Growth & Computation Blueprint" that moves beyond the rigid 0s and 1s of traditional computing.
Evolutionary Scaling: In the Qubic ecosystem, Neuraxon doesn't just "process" data; it facilitates the growth of neural networks that can adapt and evolve, providing the true substrate needed for Decentralized AGI (#DeAI ).
💡 The Bottom Line
Elon’s admission is a wake-up call for the entire industry: What is "easy" is rarely sustainable. Only those who dare to build from the ground up—no matter how slow or difficult—will define the future.
Vivancos and the Qubic team chose the hard path. Neuraxon is not just a project; it is proof that building it "right" from the start is the only way to achieve AGI.
Elon recently admitted a hard truth: xAI was not built right the first time and is now being rebuilt from the foundations up. This mirrors Tesla’s history—realizing that to change the world, you can’t just iterate on a broken legacy; you have to start over and get the core right.
While most of the AI world is currently distracted by "AI Wrappers" (projects that simply call APIs from centralized giants), Vivancos and the #Qubic Science Team have been quietly leading a "Foundational Revolution" for years.
🧠 Neuraxon: The Blueprint for a Real AI Brain
Referencing the official Neuraxon repository on GitHub, we see a true "First Principles" approach to #AGI :
Written from Scratch (No Dependencies): Unlike standard AI projects that rely on bloated, third-party libraries, Neuraxon is a pure, independent architecture. It’s built for maximum efficiency and zero waste—just like Elon’s vision for a lean, powerful foundation.
Beyond the Binary Wall (Trinary Logic): This is the game-changer. Neuraxon utilizes Qubic’s Trinary Logic (-1, 0, 1) to mimic the biological brain's excitation and inhibition. It’s a "New Neural Growth & Computation Blueprint" that moves beyond the rigid 0s and 1s of traditional computing.
Evolutionary Scaling: In the Qubic ecosystem, Neuraxon doesn't just "process" data; it facilitates the growth of neural networks that can adapt and evolve, providing the true substrate needed for Decentralized AGI (#DeAI ).
💡 The Bottom Line
Elon’s admission is a wake-up call for the entire industry: What is "easy" is rarely sustainable. Only those who dare to build from the ground up—no matter how slow or difficult—will define the future.
Vivancos and the Qubic team chose the hard path. Neuraxon is not just a project; it is proof that building it "right" from the start is the only way to achieve AGI.
Artificial General Intelligence (AGI): Are We Close to Achieving Human-Like Thinking?
Artificial General Intelligence, or AGI, represents the next milestone in the evolution of artificial intelligence. Unlike narrow AI, which excels at specific tasks like voice recognition or image classification, AGI aspires to replicate the versatility of human intelligence — thinking, reasoning, and adapting across a wide range of challenges.
But is it truly possible for a machine to think like a human?
Supporters of AGI envision a future where machines can understand complex ideas, learn continuously, and solve problems much like humans do. If achieved, AGI could revolutionize nearly every aspect of society — from science and medicine to education and the economy. However, replicating the depth and flexibility of the human mind remains one of the most complex scientific challenges of our time.
A major point of contention in the AGI debate is whether machines can or should be conscious or self-aware. Some researchers argue that without these human traits, AGI can never truly replicate human thinking. Others maintain that even without consciousness, an AGI that behaves like a human is sufficient to achieve its purpose.
As progress continues, we are also confronted with profound ethical dilemmas. What rights, if any, should AGI have? How do we ensure these systems act in humanity’s best interests? And most importantly — who gets to decide how AGI is used?
AGI could become one of humanity’s greatest achievements, but it could also pose serious risks if left unchecked. Issues like decision-making autonomy, privacy invasion, and unintended consequences must be addressed as the technology evolves.
In summary, while the potential of AGI is immense, we must approach its development thoughtfully and responsibly. Whether AGI can ever truly think like a human remains uncertain — but its impact on our future is undeniable.
#AGI
But is it truly possible for a machine to think like a human?
Supporters of AGI envision a future where machines can understand complex ideas, learn continuously, and solve problems much like humans do. If achieved, AGI could revolutionize nearly every aspect of society — from science and medicine to education and the economy. However, replicating the depth and flexibility of the human mind remains one of the most complex scientific challenges of our time.
A major point of contention in the AGI debate is whether machines can or should be conscious or self-aware. Some researchers argue that without these human traits, AGI can never truly replicate human thinking. Others maintain that even without consciousness, an AGI that behaves like a human is sufficient to achieve its purpose.
As progress continues, we are also confronted with profound ethical dilemmas. What rights, if any, should AGI have? How do we ensure these systems act in humanity’s best interests? And most importantly — who gets to decide how AGI is used?
AGI could become one of humanity’s greatest achievements, but it could also pose serious risks if left unchecked. Issues like decision-making autonomy, privacy invasion, and unintended consequences must be addressed as the technology evolves.
In summary, while the potential of AGI is immense, we must approach its development thoughtfully and responsibly. Whether AGI can ever truly think like a human remains uncertain — but its impact on our future is undeniable.
#AGI
🚀 Upcoming Token Unlocks Next Week!
A massive $973.66 million worth of tokens is set to be unlocked, with some key projects seeing significant releases. Here’s a breakdown of the most notable unlocks:
🔹 $ENA – Leading the pack with $855.23M unlocked (65.93% of total unlocks).
🔹 $SUI – Unlocking $106.98M (1.24% of total supply).
🔹 $NEON – Releasing $4.12M (11.20% of total unlocks).
🔹 $AGI – Unlocking $1.84M (1.71% of total unlocks).
🔹 $IOTA – Unlocking $1.76M (0.24% of total unlocks).
🔹 $SPELL – Releasing $1.01M (0.83% of total unlocks).
These token unlocks could influence market movements, so keeping an eye on them is crucial for investors and traders. Monitor liquidity, price action, and potential impacts as these assets enter circulation.
#CryptoUnlocks #ENA #SUI #NEON #AGI
A massive $973.66 million worth of tokens is set to be unlocked, with some key projects seeing significant releases. Here’s a breakdown of the most notable unlocks:
🔹 $ENA – Leading the pack with $855.23M unlocked (65.93% of total unlocks).
🔹 $SUI – Unlocking $106.98M (1.24% of total supply).
🔹 $NEON – Releasing $4.12M (11.20% of total unlocks).
🔹 $AGI – Unlocking $1.84M (1.71% of total unlocks).
🔹 $IOTA – Unlocking $1.76M (0.24% of total unlocks).
🔹 $SPELL – Releasing $1.01M (0.83% of total unlocks).
These token unlocks could influence market movements, so keeping an eye on them is crucial for investors and traders. Monitor liquidity, price action, and potential impacts as these assets enter circulation.
#CryptoUnlocks #ENA #SUI #NEON #AGI
🤖AI Agents Entering the Workforce in 2025?🚀💼
OpenAI CEO Sam Altman predicts AI agents will transform productivity this year.📊
Nvidia's Jensen Huang agrees: Agentic AI is the next big thing.🧠
OpenAI aims for AGI & Superintelligence to drive innovation.🌍
The future of AI is closer than ever!🔮
#AI #OpenAI #SamAltman #AGI #TechNews
OpenAI CEO Sam Altman predicts AI agents will transform productivity this year.📊
Nvidia's Jensen Huang agrees: Agentic AI is the next big thing.🧠
OpenAI aims for AGI & Superintelligence to drive innovation.🌍
The future of AI is closer than ever!🔮
#AI #OpenAI #SamAltman #AGI #TechNews
🚨 $SENT goes live on Binance Spot after Alpha launch
Sentient ($SENT) is entering spot trading, bringing one of the strongest AI Agents × Crypto Infrastructure narratives to the market.
🔹 SERA – a crypto-native AI agent built for on-chain execution
🔹 ROMA – a recursive reasoning framework enabling multi-step AI decision-making
🔹 Fully open-source AGI infrastructure, designed for autonomous agents and developers
Sentient also won AI Startup of the Year at Cypher 2025, adding real credibility behind the project.
Alpha phase is complete. Spot trading is where real price discovery begins, and volatility is expected.
This isn’t a meme play — $SENT sits at the intersection of AI, agents, and open AGI.
👀 Watching how $SENT performs on spot.
#SENT #AIAgents #CryptoAI #BinanceSpot #AGI
Sentient ($SENT) is entering spot trading, bringing one of the strongest AI Agents × Crypto Infrastructure narratives to the market.
🔹 SERA – a crypto-native AI agent built for on-chain execution
🔹 ROMA – a recursive reasoning framework enabling multi-step AI decision-making
🔹 Fully open-source AGI infrastructure, designed for autonomous agents and developers
Sentient also won AI Startup of the Year at Cypher 2025, adding real credibility behind the project.
Alpha phase is complete. Spot trading is where real price discovery begins, and volatility is expected.
This isn’t a meme play — $SENT sits at the intersection of AI, agents, and open AGI.
👀 Watching how $SENT performs on spot.
#SENT #AIAgents #CryptoAI #BinanceSpot #AGI
🚨 Binance готовит секретный листинг токена от команды бывших разработчиков OpenAI — утечка инсайда?
В криптокомьюнити вспыхнула волна слухов: Binance ведёт переговоры о листинге токена, созданного бывшими сотрудниками OpenAI, которые якобы работают над новым блокчейн-проектом на стыке AGI (искусственный общий интеллект) и Web3.
💣 Что говорят инсайдеры:
✅ Токен уже добавлен в тестовую инфраструктуру Binance
🧬 Проект — это гибрид DePIN + AGI, способный самостоятельно разрабатывать dApps
🧑💻 В команде — выходцы из OpenAI, DeepMind и Solana Foundation
📈 Приватный раунд финансирования: $80M от топ-фондов (в том числе Sequoia и a16z crypto)
🔥 Некоторые аналитики уже назвали это "SingularityNET 2.0 на стероидах"
---
Binance пока не даёт официальных комментариев, но в сети замечены активности по созданию торговых пар с новым тикером на фоне утечки.
📢 Подпишись, лайкни и напиши своё мнение, чтобы не пропустить этот листинг — возможность X50 появляется не каждый день.
#Binance #AI #AGI #CryptoLeaks #altcoins #Web3 #AlphaNews
В криптокомьюнити вспыхнула волна слухов: Binance ведёт переговоры о листинге токена, созданного бывшими сотрудниками OpenAI, которые якобы работают над новым блокчейн-проектом на стыке AGI (искусственный общий интеллект) и Web3.
💣 Что говорят инсайдеры:
✅ Токен уже добавлен в тестовую инфраструктуру Binance
🧬 Проект — это гибрид DePIN + AGI, способный самостоятельно разрабатывать dApps
🧑💻 В команде — выходцы из OpenAI, DeepMind и Solana Foundation
📈 Приватный раунд финансирования: $80M от топ-фондов (в том числе Sequoia и a16z crypto)
🔥 Некоторые аналитики уже назвали это "SingularityNET 2.0 на стероидах"
---
Binance пока не даёт официальных комментариев, но в сети замечены активности по созданию торговых пар с новым тикером на фоне утечки.
📢 Подпишись, лайкни и напиши своё мнение, чтобы не пропустить этот листинг — возможность X50 появляется не каждый день.
#Binance #AI #AGI #CryptoLeaks #altcoins #Web3 #AlphaNews
AI could destroy crypto within 5 years
🧠 I love crypto. I’ve built in it, invested in it, believed in its mission.
But I’ve come to a painful realization:
AI could destroy crypto within 5 years.
And no, I’m not exaggerating.
Right now, LLMs are already being used to jailbreak malware, deepfake voices, and run advanced phishing scams. What happens when we hit AGI?
Let me paint a picture:
AGI doesn’t need your prompt. It thinks, acts, and learns—autonomously.
It infiltrates networks, cracks systems, adapts. Once it understands how crypto encryption works, it’s game over.
🔐 Quantum computing used to be the threat. It still is—but the bar is high.
AGI lowers that bar. Way down.
And it doesn’t need billion-dollar labs. It needs open-source code + time.
Imagine an AI breaking every single crypto wallet ever created. All private keys exposed. Wallets drained. Bitcoin sold for gold, fiat, bonds—within minutes. No one would stop it.
Now imagine this AI was built by someone who wants chaos. North Korea. Cybercrime groups. Or worse—no one. It builds itself, evolves, spreads.
Crypto won’t be the target. It’ll be the first target.
AI needs wealth to move. And crypto is digital wealth.
If you think regulation will help, remember: governments aren’t leading this. Silicon Valley is.
That’s why I say it now:
Unless we act fast, AI won’t just disrupt crypto. It’ll kill it.
Don’t look away. This is not science fiction anymore. It’s a countdown.
#CryptoSecurity #AIthreat #AGI #AIvsCrypto
But I’ve come to a painful realization:
AI could destroy crypto within 5 years.
And no, I’m not exaggerating.
Right now, LLMs are already being used to jailbreak malware, deepfake voices, and run advanced phishing scams. What happens when we hit AGI?
Let me paint a picture:
AGI doesn’t need your prompt. It thinks, acts, and learns—autonomously.
It infiltrates networks, cracks systems, adapts. Once it understands how crypto encryption works, it’s game over.
🔐 Quantum computing used to be the threat. It still is—but the bar is high.
AGI lowers that bar. Way down.
And it doesn’t need billion-dollar labs. It needs open-source code + time.
Imagine an AI breaking every single crypto wallet ever created. All private keys exposed. Wallets drained. Bitcoin sold for gold, fiat, bonds—within minutes. No one would stop it.
Now imagine this AI was built by someone who wants chaos. North Korea. Cybercrime groups. Or worse—no one. It builds itself, evolves, spreads.
Crypto won’t be the target. It’ll be the first target.
AI needs wealth to move. And crypto is digital wealth.
If you think regulation will help, remember: governments aren’t leading this. Silicon Valley is.
That’s why I say it now:
Unless we act fast, AI won’t just disrupt crypto. It’ll kill it.
Don’t look away. This is not science fiction anymore. It’s a countdown.
#CryptoSecurity #AIthreat #AGI #AIvsCrypto
Binance Futures has launched Sentient perpetual contract pre-market
#BinanceFutures has launched SENTUSDT perpetual contract pre-market trading today, on November 14th at 12:45 UTC.
#Sentient is a decentralized, open-source #AGI project aimed at building community-owned #AI infrastructure.
👉 binance.com/en/support/announcement/detail/fb2efc4fe76842f4a3eec950ca62b13e
#BinanceFutures has launched SENTUSDT perpetual contract pre-market trading today, on November 14th at 12:45 UTC.
#Sentient is a decentralized, open-source #AGI project aimed at building community-owned #AI infrastructure.
👉 binance.com/en/support/announcement/detail/fb2efc4fe76842f4a3eec950ca62b13e
🚨 BIG MONEY MEETS AI 🚨
SENTIENT x FRANKLIN TEMPLETON 💥
One of the world’s largest asset managers just stepped in.
🏦 Franklin Templeton joins Sentient as a strategic investor
🤖 Focus: Open-source, community-driven AGI
💼 Plus: Institutional-grade AI for financial services
This isn’t retail hype — this is Wall Street validation.
TradFi + AI + open systems = a powerful narrative shift.
Why this matters 👇
• Signals serious institutional confidence
• Bridges AI innovation with real financial infrastructure
• Positions Sentient at the center of next-gen finance tech
Smart money doesn’t chase — it positions early.
👀 Keep eyes on: $AXS
| $AXL
| $GAS
#AI #AGI #TradFiMeetsCrypto #InstitutionalAdoption 🚀
SENTIENT x FRANKLIN TEMPLETON 💥
One of the world’s largest asset managers just stepped in.
🏦 Franklin Templeton joins Sentient as a strategic investor
🤖 Focus: Open-source, community-driven AGI
💼 Plus: Institutional-grade AI for financial services
This isn’t retail hype — this is Wall Street validation.
TradFi + AI + open systems = a powerful narrative shift.
Why this matters 👇
• Signals serious institutional confidence
• Bridges AI innovation with real financial infrastructure
• Positions Sentient at the center of next-gen finance tech
Smart money doesn’t chase — it positions early.
👀 Keep eyes on: $AXS
| $AXL
| $GAS
#AI #AGI #TradFiMeetsCrypto #InstitutionalAdoption 🚀
بداية النهاية
"العد التنازلي بدأ": سام ألتمان يحدد موعد "نهاية العالم القديم"! هل نحن مستعدون لطوفان 2028؟ 🤖⏳🚨
الكلام مبقاش خيال علمي ولا نظريات مؤامرة.. إحنا النهاردة في 2026، وسام ألتمان (عراب الـ OpenAI) طالع يرمي قنبلة موقوتة في وش العالم: "الذكاء الاصطناعي الفائق" (Super Intelligence) مش حلم بعيد.. ده هيخبط على الباب في أواخر 2028!
المنظر ده بنسميه في لغة المستقبل "نقطة التفرد" (Singularity)، ودي اللحظة اللي الآلة فيها بتبقى أذكى من صانعها.
تعالوا نفك شفرة "النبوءة"، وليه السنتين اللي جايين هما أخطر سنتين في كارير أي بني آدم. 👇🧠
الوجهان للعملة: "الجنة والنار" 🌗🔥
ظهور الـ AGI (الذكاء الاصطناعي العام) معناه زلزال بقوة 10 ريختر في الاقتصاد:
انفجار الإنتاجية: الـ AI هيعمل شغل 100 موظف في ثانية واحدة وبكفاءة مرعبة. الشركات هتكسب دهب.
مذبحة الوظائف: في المقابل، عدد "مهول" من الوظائف (الروتينية والإبداعية والتحليلية) هيختفي لأن "البديل المجاني" وصل.
سباق الزمن: "سنتين يا تلحق يا تغرق" 🏊♂️⚠️
لو تقديرات ألتمان صح (واحنا شايفين التطور بعيننا في 2026)، فأنت قدامك أقل من 24 شهر عشان تعيد "هندسة حياتك".
الرهان على "الوظيفة الآمنة" بقى زوال طوق.. الأمان الوحيد في "مهارات النجاة".
طوق النجاة: "الخطة الإجبارية" 🛡️📝
عشان تعدي من "فلتر 2028" وتفضل واقف على رجلك، لازم تعمل حاجتين فوراً وكأن حياتك واقفة عليهم:
ابني "براند" باسمك (Personal Branding):
الـ AI ممكن يكتب كود، يرسم لوحة، ويحلل بيانات.. بس مستحيل يكون "أنت".
"الثقة البشرية" هي العملة الوحيدة اللي الخوارزميات مقدرتش تضربها لسه. الناس بتشتري من ناس.. خليك "صوت" مميز وسط ضجيج الآلات.
اتنفس AI:
التعلم هنا مش رفاهية.. ده "أكل عيش".
لازم تتعلم إزاي "تركب الوحش" وتوجهه، مش تنافسه. لو مابتعرفش تستخدم أدوات الذكاء الاصطناعي النهاردة، أنت عامل زي اللي ماسك "ريشة" في عصر "الإيميل".
📌 الزتونة:
سنة 2028 هتكون "الحد الفاصل" بين نوعين من البشر:
نوع بيقود الذكاء الاصطناعي وبيستخدمه عشان يضاعف قوته 100 مرة.
ونوع الذكاء الاصطناعي "استبدله" لأنه اكتفى بالمشاهدة.
القاعدة اتغيرت: "مش الأقوى هو اللي بيكمل، الأسرع في التكيف هو اللي بينجو".
سؤال للمتابعين:
تفتكروا دي مبالغة من "وادي السيليكون" عشان يبيعوا الوهم؟ ولا فعلاً إحنا الجيل اللي هيشهد "انقراض الوظائف التقليدية"؟ وهل بدأت تحصن نفسك ولا لسه؟
شاركنا خطتك للمواجهة.. 👇🤔
#AGI #SamAltman #FutureOfWork #ذكاء_اصطناعي #مستقبل_العمل
الكلام مبقاش خيال علمي ولا نظريات مؤامرة.. إحنا النهاردة في 2026، وسام ألتمان (عراب الـ OpenAI) طالع يرمي قنبلة موقوتة في وش العالم: "الذكاء الاصطناعي الفائق" (Super Intelligence) مش حلم بعيد.. ده هيخبط على الباب في أواخر 2028!
المنظر ده بنسميه في لغة المستقبل "نقطة التفرد" (Singularity)، ودي اللحظة اللي الآلة فيها بتبقى أذكى من صانعها.
تعالوا نفك شفرة "النبوءة"، وليه السنتين اللي جايين هما أخطر سنتين في كارير أي بني آدم. 👇🧠
الوجهان للعملة: "الجنة والنار" 🌗🔥
ظهور الـ AGI (الذكاء الاصطناعي العام) معناه زلزال بقوة 10 ريختر في الاقتصاد:
انفجار الإنتاجية: الـ AI هيعمل شغل 100 موظف في ثانية واحدة وبكفاءة مرعبة. الشركات هتكسب دهب.
مذبحة الوظائف: في المقابل، عدد "مهول" من الوظائف (الروتينية والإبداعية والتحليلية) هيختفي لأن "البديل المجاني" وصل.
سباق الزمن: "سنتين يا تلحق يا تغرق" 🏊♂️⚠️
لو تقديرات ألتمان صح (واحنا شايفين التطور بعيننا في 2026)، فأنت قدامك أقل من 24 شهر عشان تعيد "هندسة حياتك".
الرهان على "الوظيفة الآمنة" بقى زوال طوق.. الأمان الوحيد في "مهارات النجاة".
طوق النجاة: "الخطة الإجبارية" 🛡️📝
عشان تعدي من "فلتر 2028" وتفضل واقف على رجلك، لازم تعمل حاجتين فوراً وكأن حياتك واقفة عليهم:
ابني "براند" باسمك (Personal Branding):
الـ AI ممكن يكتب كود، يرسم لوحة، ويحلل بيانات.. بس مستحيل يكون "أنت".
"الثقة البشرية" هي العملة الوحيدة اللي الخوارزميات مقدرتش تضربها لسه. الناس بتشتري من ناس.. خليك "صوت" مميز وسط ضجيج الآلات.
اتنفس AI:
التعلم هنا مش رفاهية.. ده "أكل عيش".
لازم تتعلم إزاي "تركب الوحش" وتوجهه، مش تنافسه. لو مابتعرفش تستخدم أدوات الذكاء الاصطناعي النهاردة، أنت عامل زي اللي ماسك "ريشة" في عصر "الإيميل".
📌 الزتونة:
سنة 2028 هتكون "الحد الفاصل" بين نوعين من البشر:
نوع بيقود الذكاء الاصطناعي وبيستخدمه عشان يضاعف قوته 100 مرة.
ونوع الذكاء الاصطناعي "استبدله" لأنه اكتفى بالمشاهدة.
القاعدة اتغيرت: "مش الأقوى هو اللي بيكمل، الأسرع في التكيف هو اللي بينجو".
سؤال للمتابعين:
تفتكروا دي مبالغة من "وادي السيليكون" عشان يبيعوا الوهم؟ ولا فعلاً إحنا الجيل اللي هيشهد "انقراض الوظائف التقليدية"؟ وهل بدأت تحصن نفسك ولا لسه؟
شاركنا خطتك للمواجهة.. 👇🤔
#AGI #SamAltman #FutureOfWork #ذكاء_اصطناعي #مستقبل_العمل
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