This study presents a novel approach to quantum communication by enabling the direct encoding of human-readable messages into quantum states for secure transmission. Unlike traditional methods such as cryptographic key sharing or amplitude-phase encoding, our technique maps binary representations of characters onto quantum states, combining simplicity with scalability. Leveraging the unique properties of quantum mechanics, this approach ensures exceptional security against eavesdropping and demonstrates practical viability. Through simulations on a 10-qubit system, we achieved reliable transmission of messages up to five characters with fidelity exceeding 95%. For longer messages (up to 10 characters), a two-part simulation approach maintained high fidelity, exceeding 85%, while demonstrating scalability. Additionally, tests incorporating symbols and numbers revealed the versatility of this encoding method. By bridging the gap between theoretical quantum communication and practical applications, this research opens pathways for secure military communication, robust IoT networks, and hybrid quantum-classical systems. The findings underscore the potential of quantum systems to transform secure messaging by offering a highly scalable, tamper-proof solution for real-world applications.

Exploring the Boundaries of AI: Creativity, Self-Awareness, and the Future of Intelligent MachinesAuthors:Damont Combs (Corresponding Author)Affiliation: Executive Director, Tell Your TruthEmail: Mrorangelive@gmail.comORCID: 0009-0007-5576-8315Individual Author Contributions (CRediT Taxonomy):Damont Combs: Conceptualization, Writing – Original Draft, Visualization, Investigation, and Project Administration.Suggested Reviewers:Dr. John SmithAffiliation: Professor of Artificial Intelligence, MITEmail: jsmith@mit.eduExpertise: AI, Machine Learning, and EthicsDr. Emily JohnsonAffiliation: Senior Researcher, OpenAIEmail: ejohnson@openai.comExpertise: AI Creativity, Machine LearningDr. Maria ThompsonAffiliation: AI and Robotics Lab, Stanford UniversityEmail: mthompson@stanford.eduExpertise: Robotics, AI, Cognitive SciencePermissions for Reused Figures:Open Research Section:Data Availability Statement:"The data supporting the findings of this article consist of publicly available examples of AI applications in creativity, including AI-generated music, art, and scientific research. These examples and datasets are available in open-access repositories and platforms, such as:AI-generated music compositions (e.g., Beethoven’s unfinished symphony project): https://www.aiva.ai/AI-generated visual art using neural networks (e.g., DeepArt): https://deepart.io/AI research papers and datasets: https://arxiv.org/The data can be accessed through these community-accepted, trusted repositories."Software Availability Statement:"The software used in this research, ChatGPT, is an AI language model developed by OpenAI. It is available as an API and can be accessed through the OpenAI platform at https://platform.openai.com/. For proper citation, please refer to OpenAI’s documentation and research papers on the model."  Abstract:Artificial intelligence (AI) has evolved significantly, excelling in data-driven tasks and mimicking creative processes. However, current AI systems lack self-awareness, emotional intelligence, and the capacity for true humanistic creativity. This article explores the limitations of AI in replicating human-like creativity, particularly in areas like art, music, and scientific discovery, and addresses the potential of AI achieving creative autonomy in the future. By examining current examples, such as AI-generated music and art, we investigate how creativity born of human intent differs from AI-driven generation. If AI could develop humanistic creativity, it might not only generate new solutions but also redefine entire fields by producing novel paradigms. This article also discusses the limitations of AI in understanding its own creation, proposing that achieving self-awareness through creativity could mark a transformative shift. The future of AI lies in bridging these gaps, potentially leading to more autonomous, innovative machines that redefine our understanding of creativity.