Mark Burgin’s Legacy: The General Theory of Information, the Digital Genome, and the Future of Machine Intelligence

Mikkilineni, Rao

doi:10.3390/philosophies8060107

Cited by 3 publications

(12 citation statements)

References 31 publications

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“…The General Theory of Information (GTI) and the Burgin Mikkilineni thesis provide a framework for understanding information processing and knowledge structures. The GTI, developed by Mark Burgin [8,11,17], is an approach that offers powerful tools for all areas of information studies. It is built on an axiomatic base as a system of two classes of principles and their consequences.…”

Section: Information Processing and Knowledge Networkmentioning

confidence: 99%

“…Cognition allows them to process information into knowledge and use it to manage its interactions between various constituent parts within the system and its interaction with the environment. A digital genome is a model that specifies the operational knowledge of algorithms executing software life processes [8,17]. It is derived from our understanding of genomics, neuroscience, and GTI.…”

Section: Structural Machinesmentioning

confidence: 99%

“…In terms of designing autopoietic and cognitive digital automata [8,17], knowledge structures and networks provide a common knowledge representation from existing symbolic and subsymbolic computing structures to implement autopoiesis and cognitive behaviors. Autopoiesis enables digital automata to use the specifications in their digital genomes to instantiate themselves using matter and energy transformations.…”

Section: Knowledge Structures and The Knowledge Networkmentioning

confidence: 99%

“…They are different from the Turing Oracle Machines [8,17] which are abstract machines used to study decision problems. They can be visualized as a Turing machine with a black box, called an oracle, which can solve certain problems in a single operation.…”

Section: Cognizing Oraclesmentioning

confidence: 99%

“…The selforganizing and self-regulating patterns sense and counteract fluctuations to maintain their stability [3]. On the other hand, current digital computing structures when deployed as a distributed system with asynchronous communication between them, are not stable under large fluctuations in their resource availability or demand [6][7][8]. An application often is executed by several distributed software components using computing resources often owned and managed by different providers and the assurance of end-to-end process sustenance with adequate resources, its stability, safety, security, and compliance with global requirements requires a complex layer of additional processes that increase complexity leading to 'who manages the managers' conundrum.…”

Section: Introductionmentioning

confidence: 99%

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Machine Intelligence with Associative Memory and Event-Driven Transaction History

Mikkilineni,

Kelly

2024

Preprint

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Digital machine intelligence has evolved from its inception in the form of computation of numbers to AI, which is centered around performing cognitive tasks that humans can perform, such as predictive reasoning or complex calculations. The state of the art includes tasks that are easily described by a list of formal, mathematical rules or a sequence of event-driven actions such as modeling, simulation, business workflows, interaction with devices, etc., and also tasks that are easy to do “intuitively”, but are hard to describe formally or as a sequence of event-driven actions such as recognizing spoken words or faces. While these tasks are impressive, they fall short in applying common sense reasoning to new situations, filling in information gaps, or understanding and applying unspoken rules or norms. Human intelligence uses both associative memory and event-driven transaction history to make sense of what they are observing fast enough to do something about it while they are still observing it. In addition to this cognitive ability, all bio-logical systems exhibit autopoiesis and self-regulation. In this paper, we demonstrate how machine intelligence can be enhanced to include both associative memory and event-driven transaction history to create a new class of knowledge-based assistants to augment human intelligence. The digital assistants use global knowledge derived from the Large Language Models to bridge the knowledge gap between various participants interacting with each other. We use the general theory of information and schema-based knowledge representation to create the memory and history of various transactions involved in the interactions.

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Section: Information Processing and Knowledge Networkmentioning

confidence: 99%

Section: Structural Machinesmentioning

confidence: 99%

Section: Knowledge Structures and The Knowledge Networkmentioning

confidence: 99%

Section: Cognizing Oraclesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine Intelligence with Associative Memory and Event-Driven Transaction History

Mikkilineni,

Kelly

2024

Preprint

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A New Class of Intelligent Machines with Self-Regulating, Event-Driven Process Flows for Designing, Deploying, and Managing Distributed Software Applications

Mikkilineni,

Kelly

2023

Preprint

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The benefits of event-driven architecture (EDA) derive from how systems and components are loosely coupled, which can facilitate independent development and deployment of systems, improved scaling and fault tolerance, and integration with external systems, especially in comparison to monolithic architectures. With the advent of new technologies such as containers, and microservices, a new generation of distributed event streaming platforms are commonly used in event-driven architecture for efficient event-driven communication. However, the asynchronous and distributed nature of EDA poses several problems that include handling failures, the dependence of an end-to-end transaction on individual component stability, etc. In this paper, we describe a new approach to designing self-regulating distributed applications with autopoietic and cognitive workflow management. This approach is based on the new science of information processing structures derived from the General Theory of Information. Just as a genome enables self-organizing and self-regulating biological structures, a digital genome enables a specific software application with several components, the ability to use distributed resources and self-regulate the evolution of the system based on functional and non-functional requirements, and best-practice policies that maintain the stability, safety, and survival under non-deterministic fluctuations in the demand for resources. In addition, cognitive workflow management assures end-to-end transaction delivery.

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Digital Genome and Self-Regulating Distributed Software Applications with Associative Memory and Event-Driven History

Mikkilineni,

Kelly,

Crawley

2024

Preprint

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Biological systems have a unique ability inherited through their genome. It allows them to build, operate, and manage a society of cells with complex organizational structures where autonomous components execute specific tasks and collaborate in groups to fulfill systemic goals with shared knowledge. The system receives information from various senses, makes sense of what is being observed, and acts using its experience, while the observations are still in progress. We use the General Theory of Information (GTI) to implement a digital genome, specifying the operational processes that design, deploy, operate, and manage a cloud-agnostic distributed application that is independent of IaaS and PaaS infrastructure, which provides the resources required to execute the software components. The digital genome specifies the functional and non-functional requirements that define the goals and best-practice policies to evolve the system using associative memory and event-driven interaction history to maintain stability and safety while achieving the system’s objectives. We demonstrate a structural machine, cognizing oracles, and knowledge structures derived from GTI used for designing, deploying, operating, and managing a distributed video streaming application with autopoietic self-regulation that maintains structural stability and communication among distributed components with shared knowledge while maintaining expected behaviors dictated by functional requirements.

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Mark Burgin’s Legacy: The General Theory of Information, the Digital Genome, and the Future of Machine Intelligence

Cited by 3 publications

References 31 publications

Machine Intelligence with Associative Memory and Event-Driven Transaction History

Machine Intelligence with Associative Memory and Event-Driven Transaction History

A New Class of Intelligent Machines with Self-Regulating, Event-Driven Process Flows for Designing, Deploying, and Managing Distributed Software Applications

Digital Genome and Self-Regulating Distributed Software Applications with Associative Memory and Event-Driven History

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