�ݺ�ߣshows by User: ubix

�ݺ�ߣshows by User: ubix / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ubix / Sun, 12 Jan 2025 15:59:32 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ubix MOSS Hyperloop on-chain ETL platform for AGI /slideshow/moss-hyperloop-on-chain-etl-platform-for-agi/274820521 120translate20250112225229-250112155932-fade3a23
The document introduces the **Data Hyperloop**, an innovative data transmission technology inspired by the Hyperloop concept in transportation. Key aspects of the Data Hyperloop include: 1. **Technology Overview**: - Utilizes blockchain, cryptography, edge computing, and AI to establish secure, efficient, and closed-loop data transmission and storage systems. - Data is transmitted via encrypted capsules (DataCapsules) to edge nodes (Data EdgeStations), ensuring high security and efficient utilization. 2. **Advantages**: - **Data Integrity**: Blockchain ensures data cannot be cloned or copied. - **Security**: AI analyzes data reading/writing behavior to prevent leaks. - **Flexibility**: Reduces central data center load and enables decentralized, manageable point-to-point sharing. - **Efficiency**: Allows seamless integration of traditional applications into blockchain frameworks with one-click deployment. 3. **Applications**: - Designed for both private and public cloud deployments. - Supports SQL-based interactions while providing enhanced security through semantic-level data leakage prevention. 4. **Operational Features**: - Includes intelligent tools like Smart Data Hatch (SDH) for secure access to data. - Offers blockchain ETL engines for on-chain operations, ensuring traceability and authenticity. - Provides performance monitoring and regulatory insights through specialized dashboards. 5. **Use Cases**: - Facilitates secure inter-departmental data exchanges with granular access control. - Enhances collaboration efficiency while maintaining strict data privacy and integrity. The document underscores the transformative potential of Data Hyperloop in addressing inefficiencies in traditional data management systems, particularly for large-scale organizations. It combines advanced technologies to ensure secure, flexible, and efficient data sharing.]]>
The document introduces the **Data Hyperloop**, an innovative data transmission technology inspired by the Hyperloop concept in transportation. Key aspects of the Data Hyperloop include: 1. **Technology Overview**: - Utilizes blockchain, cryptography, edge computing, and AI to establish secure, efficient, and closed-loop data transmission and storage systems. - Data is transmitted via encrypted capsules (DataCapsules) to edge nodes (Data EdgeStations), ensuring high security and efficient utilization. 2. **Advantages**: - **Data Integrity**: Blockchain ensures data cannot be cloned or copied. - **Security**: AI analyzes data reading/writing behavior to prevent leaks. - **Flexibility**: Reduces central data center load and enables decentralized, manageable point-to-point sharing. - **Efficiency**: Allows seamless integration of traditional applications into blockchain frameworks with one-click deployment. 3. **Applications**: - Designed for both private and public cloud deployments. - Supports SQL-based interactions while providing enhanced security through semantic-level data leakage prevention. 4. **Operational Features**: - Includes intelligent tools like Smart Data Hatch (SDH) for secure access to data. - Offers blockchain ETL engines for on-chain operations, ensuring traceability and authenticity. - Provides performance monitoring and regulatory insights through specialized dashboards. 5. **Use Cases**: - Facilitates secure inter-departmental data exchanges with granular access control. - Enhances collaboration efficiency while maintaining strict data privacy and integrity. The document underscores the transformative potential of Data Hyperloop in addressing inefficiencies in traditional data management systems, particularly for large-scale organizations. It combines advanced technologies to ensure secure, flexible, and efficient data sharing.]]> Sun, 12 Jan 2025 15:59:32 GMT /slideshow/moss-hyperloop-on-chain-etl-platform-for-agi/274820521 ubix@slideshare.net(ubix) MOSS Hyperloop on-chain ETL platform for AGI ubix The document introduces the **Data Hyperloop**, an innovative data transmission technology inspired by the Hyperloop concept in transportation. Key aspects of the Data Hyperloop include: 1. **Technology Overview**: - Utilizes blockchain, cryptography, edge computing, and AI to establish secure, efficient, and closed-loop data transmission and storage systems. - Data is transmitted via encrypted capsules (DataCapsules) to edge nodes (Data EdgeStations), ensuring high security and efficient utilization. 2. **Advantages**: - **Data Integrity**: Blockchain ensures data cannot be cloned or copied. - **Security**: AI analyzes data reading/writing behavior to prevent leaks. - **Flexibility**: Reduces central data center load and enables decentralized, manageable point-to-point sharing. - **Efficiency**: Allows seamless integration of traditional applications into blockchain frameworks with one-click deployment. 3. **Applications**: - Designed for both private and public cloud deployments. - Supports SQL-based interactions while providing enhanced security through semantic-level data leakage prevention. 4. **Operational Features**: - Includes intelligent tools like Smart Data Hatch (SDH) for secure access to data. - Offers blockchain ETL engines for on-chain operations, ensuring traceability and authenticity. - Provides performance monitoring and regulatory insights through specialized dashboards. 5. **Use Cases**: - Facilitates secure inter-departmental data exchanges with granular access control. - Enhances collaboration efficiency while maintaining strict data privacy and integrity. The document underscores the transformative potential of Data Hyperloop in addressing inefficiencies in traditional data management systems, particularly for large-scale organizations. It combines advanced technologies to ensure secure, flexible, and efficient data sharing. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/120translate20250112225229-250112155932-fade3a23-thumbnail.jpg?width=120&height=120&fit=bounds" /> The document introduces the **Data Hyperloop**, an innovative data transmission technology inspired by the Hyperloop concept in transportation. Key aspects of the Data Hyperloop include: 1. **Technology Overview**: - Utilizes blockchain, cryptography, edge computing, and AI to establish secure, efficient, and closed-loop data transmission and storage systems. - Data is transmitted via encrypted capsules (DataCapsules) to edge nodes (Data EdgeStations), ensuring high security and efficient utilization. 2. **Advantages**: - **Data Integrity**: Blockchain ensures data cannot be cloned or copied. - **Security**: AI analyzes data reading/writing behavior to prevent leaks. - **Flexibility**: Reduces central data center load and enables decentralized, manageable point-to-point sharing. - **Efficiency**: Allows seamless integration of traditional applications into blockchain frameworks with one-click deployment. 3. **Applications**: - Designed for both private and public cloud deployments. - Supports SQL-based interactions while providing enhanced security through semantic-level data leakage prevention. 4. **Operational Features**: - Includes intelligent tools like Smart Data Hatch (SDH) for secure access to data. - Offers blockchain ETL engines for on-chain operations, ensuring traceability and authenticity. - Provides performance monitoring and regulatory insights through specialized dashboards. 5. **Use Cases**: - Facilitates secure inter-departmental data exchanges with granular access control. - Enhances collaboration efficiency while maintaining strict data privacy and integrity. The document underscores the transformative potential of Data Hyperloop in addressing inefficiencies in traditional data management systems, particularly for large-scale organizations. It combines advanced technologies to ensure secure, flexible, and efficient data sharing.

MOSS Hyperloop on-chain ETL platform for AGI from Linchuan Wang

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0 MOSS AI Web3-Road-to-AGI_HongKong-EN.pptx /slideshow/moss-ai-web3-road-to-agi_hongkong-en-pptx/274803407 web3-road-to-agihongkong-en-250111132500-f1508883
shared at HongkongRelated Work Productivity, Means of Production, and Relations of Production in AGI Why Now? The Fusion of Two Major AI Schools of Thought: Connectionism vs. Symbolism A New Paradigm for Web3 Computing (From General Computing to Intelligent Computing) The Evolution Path of Crypto Assets (From Scalars and Vectors to Tensor Assets) Conclusion: The Web3 Path for AGI Current Progress Next Steps , April, 2024]]>
shared at HongkongRelated Work Productivity, Means of Production, and Relations of Production in AGI Why Now? The Fusion of Two Major AI Schools of Thought: Connectionism vs. Symbolism A New Paradigm for Web3 Computing (From General Computing to Intelligent Computing) The Evolution Path of Crypto Assets (From Scalars and Vectors to Tensor Assets) Conclusion: The Web3 Path for AGI Current Progress Next Steps , April, 2024]]> Sat, 11 Jan 2025 13:25:00 GMT /slideshow/moss-ai-web3-road-to-agi_hongkong-en-pptx/274803407 ubix@slideshare.net(ubix) MOSS AI Web3-Road-to-AGI_HongKong-EN.pptx ubix shared at HongkongRelated Work Productivity, Means of Production, and Relations of Production in AGI Why Now? The Fusion of Two Major AI Schools of Thought: Connectionism vs. Symbolism A New Paradigm for Web3 Computing (From General Computing to Intelligent Computing) The Evolution Path of Crypto Assets (From Scalars and Vectors to Tensor Assets) Conclusion: The Web3 Path for AGI Current Progress Next Steps , April, 2024 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/web3-road-to-agihongkong-en-250111132500-f1508883-thumbnail.jpg?width=120&height=120&fit=bounds" /> shared at HongkongRelated Work Productivity, Means of Production, and Relations of Production in AGI Why Now? The Fusion of Two Major AI Schools of Thought: Connectionism vs. Symbolism A New Paradigm for Web3 Computing (From General Computing to Intelligent Computing) The Evolution Path of Crypto Assets (From Scalars and Vectors to Tensor Assets) Conclusion: The Web3 Path for AGI Current Progress Next Steps , April, 2024

MOSS AI Web3-Road-to-AGI_HongKong-EN.pptx from Linchuan Wang

]]> 231 0 https://cdn.slidesharecdn.com/ss_thumbnails/web3-road-to-agihongkong-en-250111132500-f1508883-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Causal Emergence and Artificial Intelligence.pptx /slideshow/causal-emergence-and-artificial-intelligence-pptx/274377212 causalemergenceandartificialintelligence-241225140312-887bbfd5
Causal Emergence and Artificial Intelligence This presentation explores the intersection of causal emergence, neural networks, and artificial intelligence. It delves into the fundamental questions of intelligence, both natural and artificial, and examines how principles derived from nature can inform and optimize computational paradigms. Central to the discussion is the concept of causal emergence, which occurs when a reorganized network at a macroscopic scale has greater effective information (EI) than the original microscopic network. This phenomenon underpins the organization and efficiency of biological systems, offering insights into the design of adaptive and scalable artificial systems. The presentation highlights: Wild Intelligence: A meta-force underlying the diverse abilities of natural organisms, from foraging to communication. Aspect-Oriented Programming (AOP): Explored as a method to encapsulate cross-cutting concerns, drawing analogies with biological systems like neurons and ganglia to illustrate how nature achieves modularity and complexity. Neural Network Simulation with AOP: Parallels between neuronal structures and AOP paradigms, where Aspects, PointCuts, and Advice mimic the roles of neurons, synapses, and signal transmission. Causal Structures in Networks: The role of effective information and entropy in understanding and optimizing causal relationships within networks. Biological Analogies: Examples from single-celled organisms to vertebrates demonstrate how nature organizes cross-cutting concerns for survival, adaptability, and efficiency. Emergence in AI: The potential of leveraging causal emergence for developing neural networks capable of dynamic reorganization and optimization. This innovative approach combines insights from biology, programming paradigms, and AI research, proposing a unified framework to address complex challenges in network dynamics and intelligence modeling.]]>
Causal Emergence and Artificial Intelligence This presentation explores the intersection of causal emergence, neural networks, and artificial intelligence. It delves into the fundamental questions of intelligence, both natural and artificial, and examines how principles derived from nature can inform and optimize computational paradigms. Central to the discussion is the concept of causal emergence, which occurs when a reorganized network at a macroscopic scale has greater effective information (EI) than the original microscopic network. This phenomenon underpins the organization and efficiency of biological systems, offering insights into the design of adaptive and scalable artificial systems. The presentation highlights: Wild Intelligence: A meta-force underlying the diverse abilities of natural organisms, from foraging to communication. Aspect-Oriented Programming (AOP): Explored as a method to encapsulate cross-cutting concerns, drawing analogies with biological systems like neurons and ganglia to illustrate how nature achieves modularity and complexity. Neural Network Simulation with AOP: Parallels between neuronal structures and AOP paradigms, where Aspects, PointCuts, and Advice mimic the roles of neurons, synapses, and signal transmission. Causal Structures in Networks: The role of effective information and entropy in understanding and optimizing causal relationships within networks. Biological Analogies: Examples from single-celled organisms to vertebrates demonstrate how nature organizes cross-cutting concerns for survival, adaptability, and efficiency. Emergence in AI: The potential of leveraging causal emergence for developing neural networks capable of dynamic reorganization and optimization. This innovative approach combines insights from biology, programming paradigms, and AI research, proposing a unified framework to address complex challenges in network dynamics and intelligence modeling.]]> Wed, 25 Dec 2024 14:03:12 GMT /slideshow/causal-emergence-and-artificial-intelligence-pptx/274377212 ubix@slideshare.net(ubix) Causal Emergence and Artificial Intelligence.pptx ubix Causal Emergence and Artificial Intelligence This presentation explores the intersection of causal emergence, neural networks, and artificial intelligence. It delves into the fundamental questions of intelligence, both natural and artificial, and examines how principles derived from nature can inform and optimize computational paradigms. Central to the discussion is the concept of causal emergence, which occurs when a reorganized network at a macroscopic scale has greater effective information (EI) than the original microscopic network. This phenomenon underpins the organization and efficiency of biological systems, offering insights into the design of adaptive and scalable artificial systems. The presentation highlights: Wild Intelligence: A meta-force underlying the diverse abilities of natural organisms, from foraging to communication. Aspect-Oriented Programming (AOP): Explored as a method to encapsulate cross-cutting concerns, drawing analogies with biological systems like neurons and ganglia to illustrate how nature achieves modularity and complexity. Neural Network Simulation with AOP: Parallels between neuronal structures and AOP paradigms, where Aspects, PointCuts, and Advice mimic the roles of neurons, synapses, and signal transmission. Causal Structures in Networks: The role of effective information and entropy in understanding and optimizing causal relationships within networks. Biological Analogies: Examples from single-celled organisms to vertebrates demonstrate how nature organizes cross-cutting concerns for survival, adaptability, and efficiency. Emergence in AI: The potential of leveraging causal emergence for developing neural networks capable of dynamic reorganization and optimization. This innovative approach combines insights from biology, programming paradigms, and AI research, proposing a unified framework to address complex challenges in network dynamics and intelligence modeling. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/causalemergenceandartificialintelligence-241225140312-887bbfd5-thumbnail.jpg?width=120&height=120&fit=bounds" /> Causal Emergence and Artificial Intelligence This presentation explores the intersection of causal emergence, neural networks, and artificial intelligence. It delves into the fundamental questions of intelligence, both natural and artificial, and examines how principles derived from nature can inform and optimize computational paradigms. Central to the discussion is the concept of causal emergence, which occurs when a reorganized network at a macroscopic scale has greater effective information (EI) than the original microscopic network. This phenomenon underpins the organization and efficiency of biological systems, offering insights into the design of adaptive and scalable artificial systems. The presentation highlights: Wild Intelligence: A meta-force underlying the diverse abilities of natural organisms, from foraging to communication. Aspect-Oriented Programming (AOP): Explored as a method to encapsulate cross-cutting concerns, drawing analogies with biological systems like neurons and ganglia to illustrate how nature achieves modularity and complexity. Neural Network Simulation with AOP: Parallels between neuronal structures and AOP paradigms, where Aspects, PointCuts, and Advice mimic the roles of neurons, synapses, and signal transmission. Causal Structures in Networks: The role of effective information and entropy in understanding and optimizing causal relationships within networks. Biological Analogies: Examples from single-celled organisms to vertebrates demonstrate how nature organizes cross-cutting concerns for survival, adaptability, and efficiency. Emergence in AI: The potential of leveraging causal emergence for developing neural networks capable of dynamic reorganization and optimization. This innovative approach combines insights from biology, programming paradigms, and AI research, proposing a unified framework to address complex challenges in network dynamics and intelligence modeling.

Causal Emergence and Artificial Intelligence.pptx from Linchuan Wang

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0 Causal emergence and artificial intelligence.pdf /slideshow/causal-emergence-and-artificial-intelligencepdf/261621491 causalemergenceandartificialintelligence-230930101215-f7319281
Under what circumstances will an aspect arise in software? Generate highscale networks? If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated?]]>
Under what circumstances will an aspect arise in software? Generate highscale networks? If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated?]]> Sat, 30 Sep 2023 10:12:15 GMT /slideshow/causal-emergence-and-artificial-intelligencepdf/261621491 ubix@slideshare.net(ubix) Causal emergence and artificial intelligence.pdf ubix Under what circumstances will an aspect arise in software? Generate highscale networks? If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated? <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/causalemergenceandartificialintelligence-230930101215-f7319281-thumbnail.jpg?width=120&height=120&fit=bounds" /> Under what circumstances will an aspect arise in software? Generate highscale networks? If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated?

Causal emergence and artificial intelligence.pdf from Linchuan Wang

]]> 54 0 https://cdn.slidesharecdn.com/ss_thumbnails/causalemergenceandartificialintelligence-230930101215-f7319281-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Aspect oriented a candidate for neural networks and evolvable software /slideshow/aspect-oriented-a-candidate-for-neural-networks-and-evolvable-software-131636025/131636025 aspect-orientedacandidateforneuralnetworksandevolvablesoftware1-190213154122
This is a paper written in 2004 and has been accepted by WASOD workshop 2004 https://people.cs.kuleuven.be/~dirk.craeynest/ada-belgium/events/04/040927-sefm-waosd.html the meta data can be found in A Bibliography of Aspect-Oriented Software Development, Version 2.0]]>
This is a paper written in 2004 and has been accepted by WASOD workshop 2004 https://people.cs.kuleuven.be/~dirk.craeynest/ada-belgium/events/04/040927-sefm-waosd.html the meta data can be found in A Bibliography of Aspect-Oriented Software Development, Version 2.0]]> Wed, 13 Feb 2019 15:41:22 GMT /slideshow/aspect-oriented-a-candidate-for-neural-networks-and-evolvable-software-131636025/131636025 ubix@slideshare.net(ubix) Aspect oriented a candidate for neural networks and evolvable software ubix This is a paper written in 2004 and has been accepted by WASOD workshop 2004 https://people.cs.kuleuven.be/~dirk.craeynest/ada-belgium/events/04/040927-sefm-waosd.html the meta data can be found in A Bibliography of Aspect-Oriented Software Development, Version 2.0 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aspect-orientedacandidateforneuralnetworksandevolvablesoftware1-190213154122-thumbnail.jpg?width=120&height=120&fit=bounds" /> This is a paper written in 2004 and has been accepted by WASOD workshop 2004 https://people.cs.kuleuven.be/~dirk.craeynest/ada-belgium/events/04/040927-sefm-waosd.html the meta data can be found in A Bibliography of Aspect-Oriented Software Development, Version 2.0

Aspect oriented a candidate for neural networks and evolvable software from Linchuan Wang

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0 Paradigm Shifts /slideshow/paradigm-shifts-1514977/1514977 paradigmshifts-090531220453-phpapp02
Paradigm shifts in management, computation, development process...what is the invisible hand? Is Tao?]]>
Paradigm shifts in management, computation, development process...what is the invisible hand? Is Tao?]]> Sun, 31 May 2009 22:04:42 GMT /slideshow/paradigm-shifts-1514977/1514977 ubix@slideshare.net(ubix) Paradigm Shifts ubix Paradigm shifts in management, computation, development process...what is the invisible hand? Is Tao? <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/paradigmshifts-090531220453-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Paradigm shifts in management, computation, development process...what is the invisible hand? Is Tao?

Paradigm Shifts from Linchuan Wang

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0 Scrum Practices /slideshow/scrumpractices/1514955 scrumpractices-12438249879-phpapp01
scrum practice]]>
scrum practice]]> Sun, 31 May 2009 21:56:52 GMT /slideshow/scrumpractices/1514955 ubix@slideshare.net(ubix) Scrum Practices ubix scrum practice <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/scrumpractices-12438249879-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> scrum practice

Scrum Practices from Linchuan Wang

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0 Paradigm Shifts /slideshow/paradigmshifts/1514950 paradigmshifts-124382480702-phpapp01
paradigm shifts in management, computation and development process]]>
paradigm shifts in management, computation and development process]]> Sun, 31 May 2009 21:55:37 GMT /slideshow/paradigmshifts/1514950 ubix@slideshare.net(ubix) Paradigm Shifts ubix paradigm shifts in management, computation and development process <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/paradigmshifts-124382480702-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> paradigm shifts in management, computation and development process

Paradigm Shifts from Linchuan Wang

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0 https://public.slidesharecdn.com/v2/images/profile-picture.png www.tagtal.com https://cdn.slidesharecdn.com/ss_thumbnails/120translate20250112225229-250112155932-fade3a23-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/moss-hyperloop-on-chain-etl-platform-for-agi/274820521 MOSS Hyperloop on-chai... https://cdn.slidesharecdn.com/ss_thumbnails/web3-road-to-agihongkong-en-250111132500-f1508883-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/moss-ai-web3-road-to-agi_hongkong-en-pptx/274803407 MOSS AI Web3-Road-to-A... https://cdn.slidesharecdn.com/ss_thumbnails/causalemergenceandartificialintelligence-241225140312-887bbfd5-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/causal-emergence-and-artificial-intelligence-pptx/274377212 Causal Emergence and A...