rmikkilineni at ggu.edu

From Prompt to Purpose: Toward Mindful Machines and the Architecture of Meaningful Intelligence

🔊Listen to a Deep Dive on Mindful Machines by clicking the above picture Abstract The rapid proliferation of large language models (LLMs) like GPT has catalyzed a transformation in artificial intelligence. These systems demonstrate linguistic fluency, scalability, and modularity, yet remain limited by their lack of memory, embodiment, intentionality, and meta-cognition. This paper introduces MindfulContinue reading “From Prompt to Purpose: Toward Mindful Machines and the Architecture of Meaningful Intelligence”

From Cells to Code and Chips: Integrating Enterprise Processes with Digital Genome

Understanding the Digital Genome: Bridging Human and Machine Intelligence

Mark Burgin’s Legacy, General Theory of Information, and Future of AI

February 18, 2025 marks the second anniversary of Late Prof. Mark Burgin’s passing away leaving a wealth of information in many books, papers in several journals and International Conferences for us to update our knowledge. I had the privilege of learning about the General Theory of Information and work closely with him to develop severalContinue reading “Mark Burgin’s Legacy, General Theory of Information, and Future of AI”

Natural Intelligence, Machine Intelligence, General Theory of Information, and all that Jazz: Part I

Video: Ingredients of natural intelligence, machine intelligence, and GTI Part I: Understanding Natural and Machine Intelligence The holy grail of computer scientists and information technology professionals is to design and build machines that replicate the capabilities of human intelligence. While trillions of dollars spent have produced impressive results in process automation, intelligent decision-making using insightsContinue reading “Natural Intelligence, Machine Intelligence, General Theory of Information, and all that Jazz: Part I”

What is a Computer and Is the Brain a Computer?

When someone asks the question “Is the brain a computer?”, the answer depends on the knowledge, the person or the system (for example a Large Language Model (LLM)), possesses and whether it is adequate to answer the question. Whether the response is accepted or rejected also depends on the knowledge the receiver possesses. So, it is important to understand the nature of knowledge, how it is acquired (the learning process), and how it is used. General Theory of Information provides a framework for understanding and modeling the representation and use of knowledge in both biological and artificial systems.

Human Learning, The Knowledge Gap, Machine Learning, The Role of Large Language Models, Future of AI, and All that Jazz

Bing Eye’s View of General Theory of Information, Burgin-Mikkilineni Thesis, Autopoietic and Cognitive Automata, and all that Jazz

This video and the article are about showing a new approach to creating a transparent model-based machine intelligence that captures the associative long-term memory based on event history. The system is designed to use medical knowledge from various sources including the large language models (LLMs) to create and use event history in the early medical disease diagnosis process. The system is designed using the Structural Machines, Cognizing Oracles, and Knowledge Structures suggested by the General Theory of Information.

Machine Intelligence, Human Intelligence, the Future of AI, General Theory of Information, and all that Jazz

This blog discusses the evolution of machine intelligence and potential future options for machine intelligence evolution.

Human Intelligence and Machine Intelligence, what is the Difference?

Making computing machines mimic living organisms has captured the imagination of many since the dawn of digital computers.According to Charles Darwin, the difference in mind between humans and higher animals, great as it is, certainly is one of degree and not of kind. Human intelligence stems from the genome that is transmitted from the survivor to the successor. Machine intelligence stems from humans representing how knowledge can be represented as a sequence of symols (data structures) and operations on them (programs), also represented as a sequence of symbols. The evolution of the data structures, using John von Neumann’s stored program control implementation of the Turing Mchine, operated on by the programs lead to process automation and mimicking neural networks of the human brain. This blog explores the difference between current state of the art of human and machine intelligence.

General Theory of Information, Managing the Business of Life, Life Processes, Free Will, and all that Jazz.

General Theory of Information, Managing the Business of Life, Life Processes, Free Will, and all that Jazz