Difference between revisions of "Network Pattern"
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| − | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
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[http://www.youtube.com/results?search_query=network+nature+linked+connected+Graph+AI Youtube search...] | [http://www.youtube.com/results?search_query=network+nature+linked+connected+Graph+AI Youtube search...] | ||
[http://www.google.com/search?q=network+nature+linked+connected+Graph+AI ...Google search] | [http://www.google.com/search?q=network+nature+linked+connected+Graph+AI ...Google search] | ||
| − | * [[Graph]] | + | * [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]] |
| + | * [http://networksciencebook.com/ Network Science |] [[Creatives#Albert-László Barabási|Albert-László Barabási]]... free online book to get started | ||
| + | * [[Life~Meaning]] ... [[Consciousness]] ... [[Loop#Feedback Loop - Creating Consciousness|Creating Consciousness]] ... [[Quantum#Quantum Biology|Quantum Biology]] ... [[Orch-OR]] ... [[TAME]] ... [[Protein Folding & Discovery|Proteins]] | ||
| + | * [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database|Database; Vector & Relational]] ... [[Graph]] ... [[LlamaIndex]] | ||
* [[Computer Networks]] | * [[Computer Networks]] | ||
* [[Python#NetworkX|NetworkX]] a Python library for studying graphs and networks. | * [[Python#NetworkX|NetworkX]] a Python library for studying graphs and networks. | ||
| − | * [[Emergence]] | + | * [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ... [[Algorithm Administration#Automated Learning|Automated Learning]] |
| + | * [[Math for Intelligence]] ... [[Finding Paul Revere]] ... [[Social Network Analysis (SNA)]] ... [[Dot Product]] ... [[Kernel Trick]] | ||
* [[COVID-19]] | * [[COVID-19]] | ||
| − | * [http:// | + | * [http://www.network-science.org/ Network Science.org] ...power-law (scale-free) node-degree distributions are a property of only sparsely connected networks. More densely connected networks show an increasing divergence from power-law |
* [http://www.uvm.edu/pdodds/files/papers/others/1969/travers1969.pdf An Experimental Study of the Small World Problem | Jeffrey Travers and Stanley Milgram] | * [http://www.uvm.edu/pdodds/files/papers/others/1969/travers1969.pdf An Experimental Study of the Small World Problem | Jeffrey Travers and Stanley Milgram] | ||
* [http://www.penguinrandomhouse.com/books/549846/the-square-and-the-tower-by-niall-ferguson/ The Square and the Tower | Niall Ferguson] | * [http://www.penguinrandomhouse.com/books/549846/the-square-and-the-tower-by-niall-ferguson/ The Square and the Tower | Niall Ferguson] | ||
* [http://oracleofbacon.org/ The Oracle of Bacon] computes the Bacon number of any actor or actress from Wikipedia data. A previous implementation used IMDB data. ...[http://en.wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon Six Degrees of Kevin Bacon | Wikipedia] | * [http://oracleofbacon.org/ The Oracle of Bacon] computes the Bacon number of any actor or actress from Wikipedia data. A previous implementation used IMDB data. ...[http://en.wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon Six Degrees of Kevin Bacon | Wikipedia] | ||
| − | Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology. The United States National Research Council defines network science as "the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena." [http://en.wikipedia.org/wiki/Network_science#:~:text=Network%20science%20is%20an%20academic,connections%20between%20the%20elements%20or Network science | Wikipedia] | + | A network pattern is a recurring structural arrangement or established topology of connections between nodes that dictates how they interact, communicate, or distribute resources within a system. This architecture bridges the gap between silicon and biology, echoing the principles of [[Creatives#Michael Levin|Michael Levin's]] bioelectric networks, where cells utilize voltage gradients not just for localized reactions, but to store pattern memories and coordinate large-scale decision-making. In this light, a well-architected network pattern serves as the digital nervous system of your enterprise—not merely a static set of cables, but a self-organizing ecosystem. Just as biological systems rely on intricate feedback loops to sustain life, your digital infrastructure uses topologies like mesh, hub-and-spoke, or decentralized peer-to-peer structures to define the rules of engagement. Here, nodes—whether they are distinct devices, data centers, or software microservices—act like individual cells, communicating continuously to optimize data flow and distribute resources. By mimicking the resilience found in nature, this approach allows the system to adapt to stress, heal around bottlenecks, and evolve with changing demands. Implementing the correct network pattern is therefore critical for scalability; it ensures that communication remains low-latency and secure, minimizing bottlenecks while maximizing availability across the entire digital ecosystem. |
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| + | "A key discovery of network science is that the architecture and the evolution of networks emerging in various domains of science, nature, and technology are rather similar to each other, allowing us to use the same mathematical tools to explore the organizing principles of all these systems." | ||
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| + | — Albert-László Barabási, Network Science | ||
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| + | Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology. The United States National Research Council defines network science as "the study of network representations of physical, biological, and social phenomena leading to [[Predictive Analytics|predictive models]] of these phenomena." [http://en.wikipedia.org/wiki/Network_science#:~:text=Network%20science%20is%20an%20academic,connections%20between%20the%20elements%20or Network science | Wikipedia] | ||
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| − | <b>Authors in Conversation: Niall Ferguson and Albert- | + | <b>Authors in Conversation: Niall Ferguson and [[Creatives#Albert-László Barabási|Albert-László Barabási]] |
| − | </b><br>Harvard Club of Boston's Author Series hosted a special evening conversation with renowned historian Niall Ferguson and the nation's foremost network science expert Albert- | + | </b><br>Harvard Club of Boston's Author Series hosted a special evening conversation with renowned historian Niall Ferguson and the nation's foremost network science expert [[Creatives#Albert-László Barabási|Albert-László Barabási]]. In his most recent book, The Square and the Tower, Ferguson applies lessons from [[Creatives#Albert-László Barabási|Barabási's]] pioneering work in network science to the domain of historical analysis, drawing insights from a wide range of fascinating examples across past decades and centuries, with important implications for current affairs. As [[Creatives#Albert-László Barabási|Barabási]] has demonstrated both in his academic work and in his popular writing (Linked), network science research has led to meaningful discoveries in areas ranging from biology and medicine, to institutional analysis and social networks. |
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| − | <b>BURSTS: The Hidden Pattern Behind Everything We Do | Albert László Barabási | Talks at Google | + | <b>BURSTS: The Hidden Pattern Behind Everything We Do | [[Creatives#Albert-László Barabási|Albert-László Barabási]] | Talks at Google |
| − | </b><br>The Authors@Google program welcomed Albert László Barabási to Google's New York office to discuss his book, " | + | </b><br>The Authors@Google program welcomed Albert László Barabási to Google's New York office to discuss his book, [http://barabasi.com/book/bursts "Bursts: The Hidden Patterns Behind Everything We Do, from Your E-mail to Bloody Crusades"] "In BURSTS (April 2010), [[Creatives#Albert-László Barabási|Barabási]], Director of the Center for Network Science at Northeastern University, shatters one of the most fundamental assumptions in modern science and technology regarding human behavior. [[Creatives#Albert-László Barabási|Barabási]] argues that, rather than being random, humans actually act in predictable patterns. We go along for long periods of quiet routine followed suddenly by loud bursts of activity. Barabasi demonstrates that these breaks in routine, or "bursts," are present in all aspects of our existence— in the way we write emails, spend our money, manage our health, form ideas. [[Creatives#Albert-László Barabási|Barabási]] has even found "burstiness" in our webpage clicking activity and the online news cycle." |
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<b>The Pattern in Nature's Networks | <b>The Pattern in Nature's Networks | ||
| − | </b><br>cience shows it's a small world after all—and nature's networks follow a similar pattern. NOVA Facebook: https://www.facebook.com/NOVAonline NOVA Twitter: https://www.twitter.com/novapbs Follow Mark Zastrow on Twitter: @MarkZastrow PRODUCTION CREDITS Writer, Producer, and Narrator Mark Zastrow Music by Mark Zastrow | + | </b><br>cience shows it's a small world after all—and nature's networks follow a similar pattern. NOVA [[Meta|Facebook]]: https://www.facebook.com/NOVAonline NOVA Twitter: https://www.twitter.com/novapbs Follow Mark Zastrow on Twitter: @MarkZastrow PRODUCTION CREDITS Writer, Producer, and Narrator Mark Zastrow Music by Mark Zastrow |
Editorial Help from Anna Rothschild Original Footage © WGBH Educational Foundation 2014 MEDIA CREDITS Mississippi River watershed National Park Service Diffusion tensor images Human Connectome Project, NIH, Massachusetts General Hospital, Meredith Reid (University of Alabama--Birmingham) Neurons, In Vitro Color! Flickr /thelunch_box (CC BY-NC 2.0) Small world neural network based on figure from van den Heuvel and Sporns (2011) / The Journal of Neuroscience 31(44):15775--15786 Autism spectrum disorder networks Barttfeld et al. (2011) / Neuropsychologia 49 (2011) 254--263 The Formation of Stars and Brown Dwarfs and the Truncation of Protoplanetary Discs in a Star Cluster Matthew R. Bate, Ian A. Bonnell, and Volker Bromm, UK Astrophysical Fluids Facility Floral Art Flickr / Louise Docker (CC BY 2.0) Dark matter filaments Ralf Kaehler, Oliver Hahn and Tom Abel, Kavli Institute for Particle Astrophysics and Cosmology (Stanford) Millennium Simulation flythroughs | Editorial Help from Anna Rothschild Original Footage © WGBH Educational Foundation 2014 MEDIA CREDITS Mississippi River watershed National Park Service Diffusion tensor images Human Connectome Project, NIH, Massachusetts General Hospital, Meredith Reid (University of Alabama--Birmingham) Neurons, In Vitro Color! Flickr /thelunch_box (CC BY-NC 2.0) Small world neural network based on figure from van den Heuvel and Sporns (2011) / The Journal of Neuroscience 31(44):15775--15786 Autism spectrum disorder networks Barttfeld et al. (2011) / Neuropsychologia 49 (2011) 254--263 The Formation of Stars and Brown Dwarfs and the Truncation of Protoplanetary Discs in a Star Cluster Matthew R. Bate, Ian A. Bonnell, and Volker Bromm, UK Astrophysical Fluids Facility Floral Art Flickr / Louise Docker (CC BY 2.0) Dark matter filaments Ralf Kaehler, Oliver Hahn and Tom Abel, Kavli Institute for Particle Astrophysics and Cosmology (Stanford) Millennium Simulation flythroughs | ||
Springel et al. (2005) © WGBH Educational Foundation 2014 | Springel et al. (2005) © WGBH Educational Foundation 2014 | ||
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<b>The Science of Six Degrees of Separation | <b>The Science of Six Degrees of Separation | ||
</b><br>Are all people on Earth really connected through just six steps? | </b><br>Are all people on Earth really connected through just six steps? | ||
| − | There's much more science in this than I initially expected. It turns out ordered networks with a small degree of randomness become small-work networks. This is why your acquaintances turn out to be more important in job searches and finding new opportunities than close friends. Animations in this video by The Lyosacks: http://www.youtube.com/user/TheLyosacks There are some great books on this topic: Duncan Watts, Six Degrees: The Science of a Connected Age Albert- | + | There's much more science in this than I initially expected. It turns out ordered networks with a small degree of randomness become small-work networks. This is why your acquaintances turn out to be more important in job searches and finding new opportunities than close friends. Animations in this video by The Lyosacks: http://www.youtube.com/user/TheLyosacks There are some great books on this topic: Duncan Watts, Six Degrees: The Science of a Connected Age [[Creatives#Albert-László Barabási|Albert-László Barabási]], Linked: How Everything is Connected to Everything Else And here are articles I referred to: [http://www.uvm.edu/pdodds/files/papers/others/1969/travers1969.pdf Milgram's small world experiment] and [http://sociology.stanford.edu/sites/g/files/sbiybj9501/f/publications/the_strength_of_weak_ties_and_exch_w-gans.pdf Strength of Weak Ties | Mark S. Granovetter] |
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| − | == Albert-László Barabási | + | = Albert-László Barabási = |
| − | * [http://barabasi.com/book/linked Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life | Albert-László Barabási] ... [http://www.amazon.com/Linked-Everything-Connected-Business-Everyday/dp/0465085733/ref=sr_1_3?ie=UTF8&qid=1533396806&sr=8-3&keywords=linked Amazon] | + | * [http://en.wikipedia.org/wiki/Albert-L%C3%A1szl%C3%B3_Barab%C3%A1si Wikipedia] |
| − | * [http://barabasi.com/book/bursts Bursts: The Hidden Patterns Behind Everything We Do, from Your E-mail to Bloody Crusades | Albert-László Barabási] ...[http://www.amazon.com/Bursts-Patterns-Everything-mail-Crusades/dp/0452297184 Amazon] | + | * [http://barabasi.com/ Albert-László Barabási Website] |
| + | * [http://barabasi.com/book/linked Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life |] [[Creatives#Albert-László Barabási|Albert-László Barabási]] ... [http://www.amazon.com/Linked-Everything-Connected-Business-Everyday/dp/0465085733/ref=sr_1_3?ie=UTF8&qid=1533396806&sr=8-3&keywords=linked Amazon] | ||
| + | * [http://barabasi.com/book/network-science Network Science |] [[Creatives#Albert-László Barabási|Albert-László Barabási]] ...[http://www.amazon.com/Network-Science-Albert-L%C3%A1szl%C3%B3-Barab%C3%A1si/dp/1107076269 Amazon] | ||
| + | * [http://barabasi.com/book/bursts Bursts: The Hidden Patterns Behind Everything We Do, from Your E-mail to Bloody Crusades |] [[Creatives#Albert-László Barabási|Albert-László Barabási]] ...[http://www.amazon.com/Bursts-Patterns-Everything-mail-Crusades/dp/0452297184 Amazon] | ||
| + | * [http://barabasi.com/book/the-formula#the-formula The Formula: The Universal Laws of Success |] [[Creatives#Albert-László Barabási|Albert-László Barabási]] ... [http://www.amazon.com/Formula-Universal-Laws-Success/dp/0316505498 Amazon] | ||
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| + | [[Creatives#Albert-László Barabási|Albert-László Barabási]] is a Hungarian/Romanian network scientist and author. He is also the Robert Gray Dodge Professor of Network Science and a Distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research, and holds appointments in the Departments of Physics and College of Computer and Information Science, as well as in the Department of Medicine at Harvard Medical School and Brigham and Women Hospital in the Channing Division of Network Science, and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute. | ||
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Latest revision as of 08:24, 7 January 2026
Youtube search... ...Google search
- Analytics ... Visualization ... Graphical Tools ... Diagrams & Business Analysis ... Requirements ... Loop ... Bayes ... Network Pattern
- Network Science | Albert-László Barabási... free online book to get started
- Life~Meaning ... Consciousness ... Creating Consciousness ... Quantum Biology ... Orch-OR ... TAME ... Proteins
- Excel ... Documents ... Database; Vector & Relational ... Graph ... LlamaIndex
- Computer Networks
- NetworkX a Python library for studying graphs and networks.
- Artificial General Intelligence (AGI) to Singularity ... Curious Reasoning ... Emergence ... Moonshots ... Explainable AI ... Automated Learning
- Math for Intelligence ... Finding Paul Revere ... Social Network Analysis (SNA) ... Dot Product ... Kernel Trick
- COVID-19
- Network Science.org ...power-law (scale-free) node-degree distributions are a property of only sparsely connected networks. More densely connected networks show an increasing divergence from power-law
- An Experimental Study of the Small World Problem | Jeffrey Travers and Stanley Milgram
- The Square and the Tower | Niall Ferguson
- The Oracle of Bacon computes the Bacon number of any actor or actress from Wikipedia data. A previous implementation used IMDB data. ...Six Degrees of Kevin Bacon | Wikipedia
A network pattern is a recurring structural arrangement or established topology of connections between nodes that dictates how they interact, communicate, or distribute resources within a system. This architecture bridges the gap between silicon and biology, echoing the principles of Michael Levin's bioelectric networks, where cells utilize voltage gradients not just for localized reactions, but to store pattern memories and coordinate large-scale decision-making. In this light, a well-architected network pattern serves as the digital nervous system of your enterprise—not merely a static set of cables, but a self-organizing ecosystem. Just as biological systems rely on intricate feedback loops to sustain life, your digital infrastructure uses topologies like mesh, hub-and-spoke, or decentralized peer-to-peer structures to define the rules of engagement. Here, nodes—whether they are distinct devices, data centers, or software microservices—act like individual cells, communicating continuously to optimize data flow and distribute resources. By mimicking the resilience found in nature, this approach allows the system to adapt to stress, heal around bottlenecks, and evolve with changing demands. Implementing the correct network pattern is therefore critical for scalability; it ensures that communication remains low-latency and secure, minimizing bottlenecks while maximizing availability across the entire digital ecosystem.
"A key discovery of network science is that the architecture and the evolution of networks emerging in various domains of science, nature, and technology are rather similar to each other, allowing us to use the same mathematical tools to explore the organizing principles of all these systems."
— Albert-László Barabási, Network Science
Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology. The United States National Research Council defines network science as "the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena." Network science | Wikipedia
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Albert-László Barabási
- Wikipedia
- Albert-László Barabási Website
- Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life | Albert-László Barabási ... Amazon
- Network Science | Albert-László Barabási ...Amazon
- Bursts: The Hidden Patterns Behind Everything We Do, from Your E-mail to Bloody Crusades | Albert-László Barabási ...Amazon
- The Formula: The Universal Laws of Success | Albert-László Barabási ... Amazon
Albert-László Barabási is a Hungarian/Romanian network scientist and author. He is also the Robert Gray Dodge Professor of Network Science and a Distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research, and holds appointments in the Departments of Physics and College of Computer and Information Science, as well as in the Department of Medicine at Harvard Medical School and Brigham and Women Hospital in the Channing Division of Network Science, and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute.