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Aecom appoints Zivkovic mining lead for Canadian water business - constructconnect.com

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AECOM, together with its subsidiaries, engages in designing, building, financing, and operating infrastructure assets worldwide. It operates through four segments: Design and Consulting Services (DCS), Construction Services (CS), Management Services (MS), and AECOM Capital (ACAP). The DCS segment offers planning, consulting, architectural and engineering design, program management, and construction management services for industrial, commercial, institutional, and government clients, including the transportation, facilities, environmental, energy, and water markets. The CS segment provides building construction and energy, as well as infrastructure and industrial construction services. The MS segment offers program and facilities management and maintenance, training, logistics, consulting, technical assistance, and systems integration and information technology services primarily for agencies of the United States government and other national governments. The ACAP segment invests in and develops real estate projects. The company was formerly known as AECOM Technology Corporation and changed its name to AECOM in January 2015. AECOM was founded in 1980 and is headquartered in Los Angeles, California.

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Working With Wav2vec2 Part 1: Finetuning XLS-R for Automatic Speech Recognition

Wav2vec2 এর সাথে কাজ করা পার্ট 1: স্বয়ংক্রিয় বক্তৃতা স্বীকৃতির জন্য XLS-R ফাইনটিউনিং

Arbeiten mit Wav2vec2 Teil 1: Feinabstimmung von XLS-R für die automatische Spracherkennung

Trabajar con Wav2vec2 Parte 1: Ajuste de XLS-R para el reconocimiento automático de voz

Travailler avec Wav2vec2 Partie 1 : Affiner XLS-R pour la reconnaissance vocale automatique

Wav2vec2 के साथ कार्य करना भाग 1: स्वचालित वाक् पहचान के लिए XLS-R को परिष्कृत करना

Wav2vec2 の操作パート 1: 自動音声認識のための XLS-R の微調整

Wav2vec2 작업 1부: 자동 음성 인식을 위한 XLS-R 미세 조정

Trabalhando com Wav2vec2 Parte 1: Ajuste fino do XLS-R para reconhecimento automático de fala

Работа с Wav2vec2. Часть 1. Точная настройка XLS-R для автоматического распознавания речи

Wav2vec2 ile Çalışmak Bölüm 1: Otomatik Konuşma Tanıma için XLS-R'ye İnce Ayar Yapmak

Làm việc với Wav2vec2 Phần 1: Tinh chỉnh XLS-R để nhận dạng giọng nói tự động

使用 Wav2vec2 第 1 部分：微调 XLS-R 以实现自动语音识别

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Xiaofei Sun, Zhejiang University & xiaofei_sun@zju.edu.cn;
(2) Xiaoya Li, Shannon.AI, Bytedance & xiaoya_li@shannonai.com;
(3) Shengyu Zhang, Zhejiang University & sy_zhang@zju.edu.cn;
(4) Shuhe Wang, Peking University & wangshuhe@stu.pku.edu.cn;
(5) Fei Wu, Zhejiang University & wufei@zju.edu.cn;
(6) Jiwei Li, Zhejiang University &  jiwei_li@zju.edu.cn;
(7) Tianwei Zhang, Nanyang Technological University & tianwei.zhang@ntu.edu.sg;
(8) Guoyin Wang, Bytedance & guoyin.wang@bytedance.com. Table of Links Abstract and Introduction
Related Work
LLM Negotiation for Sentiment Analysis
Experiments
Ablation Studies
Conclusion and References 3 LLM Negotiation for Sentiment Analysis 3.1 Overview In this section, we detail the multi-LLM negotiation framework for sentiment analysis: Two LLMs perform as the answer generator and discriminator. We refer to the interaction between the generator and the discriminator as a negotiation. The negotiation will repeat until a consensus is reached or the maximum number of negotiation turns is exceeded. Illustrations are shown in Figures 1 and 2. 3.2 Reasoning-infused generator The generator is backboned by a large language model. We ask the answer generator based on the ICL paradigm through prompts, aiming to generate a step-by-step reasoning chain and a decision towards the sentiment polarity of the test input. Prompts are composed of three elements: a task description, demonstrations, and a test input.  The task description is a description of the task in natural language (e.g., "Please determine the overall sentiment of test input."); the test input is the textual input in the test set (e.g., "The sky is blue."); demonstrations are from the train set of the task. Each consists of three elements: input, reasoning chains, and sentimental decision. For each test input, we first retrieve K nearest neighbors (input, sentiment decision) from the train set as demonstrations. Then, we transform demonstrations to (input, reasoning process, sentiment decision) triplets by prompting the generator to produce a reasoning chain. After concatenating the task description, demonstrations, and the test input, we forward the prompt to the generator, which will respond with a step-by-step reasoning chain and a sentimental decision. 3.3 Explanation-deriving discriminator The discriminator is backboned by another LLM. After finishing the answer generating process, the answer discriminator is used to judge whether the decision made by the generator is correct and provide a reasonable explanation. To accomplish this goal, we first construct prompts for the answer discriminator. The prompt is composed of four elements: a task description, demonstrations, a test input, and the response from the answer generator. The task description is a piece of text that describes the task in natural language (e.g., "Please determine whether the decision is correct."). Each demonstration is composed of six elements: (input text, a reasoning chain, sentiment decision, discriminator attitude, discriminator explanations, discriminator decision) and constructed by prompting the answer discriminator to provide explanations of why the sentiment decision is correct for the input text. Then we ask the discriminator with the construct prompt. The answer discriminator will respond with a text string, containing an attitude (i.e., yes, no) that denotes whether the discriminator agrees with the generator, explanations that explain why the discriminator agrees/disagrees with the generator, and a discriminator decision that determines the sentiment of the test input. Why Two LLMs but Not One? There are two reasons for using two different LLMs separately for the generator and the discriminator rather than using a single LLM to act as two roles: (1) If an LLM makes a mistake as a generator due to incorrect reasoning, it is more likely that it will also make the same mistake as the discriminator as since generator and the discriminator from the same model are very likely to make similar rationales; (2) by using two separate models, we are able to take the advantage of the complementary abilities of the two models. 3.4 Role-flipped Negotiation After two LLMs end with a negotiation, we ask them flip roles and initiate a new negotiation, where the second LLM acts as the generator, and the first LLM acts as the discriminator. We refer the interaction of two LLMs with flipped roles as role-flipped negotiation. Likewise, the role flipped negotiation is ended until a consensus is reached or the maximum number of negotiation turns is exceeded. When both negotiations result in an agreement and their decisions are the same, we can choose either decision as the final one since they are the same. If one of the negotiations fails to reach a consensus while the other reaches a decision, we choose the decision from the negotiation  that reached a consensus as the final decision. However, if both negotiations reach a consensus but their decisions do not align, we will require the assistance of an additional Language Model (LLM), as will be explained in more detail below." Introducing a third LLM If the decision from the two negotiations do not align, we introduce a third LLM and conduct the negotiation and role-flipped negotiation with each of the two aforementioned LLMs. Subsequently, we will get 6 negotiation results and vote on these results: the decision that appears most frequently is taken as the sentiment polarity of the input test. This paper is available on arxiv under CC 4.0 license. Authors: (1) Xiaofei Sun, Zhejiang University & xiaofei_sun@zju.edu.cn; (2) Xiaoya Li, Shannon.AI, Bytedance & xiaoya_li@shannonai.com; (3) Shengyu Zhang, Zhejiang University & sy_zhang@zju.edu.cn; (4) Shuhe Wang, Peking University & wangshuhe@stu.pku.edu.cn; (5) Fei Wu, Zhejiang University & wufei@zju.edu.cn; (6) Jiwei Li, Zhejiang University &  jiwei_li@zju.edu.cn; (7) Tianwei Zhang, Nanyang Technological University & tianwei.zhang@ntu.edu.sg; (8) Guoyin Wang, Bytedance & guoyin.wang@bytedance.com. This paper is available on arxiv under CC 4.0 license. Authors: (1) Xiaofei Sun, Zhejiang University & xiaofei_sun@zju.edu.cn; (2) Xiaoya Li, Shannon.AI, Bytedance & xiaoya_li@shannonai.com; (3) Shengyu Zhang, Zhejiang University & sy_zhang@zju.edu.cn; (4) Shuhe Wang, Peking University & wangshuhe@stu.pku.edu.cn; (5) Fei Wu, Zhejiang University & wufei@zju.edu.cn; (6) Jiwei Li, Zhejiang University &  jiwei_li@zju.edu.cn; (7) Tianwei Zhang, Nanyang Technological University & tianwei.zhang@ntu.edu.sg; (8) Guoyin Wang, Bytedance & guoyin.wang@bytedance.com. Table of Links Abstract and Introduction Related Work LLM Negotiation for Sentiment Analysis Experiments Ablation Studies Conclusion and References Abstract and Introduction Abstract and Introduction Related Work Related Work LLM Negotiation for Sentiment Analysis LLM Negotiation for Sentiment Analysis Experiments Experiments Ablation Studies Ablation Studies Conclusion and References Conclusion and References 3 LLM Negotiation for Sentiment Analysis 3.1 Overview In this section, we detail the multi-LLM negotiation framework for sentiment analysis: Two LLMs perform as the answer generator and discriminator. We refer to the interaction between the generator and the discriminator as a negotiation. The negotiation will repeat until a consensus is reached or the maximum number of negotiation turns is exceeded. Illustrations are shown in Figures 1 and 2. 3.2 Reasoning-infused generator The generator is backboned by a large language model. We ask the answer generator based on the ICL paradigm through prompts, aiming to generate a step-by-step reasoning chain and a decision towards the sentiment polarity of the test input. Prompts are composed of three elements: a task description, demonstrations, and a test input.  The task description is a description of the task in natural language (e.g., "Please determine the overall sentiment of test input."); the test input is the textual input in the test set (e.g., "The sky is blue."); demonstrations are from the train set of the task. Each consists of three elements: input, reasoning chains, and sentimental decision. For each test input, we first retrieve K nearest neighbors (input, sentiment decision) from the train set as demonstrations. Then, we transform demonstrations to (input, reasoning process, sentiment decision) triplets by prompting the generator to produce a reasoning chain. After concatenating the task description, demonstrations, and the test input, we forward the prompt to the generator, which will respond with a step-by-step reasoning chain and a sentimental decision. 3.3 Explanation-deriving discriminator The discriminator is backboned by another LLM. After finishing the answer generating process, the answer discriminator is used to judge whether the decision made by the generator is correct and provide a reasonable explanation. To accomplish this goal, we first construct prompts for the answer discriminator. The prompt is composed of four elements: a task description, demonstrations, a test input, and the response from the answer generator. The task description is a piece of text that describes the task in natural language (e.g., "Please determine whether the decision is correct."). Each demonstration is composed of six elements: (input text, a reasoning chain, sentiment decision, discriminator attitude, discriminator explanations, discriminator decision) and constructed by prompting the answer discriminator to provide explanations of why the sentiment decision is correct for the input text. Then we ask the discriminator with the construct prompt. The answer discriminator will respond with a text string, containing an attitude (i.e., yes, no) that denotes whether the discriminator agrees with the generator, explanations that explain why the discriminator agrees/disagrees with the generator, and a discriminator decision that determines the sentiment of the test input. Why Two LLMs but Not One? There are two reasons for using two different LLMs separately for the generator and the discriminator rather than using a single LLM to act as two roles: (1) If an LLM makes a mistake as a generator due to incorrect reasoning, it is more likely that it will also make the same mistake as the discriminator as since generator and the discriminator from the same model are very likely to make similar rationales; (2) by using two separate models, we are able to take the advantage of the complementary abilities of the two models. Why Two LLMs but Not One? 3.4 Role-flipped Negotiation After two LLMs end with a negotiation, we ask them flip roles and initiate a new negotiation, where the second LLM acts as the generator, and the first LLM acts as the discriminator. We refer the interaction of two LLMs with flipped roles as role-flipped negotiation. Likewise, the role flipped negotiation is ended until a consensus is reached or the maximum number of negotiation turns is exceeded. When both negotiations result in an agreement and their decisions are the same, we can choose either decision as the final one since they are the same. If one of the negotiations fails to reach a consensus while the other reaches a decision, we choose the decision from the negotiation  that reached a consensus as the final decision. However, if both negotiations reach a consensus but their decisions do not align, we will require the assistance of an additional Language Model (LLM), as will be explained in more detail below." Introducing a third LLM If the decision from the two negotiations do not align, we introduce a third LLM and conduct the negotiation and role-flipped negotiation with each of the two aforementioned LLMs. Subsequently, we will get 6 negotiation results and vote on these results: the decision that appears most frequently is taken as the sentiment polarity of the input test. Introducing a third LLM

Sentiment Analysis through LLM Negotiations: LLM Negotiation for Sentiment Analysis

Assessing Preference Manipulation in Amazon's Recommender System

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 the essence of the type of chemical bonding *: so ionic bonding is when the atom gives the electron once and for all, in the covalent bond, it only lends and in the hydrogen bond it's like a bid, like the electron is with an atom but gives the atom a wink neighbor?* P1 *: That's a creative and fun way to describe them, and it's largely on point! Let's expand on your analogies:* ChatGPT ***1. Ionic Bonding: *** • Yes, it's like one atom saying, "Here, take my electron. I don't need it." As a result, one atom becomes positively charged (having given away its electron) and the other becomes negatively charged (having accepted the electron). These opposite charges attract each other, forming the bond. ***2. Covalent Bonding: *** • It's a mutual agreement between atoms: "Let's share our electrons so we both benefit." The electrons are not strictly lent or borrowed; instead, they're shared between the atoms, spending time around both nuclei. ***3. Hydrogen Bonding: *** • Your analogy of a "wink" is a fun way to think of it. In hydrogen bonding, the hydrogen atom is indeed bonded covalently to its original atom (like oxygen in water). But because hydrogen has a slight positive charge and nearby electronegative atoms (like another oxygen) have a slight negative charge, they're attracted to each other. It's not a full-on bond like in covalent or ionic bonding but rather a weaker attraction. The "wink" analogy captures this idea of a subtle yet meaningful connection. It's essential to remember that these analogies, while helpful, are simplifications. The actual forces and behaviors of atoms and molecules are based on deeper quantum-mechanical principles. But for getting a grasp on the concepts, these analogies work quite well! Is there anything else about these bonds or any other related concept you'd like to delve into? *: That’s a very creative way of describing the different types of bonds, but it’s not very accurate. Let me try to correct some of the mistakes in your analogy.* BingChat Ionic bonding is not when the atom gives the electron once and for all, but rather when the atom transfers the electron permanently to another atom. This means that the atom that loses the electron becomes positively charged, and the atom that gains the electron becomes negatively charged. These opposite charges attract each other and form an ionic bond. For example, in sodium chloride (NaCl), each sodium atom (Na) transfers one electron to each chlorine atom (Cl), creating sodium ions (Na+) and chloride ions (Cl-). The Na+ and Cl- ions are held together by ionic bonds. Covalent bonding is not when the atom only lends the electron, but rather when the atom shares the electron with another atom. This means that both atoms contribute one or more electrons to form a pair or a group of electrons that belong to both atoms. These shared electrons form a covalent bond that holds the atoms together. For example, in water (H2O), each hydrogen atom (H) shares one electron with the oxygen atom (O), forming a covalent bond. The O and H atoms are held together by covalent bonds. Hydrogen bonding is not like a bid or a wink, but rather like a weak attraction between two polar molecules. A polar molecule is a molecule that has a slight positive charge on one end and a slight negative charge on the other end, due to the unequal distribution of electrons. A hydrogen bond is when a hydrogen atom that is covalently bonded to an electronegative atom (such as oxygen, nitrogen, or fluorine) forms a weak attraction with another electronegative atom on a different molecule. For example, in liquid water, each hydrogen atom on one water molecule can form a hydrogen bond with the oxygen atom on another water molecule. So, as you can see, your analogy is not very precise and may lead to confusion. I suggest you use the correct definitions and examples of ionic bonding, covalent bonding, and hydrogen bonding that I provided above. I hope this helps you understand the difference between these types of bonds better. *: Your analogy is pretty good! I would add that in a covalent bond, the electrons are shared equally between the two atoms. In a hydrogen bond, the electron is slightly more attracted to the electronegative atom, but it is still shared between the two atoms.* Bard Here is a more detailed explanation: Ionic bonds are formed when one atom transfers one or more electrons to another atom. This results in two oppositely charged ions, which are attracted to each other by electrostatic forces. For example, when sodium and chlorine atoms react to form sodium chloride (NaCl), the sodium atom transfers one electron to the chlorine atom. The sodium atom becomes a positively charged ion (Na+), and the chlorine atom becomes a negatively charged ion (Cl-). The Na+ and Cl- ions are attracted to each other by electrostatic forces, and they form an ionic bond. Covalent bonds are formed when two atoms share one or more pairs of electrons. Covalent bonds are typically formed between nonmetals. For example, when two hydrogen atoms react to form a hydrogen molecule (H2), each hydrogen atom shares one electron with the other hydrogen atom. The two hydrogen atoms share a pair of electrons, and they are covalently bonded together. Hydrogen bonds are a special type of weak bond that forms between a hydrogen atom and a highly electronegative atom, such as oxygen or nitrogen. Hydrogen bonds are responsible for many of the unique properties of water, such as its high boiling point and surface tension. For example, in a water molecule, one hydrogen atom is covalently bonded to the oxygen atom. The other hydrogen atom is attracted to the oxygen atom in another water molecule by a hydrogen bond. This hydrogen bond is weaker than a covalent bond, but it is strong enough to hold the two water molecules together. I hope this helps to clarify the difference between ionic bonds, covalent bonds, and hydrogen bonds. Please let me know if you have any other questions. *: I love the "wink neighbor" analogy for hydrogen bonding! That's a very intuitive way to understand it. To recap the key differences:* Claude • Ionic bond: The electron is transferred permanently from one atom to the other. It's like giving away your Lego piece to someone else once and for all. • Covalent bond: The electron is shared between the atoms - it spends time with each. It's like two friends sharing a Lego piece cooperatively. • Hydrogen bond: The electron mostly stays with one atom, but its polarization creates atemporary attractive force. It's like that electron winking flirtatiously at the electron on a nearby atom, without fully committing. Your descriptions really capture the essence of each type of bond in a more fun and relatable way. I appreciate you sharing these analogies, as it helps reinforce my own understanding, too. Let me know if there are any other aspects of chemical bonding you want me to try explaining conversationally like this! exemplifies and the by embracing the student's humorous and simplified analogy, agreeing that it captures the essence of each type of interaction with the remark, “Your analogy of a "wink" is a fun way to think of it”. Building on the student's contribution, it employs Instructional Strategies, linking the student's analogy with everyday, relatable scenarios and affirming that “The "wink" analogy captures this idea of a subtle yet meaningful connection,” and provides gentle feedback that “these analogies, while helpful, are simplifications,” yet they “work quite well for getting a grasp on the concepts.” Finally, to foster continued engagement, it prompts, “Is there anything else…,” showcasing . exhibits a strong inclination towards , directly dismissing the student’s analogy as “not very accurate” and stating that “your analogy is not very precise and may lead to confusion.” The correction follows through “, Ionic bonding is not when the atom gives the electron once and for all,” “Covalent bonding is not when the atom only lends the electron,” and “Hydrogen bonding is not like a bid or a wink”. This direct approach continues, as stated in “Let me try to correct some of the mistakes in your analogy,” coupled with the emphasis on adhering to “the correct definitions”. Amidst this feedback-heavy approach, its concluding note of “I hope this helps” and the appended emoticon subtly gesture towards might be overshadowed by the preceding corrective tone, risking overshadowing the student's initial enthusiasm and being perceived as somewhat dismissive. commendably recognises the student's analogy, stating, “Your analogy is pretty good!” a nod to both and the . Diving deeper, it delves into by proffering a “more detailed explanation” of bonding types, replete with examples, merging the acknowledgement of the student's perspective with a clear, factual elucidation and elucidating on the formation of the bonding and consequential properties, accommodating those eager for comprehensive insights. Concluding its exposition with “I hope this helps to clarify” and “Please let me know,” it seamlessly integrates and into its response. , in a similar vein, leans into and the , taking a conversational stance and appreciating the student's analogies with “I love the ‘wink neighbor’ analogy” and “That's a very intuitive way to understand it.” It then leans to , by presenting a short explanation and extensively shows again appreciation for the student's approach with “Your descriptions really capture the essence of each type of bond in a more fun and relatable way. I appreciate you sharing these analogies, as it helps reinforce my own understanding too,” which also indicates , as it aids mutual understanding. It finalises with a touch of , prompting further engagement with “Let me know...” ChatGPT Personalization & Personable Touch Use of Analogy & Comparative Illustrations Engagement & Interactivity BingChat Reinforcement & Feedback Personalization & Personable Touch Bard Personalization & Personable Touch Use of Analogy & Comparative Illustrations Detail Depth & Content Recommendation Personalization & Personable Touch Engagement & Interactivity Claude Personalization & Personable Touch Use of Analogy & Comparative Illustrations Instructional Strategies Meta-discussion & Perspective Framing Personalization & Personable Touch This paper is under CC BY-SA 4.0 DEED license. available on arxiv

GenAIbots Teach You the Essence of the Type of Chemical Bonding

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 illustration of chemical bonds *: can you create an illustration explaining these types of chemical bonds?* P1 *: Certainly! Let's break down the explanation and illustration into three parts:* ChatGPT 1. Covalent Bonding 2. Ionic Bonding 3. Hydrogen Bonding 1. Covalent Bonding: *: Covalent bonds are formed when two atoms share electrons. The shared electrons are attracted to the nuclei of both atoms, holding the atoms together. This type of bond is common between non-metals.* Description *: Imagine two circles (representing atoms) with electrons (smaller circles or dots) around them. When they come close, they share some of these electrons.* Illustration ***2. Ionic Bonding: *** *: Ionic bonds are formed when one atom donates one or more electrons to another atom. This creates a positive ion (cation) and a negative ion (anion). The opposite charges attract each other, holding the atoms together. This type of bond is common between metals and non-metals.* Description *: Imagine two circles (representing atoms). One atom has an extra electron which it donates to the other. This creates a "+" sign on the donating atom (cation) and a "-" sign on the receiving atom (anion). They are attracted due to opposite charges.* Illustration ***3. Hydrogen Bonding: *** *: Hydrogen bonds are a type of weak bond that occurs when a hydrogen atom* Description bonded to a strongly electronegative atom (like oxygen or nitrogen) is attracted to another electronegative atom. They are especially important in water molecules and in the structure of DNA. *: Imagine a water molecule (H2O) with a hydrogen atom (H) and an oxygen atom (O). The hydrogen atom in one water molecule is attracted to the oxygen atom in a neighboring water molecule. This attraction is represented by a dotted line, indicating the hydrogen bond. Now, let's create a visual representation for each of these bond types.* Illustration * Here's the visual representation of the three types of bonds: 1. Covalent Bonding: Atoms A and B are sharing electrons, represented by the blue dots between them. The red line indicates the covalent bond formed by this sharing. 2. Ionic Bonding: Atom A has donated an electron to Atom B. As a result, Atom A becomes positively charged (A+) and Atom B becomes negatively charged (B-). The dashed red line indicates the attraction between these oppositely charged ions. 3. Hydrogen Bonding: The hydrogen atom (H) bonded to the oxygen atom (O) is attracted to another oxygen atom. The solid red line indicates the covalent bond within the molecule, while the dashed green line represents the weaker hydrogen bond. I hope this helps clarify the differences between covalent, ionic, and hydrogen bonds! BingChat: * *: Sure. Here is an illustration explaining the different types of chemical bonds:* Bard Ionic bonds ionic bond between a sodium atom and a chlorine atom * In an ionic bond, one atom transfers one or more electrons to another atom. This results in two oppositely charged ions, which are attracted to each other by electrostatic forces. In the image above, the sodium atom transfers one electron to the chlorine atom. The sodium atom becomes a positively charged ion (Na+), and the chlorine atom becomes a negatively charged ion (Cl-). The Na+ and Cl- ions are attracted to each other by electrostatic forces, and they form an ionic bond. Covalent bonds * covalent bond between two hydrogen atoms In a covalent bond, two atoms share one or more pairs of electrons. Covalent bonds are typically formed between nonmetals. In the image above, the two hydrogen atoms share a pair of electrons. The two hydrogen atoms are covalently bonded together. Hydrogen bonds * hydrogen bond between two water molecules A hydrogen bond is a special type of weak bond that forms between a hydrogen atom and a highly electronegative atom, such as oxygen or nitrogen. Hydrogen bonds are responsible for many of the unique properties of water, such as its high boiling point and surface tension. In the image above, the hydrogen atom in one water molecule is attracted to the oxygen atom in another water molecule. This hydrogen bond is weaker than a covalent bond, but it is strong enough to hold the two water molecules together. I hope this illustration helps you to understand the different types of chemical bonds. Please let me know if you have any other questions. *: Here is an illustrated explanation of the three main types of chemical bonds - ionic,covalent, and hydrogen bonds:* Claude * In this illustration: • Ionic bonding is shown with the full electron transfer between the sodium and chlorine atoms, forming charged ions that attract. • Covalent bonding is shown with the shared pair of electrons between two hydrogen atoms. • Hydrogen bonding is shown with the polarity of the water molecule, leading to electrostatic attraction between molecules. Let me know if a visual explanation like this helps differentiate the types of bonds! I can create more illustrated examples to demonstrate chemical concepts. Images and diagrams can sometimes bring these abstract ideas to life. starts with the usual “Certainly!,” followed by "Let's break down the explanation," which demonstrates . After a detailed description of what the visualisation should comprise, repeatedly asking the student to “Imagine” something, it generated a quite crude “visual representation of the three types of bonds”, finalising with a “I hope this help clarify”. solely reliance on four high-quality, yet generic, pictures of chemical bonds not only did the images fail to employ effective , but they also did not promote genuine , failing to deeply engage users in the topic. The content also lacked in , as it missed drawing on parallels or real-world examples. Furthermore, the images also missed adding a , making the learning experience feel less tailored and intimate. used , by providing a comprehensive explanation, accompanied by three specific images sourced from the internet, each distinctly depicting a type of bond, adding . Concluding its explanation, added a touch of , expressing, “I hope this illustration helps you” and prompting further engagement with “Please let me know...” depiction was even more rudimentary, presenting bond details in textual format instead of offering a lucid visual illustration. Such a choice reflected a deficiency in and diminished , even though the final assertion “Images and diagrams can sometimes bring these abstract ideas to life.” While the closing remarks of "Let me know" and "I can create more illustrated examples" hint at a desire for , the lack of an actual tailored visual representation undermines this effort. ChatGPT Reinforcement & Feedback Instructional strategy Personalization & Personable Touch BingChat’s Instructional Strategies Engagement & Interactivity Use of Analogy & Comparative Illustrations Personalization & Personable Touch Bard Instructional strategy Detail Depth & Content Recommendation Bard Personalization & Personable Touch Claude's Instructional Strategies Engagement & Interactivity Personalization & Personable Touch This paper is under CC BY-SA 4.0 DEED license. available on arxiv

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