Artificial Evolution Research Institute (AERI)
Challenge to immortality
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Strategic Research Initiative by the Artificial Evolution Research Institute and Xyronix
BioBrain
The Apex of Synthetic Evolution in Human Evolutionary Trajectory — A Convergence of Advanced Neuroengineering, Computational Neuroscience, and Biomedical AI for Cognitive Augmentation and Artificial Neurogenesis
Overview
A comprehensive exploration of Biobrain as the pinnacle of engineered evolution, highlighting its significance in the context of human advancement.
Objectives
• Redefining human potential through cutting-edge technology.
• Enhancing cognitive capabilities and neuroplasticity.
Key Components
1. Advanced Neuroengineering
• Innovations in neuroprosthetics.
• Development of brain-machine interfaces.
2. Computational Neuroscience
• Application of artificial intelligence in understanding brain functions.
• Techniques for modeling and simulating neural processes.
3. Biomedical AI
• Integration of AI to enhance cognitive augmentation.
• Use of AI in artificial neurogenesis.
Conclusion
The Institute of Artificial Evolution and Xyronix have launched a strategic research initiative centered on Biobrain, aiming to achieve the pinnacle of engineered evolution in human history. This project leverages cutting-edge neuroprosthetics, synthetic neurogenomics, and autonomous cognitive architectures to expand human potential. Through integrated biomedical AI, high-fidelity brain-machine interfacing, and artificial synaptogenesis, Biobrain seeks to enable unprecedented levels of neuroplasticity and cognitive enhancement. Biobrain represents a transformative approach to human evolution, merging technology and biology for unprecedented cognitive enhancement.
1. the Biobrain differs fundamentally from conventional fifth-generation silicon-based computers by adopting a Brain-AI Computer architecture that combines organic materials and cells, and in some cases even neural cells (neurons), to comprehensively encompass human intellectual and cognitive functions such as learning, cognition, judgment, memory, control, and perception in a way that closely resembles natural processes.
2. the Biobrain technology aims to be applied in fields such as medicine and robotics—particularly for robotic armies, robot soldiers, combat robots, machine troops, robotic soldiers, and unmanned weaponry, including unmanned tanks, unmanned snipers, unmanned aircraft carriers, unmanned battleships, and unmanned fighter jets—and in the long term, to supplement and enhance human intellectual functions, including learning, cognition, judgment, memory, control, and perception. As such systems mature, they are expected to achieve a level of ultimate, omnipotent intelligence that is as flexible and efficient as human intelligence or even surpasses humanity, far beyond the capabilities of current AI.
The sixth-generation computer (biocomputer), constructed by integrating these technologies into a Brain-AI Computer architecture, is designed to fully mimic human intellectual and cognitive activities, such as learning, cognition, judgment, memory, perception, and control. It also envisions the potential for direct connection to the human brain through our brain-machine interface (BMI). In addition to expected applications in medicine and robotics, the Biobrain aims to supplement and enhance human intellectual functions, ultimately aspiring to achieve an intelligent life form with capabilities that surpass human intelligence.
the Biobrain, currently under research and development by the General Incorporated Association of Artificial Evolution Laboratory and Xyronix Corporation, represents an uncharted and extreme research frontier. It embodies the concept of a biocomputer, referring to our artificial "brain" or intelligent system (intelligent life form) designed by integrating biological elements. This research encompasses several areas: (１)neuromorphic engineering, which involves designing circuits that mimic the synaptic and neuronal functions of neural networks based on the structural architecture of biological neural cells, aiming to replicate the network structure of neurons and synapses. (２)Cultured neural circuits, a technique that cultivates small-scale “brains” using actual neural cells, allowing for the realization of specific pattern recognition and learning capabilities that mirror functions found in biological brains. (３)molecular computing, which involves the synthetic generation of biological molecules, such as DNA and proteins, to perform logical computations and data storage. These biological molecules are integrated with the brain through our brain-machine interface (BMI) or Brain-Implanted Machine Interface, serving as the logical components of a Brain-AI Computer architecture. This approach enables computations within significantly smaller spaces than fifth-generation computers, allowing for ultra-high-density information processing. Through foundational technologies drawn from brain science, biotechnology, and biological processes, the Biobrain aims to create sixth-generation computers and systems, or biocomputers, that replicate the full functionality of the human brain.
B. The "Biobrain," jointly developed by the General Incorporated Association of Artificial Evolution Laboratory and Xyronix Corporation, is a project aimed at addressing uncharted and extreme technological challenges, aspiring to implement an advanced intelligent system (intelligent life form) as a biocomputer. This system seeks to surpass conventional silicon-based computer architectures, drawing on fields such as bionics, neuromorphic engineering, biomolecular computing (molecular computing), bioinformatics, molecular biology, and synthetic biology, with the goal of constructing a sixth-generation intelligent system (intelligent life form) that integrates these disciplines. This approach marks a significant leap from traditional silicon-based computer architectures, adopting a unique methodology that leverages state-of-the-art bio-process control technologies, including neuromorphic computing, molecular-level memory storage, and bio-computational engineering.
It is composed of the following three core technologies, which synergize to enable the mimicry of biological intelligence:
1. neuromorphic engineering: Based on the synaptic plasticity of neural cells and the spiking dynamics of neurons, this technology constructs deep neural systems, dynamic models of action potentials, and neuron actuation control. This approach enables high-fidelity replication of synaptic strengthening mechanisms within the brain, facilitating the development of self-adaptive Spiking Neural Networks (SNNs). Additionally, it includes a Neuro-Processing Unit (NPU) designed through analog-digital hybrid circuit design, which mimics both electrical and chemical synapse characteristics. By leveraging the principles of synaptic plasticity and neuronal dynamics, it builds circuits that accurately replicate neural information transmission and signal processing in the brain through neuro-simulation models and neuro-digital analog conversions. This method, utilizing the aforementioned SNN technology, achieves data processing and self-learning capabilities in ways that differ fundamentally from traditional digital processing.
2. In Vitro Neural Network: Utilizing biological neural cells, this technology cultivates small-scale "brains" through neuron branching modeling, synaptic super-resolution imaging, and artificial synapse construction. This process involves the formation of self-organizing networks mediated by neurotrophic factors and electrical stimulation patterns, employing a biological modulation system to develop pattern recognition and reinforcement learning capabilities. This enables the realization of a neural adaptation system that surpasses biological brains, thus evolving the learning functions of the Biobrain. Additionally, small-scale "brains" are cultivated based on actual neural cells, reproducing synaptic connection structures and synaptic transmission while endowing them with pattern recognition and adaptive learning abilities. This technology aims to promote the self-growth and self-modification of neural circuit networks in the culture environment through the use of bioactive substances such as Nerve Growth Factor (NGF) and Brain-Derived Neurotrophic Factor (BDNF), striving to replicate behaviors that are remarkably close to those of biological brains.
3. molecular computing: This technology utilizes biomolecular materials such as DNA, proteins, and RNA to assemble ultra-miniature information processing mechanisms using nucleic acid-based logic circuits and bio-molecular transistors alongside organic transistors. The molecular computing technology employs nucleic acid sequencing logic gates and biomolecular calibration, leveraging quantum dot synthesis and micro-bioengineering to enable ultra-high-density information processing and the storage of epigenetic memory at the molecular scale.
Furthermore, ultra-miniature information processing mechanisms are constructed using biomolecular materials such as DNA, proteins, and RNA, along with nucleic acid-based logic circuits and bio-molecular transistors in conjunction with organic transistors. By employing nucleic acid sequencing logic gates, biomolecular calibration, quantum dot synthesis, and micro-bioengineering, this technology enables ultra-high-density information processing and the storage of epigenetic memory at the molecular scale.
Additionally, a micro-bio-processor that combines DNA nanotechnology and biological logic gates is employed, utilizing logical computation and information storage technologies based on biomaterials such as DNA and proteins. This approach achieves ultra-high-density data processing capabilities that surpass traditional semiconductor transistor technology, resulting in molecular switching circuits that are independent of silicon circuits. This molecular computing technology enables nanoscale data manipulation and ultra-parallel computing, maximizing computational capabilities in significantly smaller spaces compared to fifth-generation computers.
Through molecular computing technology and organic semiconductor technology, our molecular operating system (mOS) has been realized, enabling computational processing at the molecular scale and constructing computational units that transcend traditional transistor technology. The concept of the molecular operating system (mOS) is implemented, resulting in molecular-level computational units with information processing capabilities that surpass conventional silicon-based transistor technology.
By integrating these elements, Biobrain adopts a Brain-AI Computer architecture. This architecture allows for connection to the biological brain through our brain-machine interface (BMI) capable of processing and analyzing brain waves and neural signals. By incorporating biological signal processing and neural network synapse reconstruction, it comprehensively covers human intelligence activities such as learning, cognition, judgment, memory, perception, and control, and is considered to possess functions equal to or surpassing those of the human brain.
Furthermore, the application scope of Biobrain technology extends to neuroprosthetics in the medical field, autonomous robotic arms, autonomous weapon systems, and even the enhancement and supplementation of human executive functions. As a long-term goal, it aims to achieve superintelligence by constructing an ultimate cognitive architecture that possesses flexibility and efficiency surpassing those of the human brain, thus aspiring to reach the pinnacle of intelligence.
Moreover, the sixth-generation computer (biocomputer) constructed based on the aforementioned Brain-AI Computer architecture aims to fully mimic the intelligence and cognitive activities of the human brain, such as learning, cognition, judgment, memory, perception, and control, while also considering our brain-machine interface (BMI) that can connect directly to the human brain. Biobrain is not only anticipated to have applications in medicine and robotics but also enables the supplementation and enhancement of human intellectual functions, ultimately aspiring to realize an intelligence and intelligent life form that surpasses human capabilities.
C. the Biobrain (Biobrain) project, a collaboration between the General Incorporated Association for Artificial Evolution Research Institute (AERI) and Xyronix Corporation, aims to integrate cutting-edge technologies in bioinformatics, molecular biology, and synthetic biology to construct a sixth-generation intelligent system (intelligent life form). Evolving from traditional silicon-based computer architectures, this project adopts a unique approach that utilizes advanced bioprocess control technologies, including neuromorphic computing, molecular-level memory storage, and biocomputational engineering.
The core technologies of this uncharted and extreme domain project consist of the following three components, each of which synergistically enables the complete imitation of biological intelligence:
1. neuromorphic engineering: This technology is based on the synaptic plasticity of neurons and the spiking dynamics of neurons, designing deep neural systems, dynamic models of action potentials, and neuron actuation control. This approach enables the high-fidelity reproduction of synaptic strengthening mechanisms within the brain, contributing to the construction of self-adaptive Spiking Neural Networks (SNNs). Additionally, it includes the neuroprocessing unit (NPU), which mimics the characteristics of both electrical and chemical synapses through the design of analog-digital hybrid circuits.
2. In Vitro Neural Network: This technology utilizes biological neural cells to cultivate small-scale "brains" through neuron branching modeling, super-resolution imaging of synapses, and the construction of artificial synapses. The process enables the creation of self-organizing networks through neurotrophic factors and the formation of electrical stimulation patterns, resulting in a biotic modulation system equipped with pattern recognition and reinforcement learning capabilities. This approach aims to replicate a neural adaptation system that exceeds the capabilities of biological brains, further evolving the learning functions of the Biobrain.
3. molecular computing: This technology constructs ultra-miniature information processing systems using biomolecular materials such as DNA, proteins, and RNA. By employing nucleic acid-based logic circuits, biolmolecular transistors, and organic transistors, it integrates techniques such as nucleic acid sequencing logic gates, biomolecular calibration, quantum dot synthesis, and micro-biotechnology. This approach facilitates ultra-high-density information processing at the molecular scale and the storage of epigenetic memory. As a result, it enables the realization of our molecular operating system (mOS) capable of computational processing at the molecular level, creating computational units that transcend traditional transistor technology.
our Biobrain system incorporates our brain-machine interface (BMI) composed of 100 billion computational units, with each synapse connected one-to-one to a CMOS structure of 100 billion biomolecular and organic semiconductor neural cells. This architecture is designed based on a neuro-architectural framework that facilitates the exchange and control of biological signals between the brain and sensory/motor neurons. It enables the optimization of the neural interface in real-time.
Moreover, our BMI architecture allows for information exchange with the biological brain through neuro-interface data links and neural signal control protocols. This comprehensive system supports a wide range of intelligence and cognitive activities, including memory formation, cognition, decision-making, motor control, and sensory processing, ensuring a holistic enhancement of human-like intelligence capabilities.
This technology is expected to be applied in various fields, including healthcare and robotics, focusing on neuroprosthetics, neurorehabilitation, and autonomous robotic systems (such as robotic arms and humanoid enhancements). The long-term goal is to introduce augmented intelligence and superintelligence architectures, ultimately constructing a flexible and highly efficient cognitive architecture that transcends human brain functions.
This advanced cognitive system aims to foster self-learning capabilities and perceptual reconstruction, leading to the creation of sophisticated intelligent systems (intelligent life forms) that surpass conventional human cognitive abilities. Through this integration of neurotechnology and robotics, we aim to enhance human capabilities and pave the way for revolutionary advancements in both medical and technological landscapes.
D. The integration of the three foundational technologies culminates in the Biobrain's Brain-AI Computer architecture. This architecture is equipped with advanced capabilities, including our Advanced Synaptic Reinforcement Algorithm and our Synaptic Plasticity Module, which significantly enhance the learning and adaptability of neural circuits.
The Advanced Synaptic Reinforcement Algorithm facilitates dynamic learning processes, allowing the system to refine its neural connections based on real-time feedback and experiences. Meanwhile, the Synaptic Plasticity Module mimics the natural processes of synaptic strengthening and weakening found in biological systems, enabling the Biobrain to adjust its neural pathways according to varying iNPUt and environmental stimuli.
Together, these components foster a highly adaptable and intelligent system capable of continuous learning and improvement, mirroring the complex functions of the human brain while offering enhanced efficiency and performance in various applications, including robotics, healthcare, and cognitive enhancement.
1. Biobrain is structured as our brain-machine interface (BMI), consisting of 100 billion operational units made up of biomolecular and organic semiconductor nerve cells, each connected one-to-one with CMOS structures. This design is based on our Neural Computing Architecture enabled by our BMI architecture.
This configuration facilitates the exchange and control of biological signals between the brain and sensory nerves, as well as between the brain and motor nerves, allowing for real-time optimization of the neural interface. Furthermore, our BMI architecture engages in information exchange with the biological brain through the Neuro Interface Data Link and neuro-signal control protocols.
This integration supports a wide range of cognitive functions, including memory formation, perception, decision-making, motor control, and sensory processing, providing comprehensive and cohesive assistance for all activities related to intelligence and cognition. the Biobrain's ability to enhance and streamline these processes represents a significant advancement in neurotechnology, bridging biological systems with computational capabilities.
2. Biobrain connects directly with the biological brain through our brain-machine interface (BMI), enabling bidirectional communication of biological information within the brain via the Neuro Interface Data Link and neuro-signal control protocols. This capability allows for comprehensive coverage of various cognitive functions, including memory formation, recognition, decision-making, motor control, and sensory processing.
By facilitating this intricate exchange of information, Biobrain contributes significantly to the realization of Neural Adaptive Intelligence, which enhances the brain's ability to adapt and respond to various stimuli and challenges in real time. This innovative approach positions Biobrain at the forefront of neurotechnology, merging biological intelligence with advanced computational systems.
3. The biocomputer, constructed as the 6th generation computer with the Brain-AI Computer architecture, aims to fully emulate human cognitive functions such as learning, cognition, judgment, memory, perception, and control. This architecture also considers the direct connection to the human brain through our brain-machine interface (BMI).
Biobrain not only has promising applications in the fields of medicine and robotics but also enhances and complements human intellectual capabilities. ultimately, it aspires to realize a form of intelligence that transcends human cognitive abilities, paving the way for the emergence of superintelligent entities. This vision positions Biobrain as a transformative technology with the potential to revolutionize our understanding of intelligence and its applications in various domains.
4.
1. the Biobrain technology is designed with applications in mind for both the medical and robotics fields, particularly focusing on unmanned weaponry, including:
(1) Robotic Armies
(2) Robotic Soldiers
(3) Combat Robots
(4) Mechanical Soldiers
(5) Robotic Military Personnel
(6) Unmanned Tanks
(7) Unmanned Drones
(8) Unmanned Aircraft Carriers
(9) Unmanned Battleships
(10) Unmanned Fighter Aircraft
This technology aims to enhance medical functionalities through neuroprosthetics and neurorehabilitation, enabling direct connections to the brain and facilitating bidirectional communication of neural signals. It is also expected to be applied to high-precision robotics in our unmanned weapon systems, as well as in robotic arms and humanoid enhancements.
In the long term, the goal is to implement augmented intelligence and superintelligence architectures to construct a flexible and efficient ultimate cognitive architecture that surpasses human brain capabilities. This will enable autonomous learning and perceptron reconfiguration in various situations, aiming for the creation of advanced intelligence systems (intelligent life forms).
This project ultimately seeks to complement and enhance human cognitive functions, with the aim of realizing intelligent life forms that transcend human intelligence.