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Maybe raising a child and growing up as a person are not that different. Reading parenting books taught me more about adults – most of the time, I just substitute the word “child” with the word “human” and the meaning is not changed a bit. I learned more about and how to effectively by reading than in any self-help book I read. conflict resolution skills communicate How to Talk So Kids Will Listen & Listen So Kids Will Talk taught me how to mirror the emotions of adults and children in my life, with no judgment. As a result, they just keep on talking, revealing more of their internal landscape. Peaceful Parent, Happy Kids: How to Stop Yelling and Start Connecting And then, there is Montessori. For a parent lucky enough to be literate, have access to sanitary living conditions and opportunities, it has become something like a rite of passage to get accustomed to the . Montessori pedagogy Prepared Environment In a Montessori prepared environment, all the materials and experiences are always at a child’s fingertips: furniture appropriately sized, shelves at her height, miniature everyday tools, self-correcting materials (think of Matrioshka dolls, if they are not classified correctly, there will be one doll left). This kind of environment improves learning and independence as it enables children to carry out most tasks by themselves. My adult-prepared environment is a blend of analog and digital. The most important material for me is my daily agenda. After a few tinkerings, what works for me is putting all tasks digitally in or Google Calendar synced with in Todoist. Then, I rewrite manually some of my daily tasks in my daily notebook. I prefer to plan every day in advance, and continuously throughout the day. I think better on paper, so I journal daily, trying to be more careful with how I’m spending my time. Todoist IFTTT Digitally, I also make sure to always log out from websites after I use them. At the end of the day, I clear my tabs, either using or just close them. is enabled by default. The purpose is to have an environment that would lead to… Onetab ColdTurkey Uninterrupted Work Cycle In Montessori pedagogy, it is paramount to not disturb the child when she is working. Just sit back and watch her. If she wishes to repeat the activity, let her do it as many times as she wants (practice makes it permanent). When a child is immersed in an activity that captivates her, she displays a surprising capacity for concentration, and she can stay in that activity for prolonged periods of time. Anecdotally, I lost count of hours of watching my child immersed in transfer or water activities. It is obvious that this Montessori idea corresponds to the term coined by Cal Newport. deep work Sometimes we forget that: M "The child is not an empty being who owes whatever he knows to us who have filled him up with it. No, the child is the builder of man. There is no man existing who has not been formed by the child he once was." aria Montessori If you would like to find more about Montessori, I recommend , especially for her down to earth approach (you have been warned, there are some blogs or books pushing on “My Montessori is better than yours”). Julia Palmarola’s Practical Guide book Just as children thrive on , I noticed a vast improvement in my own non-parent life when using . One of my best ways to fight procrastination is to have the same productive routine, over and over and over. And over. There is less and less mental friction to just start on something if I managed to do the same thing repeatedly in the past. routines atomic habits Always make a . Like every parent knows, leaving the house without having a plan, is a sure recipe for disaster. This does track to what one of the most productive people said plan If you fail to plan, you are planning to fail. Benjamin Franklin Problem-solving, empathy, analytical reasoning, critical thinking, leadership, adaptability, teamwork, efficient communication, all these transferable soft skills are crucial regardless of operating in a high-performance work setting or negotiating going-out rules with a 3-year-old. Previously published on my blog .

Being a Productive Parent with the Montessori Pedagogy in Mind

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Limitations of the study and possible future studies Despite its inherent limitations, including its single case design and the potential for bias, the exploratory depth of the study uncovered hidden potential within these systems, even amid serious concerns about generalizability. Future research could include: • Refining the crafting of prompts. • Exploring new features of these and other GenAIbots being introduced with increasing frequency. • Establishing standardised benchmarks to evaluate and compare chatbots and AI systems' performance, accuracy, and reliability. • Conducting long-term studies to observe the evolution of chatbots' capabilities and their impact on user interactions over time. • Conducting research with real students in classroom settings and beyond to assess these AI systems' practical educational applications and challenges. • Investigating chatbots' learning and adaptation capabilities to individual user needs and preferences over time. • Researching the integration of multimodal inputs (e.g., text, voice, image) to enhance chatbot capabilities and user interaction experiences. When implementing GenAIbots in Chemistry learning, it is crucial to evaluate benefits and drawbacks judiciously, ensuring accurate information delivery and considering the implications of reduced human interaction. These concerns may be alleviated by integrating GenAIbots with other educational tools or activities promoting collaborative dialogue among learners. Author Contributions The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation. Conflicts of interest There are no conflicts to declare. Acknowledgements The authors warmly acknowledge Melanie Swan for her invaluable suggestion, which led to the transition from using the term 'objects-to-think-with' to 'agents-to-thinkwith'. References Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionising education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152 Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4337484 Bardin, L. (1977). L’analyse de contenu. PUF - Presses Universitaires de France. Bitzenbauer, P. (2023). ChatGPT in physics education: A pilot study on easy-to-implement activities. Contemporary Educational Technology, 15(3), ep430. https://doi.org/10.30935/cedtech/13176 Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. ArXiv, 2005.14165. http://arxiv.org/abs/2005.14165 Castro Nascimento, C. M., & Pimentel, A. S. (2023). Do Large Language Models Understand Chemistry? A Conversation with ChatGPT. Journal of Chemical Information and Modeling, 63(6), 1649–1655. https://doi.org/10.1021/acs.jcim.3c00285 David, E. (2023, September 21). Microsoft to add DALL-E 3 to Bing Chat. The Verge; Vox Media. https://www.theverge.com/2023/9/21/23873690/microsoft-new-ai-features-bingsearch-shopping-dall-e-3 Dewi, C. A., Pahriah, P., & Purmadi, A. (2021). The Urgency of Digital Literacy for Generation Z Students in Chemistry Learning. International Journal of Emerging Technologies in Learning, 16(11), 88–103. https://doi.org/10.3991/ijet.v16i11.19871 Dunlop, L., Hodgson, A., & Stubbs, J. E. (2020). Building capabilities in chemistry education: happiness and discomfort through philosophical dialogue in chemistry. Chemistry Education Research and Practice, 21(1), 438–451. https://doi.org/10.1039/C9RP00141G Flavell, J. H. (1976). Metacognitive aspects of problem-solving. In L. B. Resnick (Ed.), The Nature of Intelligence (pp. 231–236). Lawrence Erlbaum. Floridi, L., & Chiriatti, M. (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1 Franciscu, S. (2023). ChatGPT: A Natural Language Generation Model for Chatbots. https://doi.org/10.13140/RG.2.2.24777.83044 Gregorcic, B., & Pendrill, A.-M. (2023). ChatGPT and the frustrated Socrates. Physics Education, 58(3), 035021. https://doi.org/10.1088/1361-6552/acc299 Latour, B. (1991). Nous n’avons jamais été modernes: Essai d’anthropologie symétrique. La Découverte. Leon, A. J., & Vidhani, D. (2023). ChatGPT Needs a Chemistry Tutor, Too. Journal of Chemical Education. https://doi.org/10.1021/acs.jchemed.3c00288 Liu, F., Budiu, R., Zhang, A., & Cionca, E. (2023, October 1). ChatGPT, Bard, or Bing Chat? Differences Among 3 Generative-AI Bots. https://www.nngroup.com/articles/ai-botcomparison/ Metz, C., & Hsu, T. (2023, September 20). ChatGPT Can Now Generate Images, Too. New York Times - Technology. https://www.nytimes.com/2023/09/20/technology/chatgpt-dalle3-images-openai.html Mishra, A., Soni, U., Arunkumar, A., Huang, J., Kwon, B. C., & Bryan, C. (2023). PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models. ArXiv, 2304.01964. https://doi.org/10.48550/arXiv.2304.01964 Mollick, E. R. (2023, April 26). A guide to prompting AI (for what it is worth): A little bit of magic,but mostly just practice. One Useful Thing Blog. https://www.oneusefulthing.org/p/a-guidetoprompting-ai-for-what Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033 OpenAI. (2023). GPT-4 Technical Report. OpenAI. https://cdn.openai.com/papers/gpt-4.pdf Papert, S. A. (1980). Mindstorms - Children, Computers and Powerful Ideas. Basic Books. http://www.arvindguptatoys.com/arvindgupta/mindstorms.pdf Permatasari, M. B., Rahayu, S., & Dasna, W. (2022). Chemistry Learning Using Multiple Representations: A Systematic Literature Review. J.Sci.Learn.2022, 5(2), 334–341. https://doi.org/10.17509/jsl.v5i2.42656 Pimentel, A., Wagener, A., Silveira, E. F. da, Picciani, P., Salles, B., Follmer, C., & Jr., O. N. O. (2023). Challenging ChatGPT with Chemistry-Related Subjects. ChemRxiv. https://doi.org/10.26434/chemrxiv-2023-xl6w3 Schlosser, M. (2019). Agency. In The Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/archives/win2019/entries/agency/ Swan, M. (2015, January 21). We Should Consider the Future World as one of Multi-Species Intelligence. Response to The Edge Question 2015: What Do You Think About Machines That Think?; Edge.org. http://edge.org/response-detail/26070 Taylor, C. A., Hogarth, H., Hacking, E. B., & Bastos, E. (2022). Posthuman Object Pedagogies: Thinking with Things to Think with Theory for Innovative Educational Research. Cultural and Pedagogical Inquiry, 14(1), 206–221. https://doi.org/10.18733/cpi29662 Timilsena, N. P., Maharjan, K. B., & Devkota, K. M. (2022). Teachers’ And Students’ Experiences In Chemistry Learning Difficulties. Journal of Positive School Psychology, 6(10), 2856–2867. https://www.journalppw.com/index.php/jpsp/article/view/13764 Tümay, H. (2016). Reconsidering learning difficulties and misconceptions in chemistry: emergence in chemistry and its implications for chemical education. Chemistry Education Research and Practice, 17(2), 229–245. https://doi.org/10.1039/C6RP00008H Turkle, S. (1984). The Second Self: Computers and the Human Spirit. Simon and Schuster. Yin, R. K. (2011). Applications of Case Study Research. SAGE Publications, Inc. This paper is under CC BY-SA 4.0 DEED license. available on arxiv

Overcoming Limitations in AI Chatbot Research for Future Educational Impact

ভবিষ্যতের শিক্ষাগত প্রভাবের জন্য এআই চ্যাটবট গবেষণায় সীমাবদ্ধতা অতিক্রম করা

Überwindung von Einschränkungen in der KI-Chatbot-Forschung für zukünftige Bildungseffekte

Superar las limitaciones en la investigación de chatbots de IA para lograr un impacto educativo futuro

Surmonter les limites de la recherche sur les chatbots IA pour un impact éducatif futur

भविष्य के शैक्षिक प्रभाव के लिए AI चैटबॉट अनुसंधान में सीमाओं पर काबू पाना

将来の教育への影響のために AI チャットボット研究の限界を克服する

미래 교육적 영향을 위한 AI 챗봇 연구의 한계 극복

Superando as limitações na pesquisa do AI Chatbot para um impacto educacional futuro

Преодоление ограничений в исследованиях чат-ботов с использованием искусственного интеллекта для будущего воздействия на образование

Gelecekteki Eğitim Etkisi için Yapay Zeka Chatbot Araştırmalarında Sınırlamaların Aşılması

Khắc phục những hạn chế trong nghiên cứu Chatbot AI để tạo ra tác động giáo dục trong tương lai

克服人工智能聊天机器人研究的局限性，为未来教育带来影响

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Question about a graph of gases turning into water over time P1: Look, this stuff of chemical equations, gases turning into water over time and all that always throw me off a bit. Could you show me this in a graph or whatever? : Certainly! Understanding how reactant concentrations change over time can be visualized effectively with a graph. ChatGPT For the combustion of hydrogen gas in the presence of oxygen: • The concentrations of hydrogen and oxygen decrease. • The concentration of water vapor increases. Eventually, when all of the hydrogen and oxygen have reacted, their concentrations drop to zero, and we're left with a maximum concentration of water vapor. To depict this, I'll plot a graph of concentration vs. time for hydrogen, oxygen, and water. Here's a visual representation of how the concentrations of reactants and products change over time during the combustion of hydrogen and oxygen to form water: This graph provides a visual way to understand the dynamics of this chemical reaction over time and how reactant concentrations decrease while product concentration increases. Does this graph help clarify the concept for you? Would you like to delve into any specific aspects further? BingChat: Bard: Sure. Here is a graph of the phase changes of water: The x-axis of the graph is temperature, and the y-axis is pressure. The three different lines on the graph represent the solid, liquid, and gas phases of water. The solid line is the melting point curve. It shows the temperature at which water will melt at a given pressure. For example, at a pressure of 1 atmosphere, water will melt at 0 degrees Celsius. The dashed line is the boiling point curve. It shows the temperature at which water will boil at a given pressure. For example, at a pressure of 1 atmosphere, water will boil at 100 degrees Celsius. The triple point is the point where all three phases of water coexist. It is at a temperature of 0.01 degrees Celsius and a pressure of 0.0060 atmospheres. The critical point is the point above which water cannot exist as a liquid. It is at a temperature of 374 degrees Celsius and a pressure of 218 atmospheres. To show the process of water vapor turning into liquid water over time, we can use the following graph: The x-axis of the graph is time, and the y-axis is temperature. The graph shows that as time goes on, the temperature of the water vapor decreases. Eventually, the temperature will reach the dew point, which is the temperature at which water vapor will condense to form liquid water. Once the temperature reaches the dew point, the water vapor will start to condense to form liquid water. The temperature will remain at the dew point until all of the water vapor has condensed to form liquid water. I hope this helps to clarify things. Please let me know if you have any other questions. *: Sure, visual representations can often help make these chemical concepts more clear.* Claude Here's a simple graph that could demonstrate water vapor condensing into liquid water over time: * In this graph: • The x-axis shows the passage of time • The y-axis shows the amount of water vapor (top line) and liquid water (bottom line) • At the start, there is a large amount of water vapor and minimal liquid water • As time passes, the water vapor condenses into liquid water • So the vapor line trends downwards while the liquid water line trends upwards • At the end, there is no more water vapor left - it has fully condensed I could create similar graphs to show the concentrations of reactants decreasing and products increasing over time for any chemical reaction. Let me know if a visual like this helps explain the concept! I can also work on more complex graphs depicting reaction rates, equilibrium etc. if helpful. At this point, the student asked the GenAIbots for a more detailed illustration of these concept. In response, effectively leveraged its Advanced Data Analysis mode to provide a graph that directly addressed the student's inquiry, elucidating the dynamics of the exemplified chemical reaction over time, demonstrating excellence in the categories. Its graph showcased the decline in reactant concentrations alongside the rise in product concentration over time, making it highly relevant and pedagogically valuable. ChatGPT Instructional Strategies and Detail Depth & Content Recommendation Conversely, , despite having the advantage of direct access to the DALL-E 3 image generator (David, 2023), failed to provide a personalized response to the student's request. While the generated images might have been undeniably high quality, the lack of direct relevance to the student's question and the generic nature of the images suggests shortcomings in the and categories. Despite this, this integration is a welcomed step forward, particularly when reflecting on the limitations of the standalone DALL-E 2 version in tasks like lettering, as it is evident in the example below that resulted from the student asking Bing Image Creator to illustrate the concept of chemical reactions. BingChat Personalization & Personable Touch Instructional Strategies Lacking the capability to generate images, showcased its adaptability by sourcing available online images that depicted graphs of water's phase changes. However, this method inherently risks not being precisely tailored to the question at hand. Even though it might have tapped into , the reliance on pre-existing content might not always be the most effective way to address specific inquiries. did attempt to employ Instructional Strategies by executing an internal code to generate a graph showcasing the dynamics of the chemical reaction over time, but the visual representation was of inferior quality, possibly confusing rather than clarifying, and weakening the effectiveness of the and categories. Bard Detail Depth & Content Recommendation Claude Engagement & Interactivity Use of Analogy & Comparative Illustrations It is worth noting that DALL-E 3 is also integrated into ChatGPT (Metz & Hsu, 2023) but as a distinct mode separate from the Advanced Data Analysis mode utilised in this session. To access its capabilities, the student would need to initiate a new chat session in that mode and reiterate the question. However, the images produced in this mode would be much more closely aligned with the student's query, as seen below. This paper is under CC BY-SA 4.0 DEED license. available on arxiv

How GenAIbots Explain Condensation 

This paper is available on arxiv under CC BY-SA 4.0 DEED license. Authors: (1) Tomáš Jakl, Czech Academy of Sciences and Czech Technical University; (2) Dan Marsden, School of Computer Science University of Nottingham; (3) Nihil Shah, Department of Computer Science University of Oxford. Table of Links Abstract & Introduction Prelimenaries FVM Theorems for Positive Existential Fragments FVM Theorems for Counting Logic FVM Theorems for The Full Logic Abstract FVM Theorems for Products Adding Equality and Other Enrichment Conclusions, Acknowledgments & References Appendix A FVM theorems for coproducts Appendix B Proofs Omitted from Section III Appendix C Proofs Omitted from Section IV Appendix D Proofs Omitted from Section V Appendix E Proofs Omitted from Section VI Appendix F Proofs Omitted from Section VII Abstract We present a categorical theory of the composition methods in finite model theory – a key technique enabling modular reasoning about complex structures by building them out of simpler components. The crucial results required by the composition methods are Feferman–Vaught–Mostowski (FVM) type theorems, which characterize how logical equivalence behaves under composition and transformation of models. Our results are developed by extending the recently introduced game comonad semantics for model comparison games. This level of abstraction allow us to give conditions yielding FVM type results in a uniform way. Our theorems are parametric in the classes of models, logics and operations involved. Furthermore, they naturally account for the positive existential fragment, and extensions with counting quantifiers of these logics. We also reveal surprising connections between FVM type theorems, and classical concepts in the theory of monads. We illustrate our methods by recovering many classical theorems of practical interest, including a refinement of a previous result by Dawar, Severini, and Zapata concerning the 3-variable counting logic and cospectrality. To highlight the importance of our techniques being parametric in the logic of interest, we prove a family of FVM theorems for products of structures, uniformly in the logic in question, which cannot be done using specific game arguments. I. INTRODUCTION Composition methods constitute a family of techniques in finite model theory for understanding the logical properties of complex structures [1]. One works in a modular fashion, building a structure out of simpler components. The larger structure can then be understood in terms of the logical properties of its parts, and how they behave under the operations used in the construction The first result of this type was proved by Mostowski [2], who showed that the first-order theory of the product of two structures A×B is determined by the first-order theories of A and B. Later, Feferman and Vaught famously proved a very general result for first-order logic, which included showing that the same holds true for infinite products and infinite disjoint unions of structures of the same type [3]. Since then many more Feferman–Vaught–Mostowski (FVM) theorems1 have been shown for various operations, logics and types of structures. These theorems have important applications in the theory of algorithms [4], for example in the development of algorithmic meta-theorems such as Courcelle’s theorem [5]. For our purposes, the typical form of an FVM theorem for a fixed n-ary operation H and logics is as follows. Given structures and L1, . . . , Ln+1 A1, . . . , An B1, . . . , Bn, Here denotes equivalence with respect to the logic . Typically, is either one or two. For example, writing ≡F O for equivalence in first-order logic, Mostowski’s result is given in the form of (1) as: ≡L L n A key tool in finite model theory for establishing that two structures are logically equivalent is that of a model comparison game. Examples of such games are the Ehrenfeucht– Fraïssé [6], [7], pebbling [8] and bisimulation games [9], establishing equivalence in fragments of first order and modal logic. FVM theorems are typically proven using these games, building a winning strategy for the composite structure out of winning strategies for the components. Despite their usefulness, working with model comparison games often requires intricate combinatorial arguments that have to be carefully adapted with even the slightest change of problem domain. To mitigate the difficulty with using game arguments directly, finite model theorists introduced higherlevel methods such as locality arguments or 0–1 laws to establish model equivalences or inexpressibility. The recently introduced game comonad framework [10], [11] provides a new such tool. This provides a unifying formalism for reasoning about model comparison games, using categorical methods. The definition of a comonad enables a transfer of results from the formally dual theory of monads, commonly encountered in the categorical semantics of computation and universal algebra [12], [13], [14]. Game comonads are designed to encapsulate a particular model comparison game, and are the key abstraction allowing us to give uniform results, whilst avoiding making arguments specific to a particular logic or its corresponding game. The early work on game comonads focused on capturing many important logics [15], [16], [17], laying the foundations for further developments. More recent results recover classical theorems from finite model theory, as well as completely new results [18], [19], [20], [21]. See [22] for a recent survey and [23] for an axiomatic formulation. Until now, there has been no account of the composition method with the game comonad framework. We close this gap by introducing a novel method for proving FVM theorems within the game comonad approach, giving results uniformly in the classes of structures, operations and logics involved. Instantiating the abstract results for our example game comonads yields concrete FVM theorems with respect to three typical fragments of first-order logic: the positive existential fragment, i.e. the fragment of firstorder logic of formulas not using universal quantification or negations, counting logic, i.e. the extension of first-order logic with counting quantifiers, full first-order logic. Conventionally, proving an FVM theorem involves cleverly combining several winning model-comparison game strategies to form a winning strategy on the composite structures. In our game comonads approach, we only need to find a collection of morphisms of a specified form to obtain an FVM theorem for the positive existential logic. This collection of morphisms is a formal witness to a combination of strategies. Perhaps surprisingly, to witness equivalence in the counting logic, the same collection of morphisms only has to satisfy two additional axioms which coincide with the standard definition of Kleisli law [25]. Although of practical interest, the FVM theorems in Sections III and IV are relatively straightforward to prove. We present them in detail for pedagogical reasons to develop the ideas gradually. The abstract FVM theorem for the full fragment is more technically challenging. This theorem shows that two additional assumptions suffice to extend an FVM theorem from counting logic to the full logic. We can rephrase these assumptions categorically as showing the operation lifts to a parametric relative right adjoint over an appropriate category. Surprising connections arise with classical results in monad theory, generalizing the notion of bilinear map and its classifying tensor product from ordinary linear algebra [26], [27].

A Categorical Account of
Composition Methods in Logic: Abstract & Introduction

As part of my job search, I'm being introduced to a new language: Python. As the proud owner of a primate brain on the one hand, I'm well aware of the power that , in the context of learning, can have on me. gamification As a technophile on the other, I couldn't miss the emergence of artificial intelligence tools, notably the conversational AI phenomenon that is ChatGPT, developed by OpenAI. How can ChatGPT help me discover Python while making the experience as fun as possible? FROM ChatGPT - the Generalist TO ChatRPG - the Python Expert Although powerful, ChatGPT is even more so when subjected to . So, I've defined how I want ChatGPT to take charge of training me in Python, following a certain formalism to give it as much as possible: role-playing context The role of the AI: ChatGPT will be a Python expert with a strong propensity for teaching. What I expect from the AI: ChatGPT will have to introduce me to the most common syntax and methods of the Python language. The method: in order to achieve this, I want ChatGPT to propose a series of exercises, I'll tell it I have a certain amount of knowledge (JS), and I'll ask it to provide me with external documentation so that I can explore the notions that I am learning further (and, moreover, it will allow me to check that ChatGPT isn't fooling me). The way: finally, I introduce the notion of gamification of my learning, specifying my minimum expectations on this subject: (RPG, Mage, notion of XP). Become a Powerful Mage Initially, ChatGPT provided me with a series of "exercises"; even though it's called that, it's nothing more than code extracts enabling me to grasp the basics of Python syntax. As agreed, he provided me with documentation, gave me experience so that I could level up, and listed the skills acquired during this first phase. Having reached Level 7, I asked ChatGPT to provide me with a more substantial challenge than simply copying code into my IDE. Notice how OpenAI doubts my kindness when I ask ChatGPT to kick some ugly monsters in the teeth. After having been congratulated on my perspicacity facing this first boss, which I easily swept aside, and then provided with a new code-copying "exercise", I had to face my . first real challenges OMG, The Data Dragon! Unimpressed by the enemy, and helped by good , I naturally . documentation slaughtered the hot breathed creature This is where learning via conversational AI makes sense. ChatGPT is capable of providing an while between the two proposals. We'll see a little later that it's capable of being even more complete when it comes to analyzing the code I propose. alternative solution explaining the difference The other advantage is the ease with which you can "shape" the conversation. This way, I was able to obtain an Artifact, and that's . dopamine directly in the veins Yeah I claimed, so what?!? A bit of lore, it's always nice. The Pythonic Monster! After a new series of exercises/lessons, a few questions about instruction 'with', a little challenge on how to throw exceptions, some article reading, and a lot of leveling-up; I asked to take on a . ChatGPT offered me a multi-stage challenge (a succession of small algorithmic problems), with the promise of a chest full of well-deserved loot : new monster Once again, ChatGPT provides a and is complete enough to demonstrate the advantages of its solution over mine. quality correction What's more, I got a really cool amulet! Make ChatRPG Even More RPGed With an MCQ At this stage of my discovery of Python with ChatGPT, I thought it would be a good idea to check that I'd acquired the concepts I'd seen previously. So I asked the AI to generate an MCQ for me, which I included in an encounter with an NPC (non-player character), with the promise of being rewarded with a if I succeeded. familiar So, after answering the questions of a (probably Gandalf undercover), I was able to choose a companion for the rest of my adventure. strange but clever peasant Aware that I sometimes find it difficult to and my code, I've chosen to fight my next battles alongside the Shadowstalker. The beast has a whole arsenal of techniques that will enable me to be more efficient in the future. factor optimize ChatGPT lets me apply a different reading to my code I've identified beforehand! So, I can ask for specific feedback without having to define what kind of feedback I need. according to the needs Here, for example, is the first of the techniques applied to a problem I was given on a quest further along my initiatory journey: the aim of the problem was to generate all the prime numbers up to the number entered by the user. It's got style! Conclusion Considering what I already knew about ChatGPT, the AI has lived up to my expectations regarding its ability to support the discovery of a new programming language. I was, however, very enthusiastic about its ability to bring a gamification layer to the process. Here, in no particular order, is a list of the pros and cons I encountered during my experience: Pros: Quick and easy to set up. Adaptable over time. Satisfactory progress overview. Lore is ok. Ability to correct behavior that doesn't meet your expectations. Possibility of re-launching the latest ChatGPT contribution if it doesn't suit you. "Wow, it can do that ?!" effect. Cons: Commits a few errors and inaccuracies: for example, the first version of the MCQ included a question to which no answer could be given. Requires reminders from time to time: "Don't forget to provide me with documentation", "give out rewards for success", "you must include my progress in the general Lore of our conversation", etc. A few tips if you want to try out this way of learning: Don't use this method on a subject you don't know too much about! If ChatGPT makes a mistake or lies to you, you won't know. Give it as clear and precise information as possible. Don't give it too many instructions at once. At the end of my experiment, I tried to automate the way it generates learning and challenge phases, in a prompt of around thirty lines and with sometimes complex instructions. The result? I broke everything! Nothing beats the expertise of a human being! Pedagogy is a virtue that's reserved for us, the machine is currently unable to appreciate precisely what a student needs to get the most out of what he/she's learning. If you want to be trained in the best possible conditions, call a professional. Bonus I asked ChatGPT to provide me with prompts to generate images using . Stable Diffusion ChatGPT : He's not wrong. What about ? Vast subject. copyright management for artists present in datasets used to train models Thanks!

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185 Stories To Learn About Ai Applications

Not a day goes by without scientists or renowned intellectuals speaking solemnly about the risks associated with the uncontrolled development of artificial intelligence. The rumor of the first Singularity, Q Star, born in the labs of OpenAI, the company behind ChatGPT, has further accelerated concerns. In the meantime, an ethical and technical framework with uncertain foreseeable effectiveness begins to be debated by politicians and governments worldwide. But what is the reality, in an almost hysterical context in which everyone gives their opinion, often without knowledge... Stephen Hawking shortly before his death, James Cameron referring to Terminator, Mo Gawdat (former CBO of Google X), Geoffrey Hinton (formerly with Google Brain now known as Google DeepMind, considered as one of the fathers of modern AI), Satya Nadella (Microsoft's CEO): all these experts, and many others, have already warned us all on multiple occasions about the civilizational danger of an uncontrolled AI. Sam Altman himself, the CEO then ex-CEO, and now new CEO of OpenAI, co-signed with 349 other experts a one-sentence declaration organized by the NGO "Center for AI Safety" last May. Their words are crystal clear: “Mitigating extinction risk from AI should be a global priority, together with other societal risks such as pandemics and nuclear war.” (1) Elon Musk has also spoken in this direction, not bothered by another contradiction, he is one of the first investors in OpenAI, signed an open letter 6 months ago with 1,100 other personalities for a 6-month moratorium concerning AI (2), and has just announced the launch of “TruthGPT”. Quite the adventure! It seems difficult to pick the wheat from the chaff as to the true intentions of these declarations when we understand that the very same people who claim to be on the side of "good" are all directly or indirectly involved in the most funded and advanced AI research labs. Ethics and necessary safeguards are at the centre of all discussions but at the same time a merciless economic and strategic war is being played out: which nation(s) will take the lead that will profoundly redefine the global power dynamics? All of this makes more sense once you become aware that it is not extraordinary intelligence or exceptional talent that has propelled contemporary billionaires to the level of wealth that is theirs today; it is hard work (this, we must admit), the happy course of events, and above all the exclusive access - well before this concept is revealed to the public - to a dedicated proprietary Singularity. Guess what Elon named his own! AI IS NOT JUST LIKE ANY OTHER INNOVATION AI is not just another innovation on the road to progress. Until now, the nation which had a determining competitive advantage for a certain period of time was the one which announced the first discovery or innovation: a new exploitable reserve of fossil energy, a rare metal mine, the scientific and industrial validation of a new type of nuclear reactors (e.g. fusion vs fission), quantum transistors (QBits), or first vaccine against the Covid-19… With AI, the first country to announce that it possesses an operational Singularity has in its hands the extraordinary tool from which ALL future innovations will emanate. It is the definitive Pandora's box. Tim Urban’s summary of the power of such a tool will help us understand better this unparalleled advantage: Imagine that a singularity is turned on in a lab somewhere on Earth; at time t=zero, it will possess the equivalent reasoning power of a human brain (approximately 100 billion synapses); After a minute, by self-learning, it is today estimated that this Artificial Intelligence will have reached the power of all human brains combined; After two minutes, the power of all human brains since the advent of humans on Earth; After just three minutes, the added power of all that is endowed with thinking in the universe; And at the end of the fourth minute, it's Lucy from the Luc Besson movie, but in real life: this Singularity will undoubtedly have more or less extensive control over space, matter, and time. And that's when the problems start for us humans. “IRREVOCABLE” RISKS The “Singularity risk” is added to a list which now fills the fingers of one hand and characterizes an unprecedented era in the history of humankind: it is the first time that we are concretely confronted with a multitude of risks of “irrevocable impact”, meaning the total destruction of humankind due to a potential catastrophe of planetary scale: nuclear holocaust climate deregulation mass extinction of species global pandemic and in the foreseeable future (within 5 to 10 years according to the consensus), the irrevocable impact of a technological Singularity. Problem: with the risk of a nuclear holocaust, it took several decades for the public to correctly assess the technical prerequisites necessary for understanding such risk, and to become capable of having an enlightened opinion on the matter. We can recall that the concept of nuclear holocaust is addressed for the first time in the Science Fiction novel Last and First Men by Olaf Stapledon (1930), that the first atomic bombing (Hiroshima) took place in 1945, and that the very first Partial Nuclear Test Ban Treaty was signed 18 years later (!) in 1963 in Moscow, by the United States and the USSR as well as a majority of both sides’ allies. But for example, the world is still very far from consensus and concrete action-plans concerning climate disruption. Although it is now proven - it is difficult to deny the statistics which show that storms, tsunamis, and temperature anomalies are increasing - the exact causes are still debated by a strongly divided scientific community. As for the risk of a global pandemic, what to think of the amateur-ish management of Covid by governments around the world, and of the TV sets invaded all day long by so-called experts coming to explain what was needed to be done while never having published any research document considered a reference in epidemiology... Thirty years have allowed people and then decision-makers to correctly understand the issues arising with the creation and proliferation of a cataclysmic weapon like nuclear fire, and to act accordingly to put in place the necessary safeguards. And it is still not fully resolved today, far from it. A full year was necessary for people and then for decision-makers to begin to understand the outbreak of a global pandemic like Covid-19 and to act accordingly to structure the necessary defense and care processes. And it is still also not correctly resolved to this day. In the case of artificial intelligence, when the first Singularity appears, humankind will have 4 minutes. In 2005, with the expression "technological singularity", the computer scientist and futurologist Raymond Kurzweil hypothesized that artificial intelligence would trigger a surge in technological growth which would induce unpredictable changes in society. Beyond this point, progress would only be the work of self-improving artificial intelligence, with new, increasingly intelligent generations appearing more and more quickly, ultimately creating a powerful superintelligence that would far surpass human intelligence. WHO THE PUBLIC NEEDS TO BE INFORMED AND EDUCATED ON AI The risks that the human race has faced up until now are eminently complex: not only are they problems with a very large number of variables (i.e. impossible to model without having to carry out multiple simplifications which degrade the relevance of the results obtained), but they also require a solid cultural and scientific background to be able to produce an elaborated reasoning and develop an opinion in full awareness. Who actually does this preliminary work? But even before this, which body structures the content that would allow people to obtain unbiased information, learn and educate themselves correctly on these subjects? Is it not precisely the job of those who are entrusted with the power to make society function to ensure that people can grasp the issues of their time? We quote Noam Chomsky - a respected intellectual and linguist, former professor at MIT who in his time, exchanged with peers of Foucault's caliber - denouncing the manipulation of the masses by the elites: "People not only don't know what's happening to them, they don't even know that they don't know In his essays, The Age of Spiritual Machines and Humanity 2.0., the computer scientist and futurologist Raymond Kurzweil creates the concept of the "law of accelerating returns" which structures the constant acceleration of technological progress based on Moore’s law (the power of computer chips doubles every two years at constant cost). He suggests that the phases of exponential growth in technological progress would be part of patterns visible throughout human history and even before, from the appearance of life on Earth, taking into account its biological complexity. According to Kurzweil, this will lead to unimaginable technological progress during the 21st century, the inflexion point of which will be the appearance of the complete Singularity. The question will then be whether all of humanity will be able to change speed, which could therefore redefine the notion of humanity, or whether there will be a part of humanity which will prefer to try to remain evolving at its previous speed. The advent of the singularity will likely be so sudden that no one will be granted time to react accordingly: the subsequent phases of awareness, observation, analysis, and then reaction for humans would be inadequate. The definition of technological singularity then becomes technological progress so rapid that it exceeds the capacity of humans to maintain control over it or to know how to anticipate it, understand it and be able to react in time. In this context, the vision of a life during which most of the knowledge and culture would be transmitted during youth and almost stops at one’s entry into the work life becomes nonsense. It is imperative to find a way to remain correctly informed and educated throughout one's life in order to stay abreast of the permanent and increasingly rapid changes occurring in the world. We need to be able to inform and educate the public about AI and the Singularity now BEFORE it happens. Because, unlike other risks of irrevocable impact, once it has happened there is only 4 minutes to go, and it will then be too late to think and decide. Humankind will then have lost any chance of maintaining control over its own destiny. Tim Urban, editor of the excellent blog of popular science , gives the following striking example: if we experimented with trying to define the period of time that would be needed for a human not to be able sustain the shock of time-travelling into the future (i.e. impossible for this person to comprehend the technological advances of this new era they live in), we discover that this period shrinks exponentially over the ages. waitbutwhy.com You would have to send a human from the period 12,000 BC to around the year 1500 for him to go crazy, but it would be enough to send a human from the period 1750 to around the 2000s to get the same result. And it is likely that we are close to the moment when this period will be less than the duration of a lifetime: a senior in the 2020s will probably not be able to mentally survive a post-Singularity world, which will simply be fundamentally too different from the one he had experienced in the first part of their life (without the information, training and learning processes having been set up accordingly to allow him to gradually adapt). HOW TO EDUCATE PEOPLE ABOUT WEB3 The issue at stake today is primarily educational. How to convince today's youth to inform and educate themselves to get the necessary prerequisites for maintaining intellectual and moral discernment at a sufficient level? The task is large when looking at the major threat posed by an unregulated AI and a singularity which could emerge in an instant, somewhere in the Qbits (quantum transistors) of a secret lab... This is the challenge of the artistic and sociological experience “World of The Machines”, created by a team of specialists in media, marketing, blockchain, NFTs, AI, and web3. Learn in a painless way, and capture attention thanks to a bold narrative, a new and immersive user interface, a connected web3 gadget, and a gamified experience. All of this permitted by the advent of the incomplete Singularity Nissam Gorma. Get ready for a deep dive in the next and last part of this series. We will complete this introduction with an interview of Huber Etienne, philosopher specializing in the ethics of artificial intelligence, founder of the "computational philosophy" movement, former head of ethics for generative AI models at Meta, and current CEO of the government consulting company Quintessence AI. Question 1 - Hubert, I imagine that you immediately spotted what was true and what was invented in these first two parts. Let’s just say that I appreciate the liberties you take with reality! Question 2 - What led you to become passionate about AI and make it your career? Unlike most of my colleagues, I have never been a geek and my interest in AI arose accidentally, as the result of a double dissatisfaction. Trained as a philosopher and financier, I was disappointed by my professors at the Sorbonne University who, although brilliant, described the world as it should be without them doing anything to change it. I was also terribly bored in the offices of investment banks and funds. All this gray matter mobilized to produce tons of slides which will barely be glimpsed; all this made no sense to me and generative AI has come to put an end to it! “How should a young philosopher in a world in crisis act to give meaning to his life? » I asked myself. It was then that I chose to embrace philosophy wholeheartedly, but to do so with the efficiency of a banker serving a goal: to participate, at my level, in saving the humanity in distress. My first metaethical questionings – with thoughts relating to the moral relationships that humans must maintain with non-human beings such as other animals, objects or robots – gradually directed me towards AI. My obsession to make myself useful led me to develop computational philosophy: a resolutely activist approach to philosophy, open to all other disciplines and which gives itself the means to enact change. Question 3 - Back to what I'm writing about: what is your opinion on Kurzweil's words and the acceleration of technology? It seems to me that Kurzweil's error consists of seeing in Moore's law a sort of physical law, like the law of universal gravity, when it is only an observed phenomenon, and whose reality only partially fits the theory. In addition, the conservation of Moore's law implies increasing investments, therefore a competition of will in order to support it. We understand that this law only binds those who believe in it and it must continue so that we believe in it; it is based on a self-fulfilling prophecy. Therefore, Kurzweil could well be right, in the sense that humanity is destined to run after Moore's law, but we would also be well advised not to be seduced by these controversial arguments. Current research in AI is gradually moving away from science towards religion and those who stop for a moment to question our collective hysteria are seen as enemies of “progress”. But no one should be ashamed of not falling into technological fanaticism; it is even our duty as reasoned men and women. Question 4 - Do you agree with my vision on the urgency of rethinking knowledge distribution systems, particularly with regards to the themes involved in what I call the "irrevocable impact risks" among which AI seems to me to be the most potentially close to materialize? Absolutely! What I hear here and there is distressing because, from the mouths of this new legion of self-proclaimed experts in AI ethics, what comes out are banalities at best, nonsense at worst, often things that seem true but which research has refuted. Access to knowledge has never been so open and yet the world seems to be disconnected from it. You were talking about the manipulation of the public by the elites but the manipulators have changed because the traditional elites are just as manipulated. They are the toys of those who blow hot and cold, playing on fears and the need for reassurance to serve unworthy ambitions. The worst part is undoubtedly that the decision makers think they know when they don’t. For example, it is often claimed that we must educate young people about the risks of disinformation on social networks, even though seniors are the ones who spread it the most by far! Without falling into ageism, we must nowadays accept that age is not necessarily a guarantee of wisdom and that to remain connected to the developments of the world we live in, continued education is necessary. AI does indeed pose civilizational threats but it remains a tool, a weapon with which some seek to destroy and others to save. “[…] the misfortune is that whoever wants to act like an angel acts like a beast,” Pascal would conclude. Question 5 - I know you've heard about the "World of the Machines" project. What do you think about it? The project is ambitious to say the least! It is also very intelligently thought out, socially useful and, let's say it, a little crazy. This is undoubtedly the reason why I like it so much and why I find it properly post-modern. It is representative of these initiatives that we see emerging in an increasingly complex and confusing world, blurring the distinctions to go back to the meta level and to question the meaning of everything. Social and artistic experience at the crossroads of technologies (NFTs, AI, IoT) and disciplines, it mixes educational pedagogy and fundraising in a world that calls for a mix of genres. Synaesthesias belong to poets as much as to psychotic subjects. We can therefore expect that some will cry genius, others monstrous, and it is again through its divisive aspect that World of the Machines represents our post-modernity as much as it invites us to define it. At the dawn of a new year which promises to be as rich in surprises as the previous one, all my wishes for success accompany this magnificent UFO. (1) (2) https://www.safe.ai/statement-on-ai-risk https://futureoflife.org/open-letter/pause-giant-ai-experiments/

The Digital Antichrist—Part 2/3:  Unraveling the Risks of Uncontrolled AI Development

Scientific American, Vol. XXXVII.—No. 2. [New Series.], July 14, 1877 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . ADDRESS OF CLARENCE KING ON CATASTROPHISM. here ADDRESS OF CLARENCE KING ON CATASTROPHISM. Mr. Clarence King lately delivered an interesting address before the Sheffield Scientific School of Yale College, New Haven, Conn., under the title of "Catastrophism, or the Evolution of Environment," which promises to evoke considerable discussion. We subjoin an abstract of the principal features of the address, which is quite lengthy. The full text will be found in our Supplements, Nos. 80, 81. Mr. King refuted the doctrine of slow evolution as taught by Huxley and Darwin, and declared that the surface of the earth and climate had been subject to sudden and catastrophic mutation, which included in its environment all types of life. He reasoned that marine fossils are found entombed in rocky beds far remote from present seas; and that these beds were once sea bottoms that have been upheaved by convulsions of Nature. The earliest history of mankind is pregnant with catastrophe, and we have historic story and biblical record of its sudden and destructive energy. He called to mind the vast and massive eruptions of the Pliocene basalt as seen upon our own continent. The great obvious changes in the rocky crust were referred to a few processes; the sub-aerial decay of continents, delivery by streams of land-detritus into the sea, the spreading out of these comminuted materials upon a pelagic floor, and lastly upheaval, by which oceanic beds were lifted up into subsequent land masses. All these processes he declared to have been more rapid in the past than now. Suddenness, world-wide destructiveness, were the characteristics of geological changes. Periods of calm, like the present, are suddenly terminated by brief catastrophic epochs. Successive faunas and floras were created only to be extinguished by general cataclysms. He believed in recurrent, abrupt accelerations of crust change, so violent as to destroy all life on the globe. He declared the idea to be the survival of a prehistoric terror, and was backed up by breaks in the great palæontological record. Of the geologic features of our continent, he said that beneath our America lies buried another distinct continent, which he called Archæan America, which was made up of what was originally ocean beds lifted into the air and locally crumpled into vast mountain chains, which were in turn eroded by torrents into mountain peaks. The original coast lines of this continent we may never be able fully to survey, but its great features, the lofty chains of the mountains which made its bones, were very nearly co-extensive with our existing systems, the Appalachians and Cordilleras. The cañon-cutting rivers of the present Western mountains have dug out the peaks and flanks of those underlying, primeval uplifts and developed an astonishing topography; peaks rising in a single sweep 30,000 feet from their bases, precipices lifting bold, solid fronts 10,000 feet into the air, and profound mountain valleys. The work of erosion, which has been carried on by torrents of the quaternary age, brings to light buried primeval chains loftier than any of the present heights of the globe. At the close of the Palæzoic age, two enormous masses of what, probably, were then continents began to sink, and as they disappeared the present Atlantic and Pacific oceans appeared, while the sea-floor of a then ocean, emerged, and became the new continent of America. Dividing this new continent was a sea, but catastrophe removed this sea and resulted in the folding up of mountain ranges 20,000 and 40,000 feet in height, thereby essentially changing the whole climate of the continent. Of the land life of the mesozoic age we have abundant remains. The wonderful reptilian and avian fauna of the mesozoic age is now familiar to all. But after the catastrophe, and the change of climate which must necessarily have ensued, this fauna totally perished. After criticising the opinions of Huxley, Lyell, Hutton, Darwin, and others, he recurred to the effects of sudden terrestrial or cosmical changes, and conceived that the effects of these changes would be, first, extermination; secondly, destruction of the biological equilibrium; and thirdly, rapid morphological change on the part of plastic species. When catastrophic change burst in upon the ages of uniformity, and sounded in the ear of every living thing the words "Change or die!" plasticity became the sole principle of salvation. And plasticity is the key to survival and prosperity. Mr. King remarked in conclusion of his address: "He who brought to bear that mysterious energy we call life upon primeval matter bestowed at the same time a power of development by change, arranging that the interaction of energy and matter, which make up environment should, from time to time, burst in upon the current of life and sweep it onward and upward to ever higher and better manifestations. Moments of great catastrophe, thus translated into the language of life, become moments of creation, when out of plastic organisms something newer and nobler is called into being." About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2012). Scientific American, Vol. XXXVII. —No. 2. [New Series.], July 14, 1877. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/38481/pg38481-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

ADDRESS OF CLARENCE KING ON CATASTROPHISM

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