Abstract: This study examines how the sentiment values in the first part of the book entitled as “Underground” of Fyodor Dostoevsky’s ”Notes from Underground” change from words to sentences to paragraphs. Using the GPT-4 language model, we conducted a descriptive analysis of standardized sentiment values and calculated cumulative binned values of the sentiment trajectories over the text. We then created differential equation models to model the sentiment tones using quantile regression analysis. We show that binned values can reveal a more dynamic and potentially chaotic structure when applied to the cumulative sum of sentiments for word, sentence, and paragraph levels. We model differential equations derived for word, sentence, and paragraph levels via quantile regression. They demonstrate how the rate and acceleration of sentiment change are influenced by their current state and rate of change. In conclusion, this study’s findings are important for enhancing the capabilities of AI-driven chatbots in sentiment analysis, particularly in dissecting and understanding the layered emotional landscapes of literary works.

In hierdie studie ondersoek ons die potensiaal van kunsmatige intelligensie (KI), spesifiek Generative Pre-trained Transformer 4 (GPT)-4), om die ontwikkeling van stelseldinamika-simulasies binne die breër konteks van stelselingenieurswese. Die navorsing het ten doel om die geleenthede en beperkings van die gebruik van KI te ontbloot om mense te help om stelseldinamika-modelle te konstrueer en te verfyn. Deur 'n sistematiese, iteratiewe proses was GPT-4 besig met take soos die skep, uitbreiding en stabilisering van simulasies, identifisering van foute, generering van uitbreidingsidees en omskakeling van modelle na Python-kode. Ons bevindinge toon dat GPT-4, hoewel dit nie foutloos is nie, die modelleringsproses aansienlik kan verbeter, menslike foute kan verminder en leer bespoedig. Hierdie artikel doen 'n kritiese ondersoek na die rol van KI in modelontwikkeling, met die klem op die voortgesette belangrikheid van menslike kundigheid in die evaluering en toetsing van simulasies. Uiteindelik argumenteer ons vir 'n simbiotiese verhouding tussen KI en menslike modelleerders, wat die krag van GPT-4 benut om menslike vermoëns te verbeter en om die velde van stelseldinamika en stelselingenieurswese te bevorder.

In this study, we investigate the potential of artificial intelligence (AI), specifically Generative Pre-trained Transformer 4 (GPT-4), to accelerate the development of system dynamics simulations within the broader context of systems engineering. The research aims to uncover the opportunities and limitations of leveraging AI to assist humans in constructing and refining system dynamics models. Through a systematic iterative process, GPT-4 was engaged in tasks such as creating, expanding, and stabilising simulations, identifying errors, generating expansion ideas, and converting models to Python code. Our findings reveal that GPT-4, while not flawless, can significantly enhance the modelling process, reduce human error, and expedite learning. This paper critically examines the role of AI in model development, emphasising the continued importance of human expertise in the evaluation and testing of simulations. Ultimately, we argue for a symbiotic relationship between AI and human modellers, harnessing the power of GPT-4 to augment human capabilities and advance the fields of system dynamics and systems engineering.

Resumen Las innovadoras tecnologías del metaverso y el chat GPT4 (basado en inteligencia artificial) están presentes en el discurso cotidiano de la sociedad; recientemente se han introducido en la práctica médica y están provocando importantes cambios. En cuanto al metaverso ("después del universo"), diversas escuelas y facultades de medicina del mundo comienzan a utilizarlo como una estrategia innovadora dirigida a la enseñanza de materias como anatomía, histología, oftalmología y simulación en mundos paralelos (virtuales) para el aprendizaje y supervisión de cirugías, así como para otras aplicaciones en educación médica y en la relación médico-paciente. Si bien debe tomarse en cuenta como un área de oportunidad para la transformación de la medicina, es importante considerar las diversas limitaciones y riesgos del metaverso en la práctica médica, la formación de estudiantes y la relación del médico con los problemas de salud a los que se enfrenta en su práctica.

Abstract Innovative technologies such as the metaverse and chat GPT-4 (based on artificial intelligence) are present in the daily discourse of society; recently, they have been introduced into medical practice and are bringing about important changes. In the case of the metaverse ("beyond the universe"), various medical schools and departments around the world are beginning to use it as an innovative strategy for teaching subjects such as anatomy, histology, ophthalmology, and simulation in parallel (virtual) worlds for learning and supervision of surgeries, as well as for other applications in medical education and in the doctor-patient relationship. Although it should be regarded as an area of opportunity for the transformation of medicine, it is important to consider the various limitations and risks of the metaverse in medical practice, student training, and physicians' relationship with the health problems they have to deal with in their practice.