General Theory of Information: The Bridge to Mindful Machines

General Theory of Information (GTI) offers a groundbreaking framework for designing mindful machines that bridge the divide between biological intelligence and digital automation. GTI reimagines traditional computing by introducing cognitive, autopoietic (self-regulating) capabilities in digital systems, enabling them to perceive, adapt, and respond autonomously to changing conditions. Unlike conventional AI and AGI models that operate within predefined algorithmic constraints, GTI-based systems go beyond by incorporating self-awareness and a resilient digital self, capable of storing interaction histories and learning from them. This paper explores GTI’s practical applications in systems requiring resilience, cognition, and ethical safeguards. In video streaming and medical assistance, GTI-based digital genomes enable systems to function independently, actively self-correct, and conform to policy-driven ethical standards. These mindful machines embody unique traits rarely achieved with traditional AI: robust resilience through self-corrective mechanisms, adaptive learning from accumulated experiences, and alignment with ethical principles that govern system behavior. In demonstrating how GTI can cultivate resilience, autonomy, and ethical decision-making, this paper reveals GTI’s potential to empower digital automata with human-like adaptability and values. As such, GTI emerges as a bridge to a new generation of digital systems designed not merely to execute but to understand, adapt, and ethically engage within complex real-world environments.