Renato P. dos Santos

Melanie Swan, Takashi Kido, Eric Roland et al.

The advancement in generative AI could be boosted with more accessible mathematics. Beyond human-AI chat, large language models (LLMs) are emerging in programming, algorithm discovery, and theorem proving, yet their genomics application is limited. This project introduces Math Agents and mathematical embedding as fresh entries to the "Moore's Law of Mathematics", using a GPT-based workflow to convert equations from literature into LaTeX and Python formats. While many digital equation representations exist, there's a lack of automated large-scale evaluation tools. LLMs are pivotal as linguistic user interfaces, providing natural language access for human-AI chat and formal languages for large-scale AI-assisted computational infrastructure. Given the infinite formal possibility spaces, Math Agents, which interact with math, could potentially shift us from "big data" to "big math". Math, unlike the more flexible natural language, has properties subject to proof, enabling its use beyond traditional applications like high-validation math-certified icons for AI alignment aims. This project aims to use Math Agents and mathematical embeddings to address the ageing issue in information systems biology by applying multiscalar physics mathematics to disease models and genomic data. Generative AI with episodic memory could help analyse causal relations in longitudinal health records, using SIR Precision Health models. Genomic data is suggested for addressing the unsolved Alzheimer's disease problem.

Fabiano Villan, Renato P. dos Santos

Background: In the contemporary educational landscape, technology has the power to drive innovative pedagogical practices. Overcoming the resistance of teachers and students to adopting new methods and technologies is a challenge that needs to be addressed. Objectives: To evaluate the effectiveness of ChatGPT as a co-advisor in research projects and its influence on the implementation of Project-Based Learning (PBL), as well as overcoming resistance to the use of new pedagogical methodologies. Design: An action-research methodology was employed, including unstructured interviews and the application of questionnaires via Google Forms. Setting and Participants: The research was conducted in an elementary school, involving 353 students and 16 teachers. Data Collection and Analysis: Data were gathered through observations and notes in meetings and interviews, complemented by electronic questionnaires, with quantitative and qualitative analyses performed via Microsoft Excel and Google Forms. Results: The introduction of ChatGPT as a pedagogical tool led to increased student engagement and decreased teacher resistance, reflected in recognition at local science fairs. Conclusion: The study confirmed the utility of ChatGPT in school research co-orientation, highlighting its role in facilitating PBL and promoting cultural changes in educational practice, with proactive school management identified as a catalysing element in adapting to educational innovations.

Gian Alexandre Michaelsen, Renato P. dos Santos

Background: The integration of artificial intelligence (AI) into daily life, particularly through chatbots utilizing natural language processing (NLP), presents both revolutionary potential and unique challenges. This intended to investigate how different input forms impact ChatGPT, a leading language model by OpenAI, performance in understanding and executing complex, multi-intention tasks. Design: Employing a case study methodology supplemented by discourse analysis, the research analyzes ChatGPT's responses to inputs varying from natural language to pseudo-code engineering. The study specifically examines the model's proficiency across four categories: understanding of intentions, interpretability, completeness, and creativity. Setting and Participants: As a theoretical exploration of AI interaction, this study focuses on the analysis of structured and unstructured inputs processed by ChatGPT, without direct human participants. Data collection and analysis: The research utilizes synthetic case scenarios, including the organization of a "weekly meal plan" and a "shopping list," to assess ChatGPT's response to prompts in both natural language and pseudo-code engineering. The analysis is grounded in the identification of patterns, contradictions, and unique response elements across different input formats. Results: Findings reveal that pseudo-code engineering inputs significantly enhance the clarity and determinism of ChatGPT's responses, reducing ambiguity inherent in natural language. Enhanced natural language, structured through prompt engineering techniques, similarly improves the model's interpretability and creativity. Conclusions: The study underscores the potential of pseudo-code engineering in refining human-AI interaction and achieving more deterministic, concise, and direct outcomes, advocating for its broader application across disciplines requiring precise AI responses.

Renato P. dos Santos, Melanie Swan

In a previous paper, it was discussed whether Bitcoin and/or its blockchain could be considered a complex system and, if so, whether a chaotic one, a positive response raising concerns about the likelihood of Bitcoin/blockchain entering a chaotic regime, with catastrophic consequences for financial systems based on it. This paper intends to simplify and extend that analysis to other PoW, PoS, and hybrid protocol-based cryptocurrencies. As before, this study was carried out with the help of Information Theory of Complex Systems, in general, and Crutchfield's Statistical Complexity measure, in particular. This paper is a work-in-progress. We intend to uncover some other measures that capture the qualitative notion of complexity of systems that can be applied to these cryptocurrencies to compare with the results here obtained.

Renato P. dos Santos

The philosophy of blockchain technology is concerned, among other things, with blockchain ontology, how it might be characterised, how it is being created, implemented, and adopted, how it operates in the world, and how it evolves over time. This paper concentrates on whether Bitcoin/blockchain can be considered a complex system and, if so, whether it is a chaotic one. Beyond mere academic curiosity, a positive response would raise concerns about the likelihood of Bitcoin/blockchain entering a 2010-Flash-Crash-type of chaotic regime, with catastrophic consequences for financial systems based on it. The paper starts by highlighting the relevant details of the Bitcoin/blockchain ecosystem formed by the blockchain itself, bitcoin end users (payers and payees), capital gains seekers, miners, full nodes maintainers, and developers, and their interactions. Then the Information Theory of Complex Systems is briefly discussed for later use. Finally, the blockchain is investigated with the help of Crutchfield's Statistical Complexity measure. The low non-null statistical complexity value obtained suggests that the blockchain may be considered algorithmically complicated but hardly a complex system and unlikely to enter a chaotic regime.

Renato P. dos Santos

Student difficulties in learning Physics have been thoroughly discussed in the scientific literature. Already in 1980, Papert complained that schools teach Newtonian motion by manipulating equations rather than by manipulating the Newtonian objects themselves, what would be possible in a 'physics microworld'. On the other hand, Second Life and its scripting language have a remarkable learning curve that discourages most teachers at using it as an environment for educational computer simulations and microworlds. The objective of this work is to describe TATI, a textual interface which, through TATILogo, an accessible Logo language extension, allows the generation of various physics microworlds in Second Life, containing different types of objects that follow different physical laws, providing a learning path into Newtonian Physics.