AI Tools for Researchers: From Writing to Publishing Your Academic Papers

1. Research Video Intro: During my time as a medical student, right back when I was in med school, I had my fair share of experience with academic writing, and I had to conduct research multiple times for various different topics. Now, up until this date, I've been a corresponding author to three published research articles that I've published at PubMed, and I have assisted in both research and production of multiple other papers that have also been published on PubMed. So I clearly remember being a medical student, and having my fair share of academic writing and research to conduct. For the first two articles that I was the corresponding author, I clearly remember struggling for very minor stuff that could be easily outsourced and leveraged with the usage of artificial intelligence. Now, keep in mind that back in the day, I didn't know what AI was. I didn't know how to leverage the power of artificial intelligence for research, for academic writing. So you can imagine how impressed I was when I found out about the eight artificial intelligence tools that we'll be analyzing in this course right here. Ever since I found out about these tools that we're going to be analyzing in the course, ever since I've implemented them in my academic research, in my publications, it has been a complete game changer. Trust me, the whole process of performing research, collecting other articles, and writing manuscripts, also submitting manuscripts has been completely transformed. In general, research and more specifically, academic research is one of these fields that has been directly and completely changed. The introduction of artificial intelligence. And this course is if you will, your ticket to introduce yourself in all of these different ways that's going to absorb AI into your academic work. Now to give you a bit more context, in this course right here, we're going to be analyzing eight different artificial intelligence tools that have completely transformed my workflow as an academic writer that I wish I had when I was starting out. This course obviously isn't made just for doctors, right? This course and what we're going to be analyzing inside of these lessons apply to any scientific field and anyone that wants to conduct research on pretty much any existing topic. So thank you very much for being here. I'm going to see in the first lesson of the course. 2. The Class project: On the course, I'm very, very happy to have you here. Now, before we start with Lesson one, I just wanted to elaborate on the class project that you're called to complete by the end of this course right here. Now, the class project is going to be very simple and very basic, right, but it's going to also be very cool. So here me out. The first artificial intelligence tool that we're going to be analyzing is called Research Rabbi. Right? And you will see that research rabbit has a sequence on how we can perform research and how we can trace from one author to another from one abstract to another from one paper and manuscript to another, which is extremely cool. You're going to see it in the next lesson. So your class project is going to be to take a screenshot of your research rabbit interface and just show demonstrate us how you trace authors and how you trace abstracts and papers from your research, depending, of course, on the topic of your research. All right, so the class project is for you to take a screenshot, again, of the process of your research through research rabbit, pretty much the interface of the program. Applied obviously to your case, to the thing that you're researching about and submitting it in the class project description. I am very, very happy to see class project being submitted because it's just an amazing way to also connect with me because I'm going to be providing feedback into every single class project that you guys submit, right? So thank you very much for being here. See you in the first lesson of the course. 3. ChatGPT for Research: Everybody, and welcome to the first lesson of the course. I'm very happy that you're here. And in this lesson, we're going to be discussing about a very widely known and important artificial intelligence program, chat GPT. Now, more specifically, in the beginning of this lesson, we're going to be analyzing some general information about this program, right, about HGPT, some very basic knowledge that you need to know, and then we're going to gradually move towards the application of this artificial intelligence tool for students and researchers. How can we apply all of this potential power that there is in this program for our benefit as students and researchers? At the end of this lesson, we're closing with a test, so we're putting, again, this computing part of HGP into a real world test in which we're going to be applying, again, all the knowledge that we have in this lesson to this test demonstration. So thank you very much. Welcome to this course, and let's launch our PowerPoint presentation. So we come again to this introduction to HGPT and how we can utilize this amazing artificial intelligence program as students and researchers. Before we move into that, we need to know and understand what really is HGPT. So HGPT is an artificial intelligence language model developed by OpenAI. OpenAI is pretty much the company that developed HAGPT is proficient in natural language understanding and generation. So it understands and generate language as of course, an artificial intelligence language model. Okay, Tach Bi can engage in human like conversations with users, offering instant and coherent responses to a wide range of queries and prompts. Okay? This is very, very important to note, okay? It is trained on vast and diverse text data enabling to provide valuable assistance in various fields, okay, including education, research, writing, and problem solving. Okay, THV capabilities make it a versatile tool for students and researchers, and it revolutionized communication and knowledge sharing. Now, this is one of the most important sentences of this lesson, and I'm going to elaborate why this is in the next slide. So hATPT pretty much, as we said, engages in human conversations with users, offering instant and coherent responses, Okay, to a wide range of queries and prompts. And the keyword in this slide right here, ladies and gentlemen, is the word prompt because as a language model, okay, HHIPT the input that we give to JCPT actually pretty much 100% determine the output that HGPT will give us. So at this point of this lesson, we need to understand what a prompt is. Okay, and this image that I added right here is pretty much the search bar where we actually give the prompts to HGPT. So what is a prompt? Okay? And why do we need to understand what a prompt is in order to utilize the par of HGPT? So HHVT prompts are input queries or statements given by users or given by us to engage in conversations with this AI language model. It is pretty much the input that we're giving to this AI language model, right? And they can take the form of natural language questions, incomplete sentences or specific instructions which guide the AI's response. I'm going to see the specific instructions. Example, at the end of this lesson in which we're going to be pretty much simulating a historical data. So prompts, again, are the input that we give to hachPT. And hachPT has all the data of the world, okay? But in order to extract the data and extract the correct information that we need, okay, we need to give and ask the correct questions. Okay? So users can use prompts to seek information, ask for explanation or generate content tailored to their specific needs. If you can take something from the stat right here is the fact that the more structured and the more based your prompts are, okay, the input that you give to HGPT, the better you will utilize this tool as a researcher and a student. So the quality, again, and relevance of the AIs responses are influenced by the clarity and specificity of the prompts provided. So please, we need to understand what are prompts, why it is very important to provide the correct prompts, the correct input to HGPT to get the output that we want. So you need to remember before we move into the application of THP in students and researches, I want you to remember that HGPT is context aware, Okay, which means that it can retain information from previous interactions that it had within the same conversation. And when we launch a program, you're going to see that every time you type something, okay, it opens a new conversation with a program, you start new chats and every chat that we open can have a completely different theme. But within each chat that you have with JTPT, okay, within each interaction you have with this language model, JTPTs context aware. It means that it remembers pretty much what you told it, so you don't have to repeat yourself every time. Okay? So, in addition to that, okay, the prompt as we said, hugely influences the responses that we get. So the prompt is the input that we give, and it hugely influences the responses that we get. The way that a prompt is framed significantly impacts the AI's output. So users can fine tune the responses that they receive by adjusting the wording and tone of their prompts and sharing more precise and tailored answers. So I know and I'm pretty sure that you actually understood this because we mentioned it many times, but it is of key importance if we're discussing about what HAHBT is for you to know the value, okay, and the importance of actually delivering correct prompts. In addition to that, as students and as researchers, more importantly, as researchers, we need to know that there is potential bias, okay, in the responses that we get from JHPT. And despite its remarkable capabilities, HTPT may sometimes exhibit biased responses, okay, due to the data that it was trained on. JTP might be an artificial intelligence language model, but it was developed by people, and people are biased. Okay, so users need to be aware of this and carefully frame prompts to avoid reinforcing any existing biases. Okay? So let's move to now the second category of the stats arque, the second subcategory of the stats, which is what are the actual applications of this tool in research? Okay, how can JachVT help me in my research? Are there any applications of this tool in research? The answer is yes, they are. And actually, there are many. There are much more than all of those applications that I mentioned right here. But Jahv to give you a very brief explanation can help in instant information retrieval in simulation modeling as a study I can help with coding and technical support. It is, of course, a writing assistant as a language model. It can help us with literature review with automation of repetitive tasks with data analysis and ID generation. Those are the most important and widely known applications of HGPT again in research. Okay, so let's put all of those applications into practice. Let's actually have a real world practical scenario while utilizing again the power of JGPT to our advantage as researchers. So let's say that you're a student, or a researcher, interested in history and you want to delve into the minds of prominent historical figures to understand their viewpoints on specific events or issues. Okay, the coolest thing here is that Jajbit can actually be employed, okay, to simulate conversations with these figures and extract valuable insights. I don't know if you understood this, but Jajubt can actually answer and you can chat LTHPD is one of those characters that you want to extract information from. So to get more specific here, the step one to do this is to actually choose a historical figure, right? So let's choos a historical figure, a well known historical figure, for example, from any era or field of interest. For instance, let's just pick Albert Einstein. So let's try to make JachPt simulate, okay, that it is Albert Einstein, and let's have it respond to our proms as Albert Einstein. So this is, for example, a prom that I gave hachPt in my chat, and I said, answer to my questions and engage to the conversation. As if you are Albert Einstein. And JZPT answered, of course, I'll do my best to answer your questions and engage in the conversation as if I were Albert Einstein. How can I assist you today? So, the second step here is to formulate, if you want to conduct research, right? Form a series of questions that you would like to ask Albert Einstein. And these questions focus on his perspectives and opinions regarding specific topics, okay or significant historical events. So pretty much any question that you have to ask Albert Einstein from for your research, right, you can just formulate a series of questions and go ahead and ask JTP, which has now taken the role of Albert Einstein. So, for example, you can ask, What were your thoughts on the theory of relativity when you first proposed it? Or how did you view the role of science in society during your time? Or what were your reflections on the political climate during World War two? All of those questions you can ask Albert Einstein, and now JCPT has pretty much gotten the role of Albert Einstein. So we can ask JAGPT. So I went ahead and actually asked, what were your thoughts on the theory of relativity when you first proposed it? And guess what? Jach Pit analyzes all of the data that exist, Okay, on the web about Albert Einstein in milliseconds, right? And then it formulates an answer based on all of this data that exists. In the world, it formulates an answer and gives me an answer just like Albert Einstein would give me. It answers, Ah, the theory of relativity, one of my most significant scientific accomplishments. When I first proposed this theory, I was both excited and nervous, excited because I believed that it could revolutionize our understanding of the universe and Axis because I knew it would challenge some of the fundamental ideas of classical physics. Okay? And it goes ahead and actually answers as if it was Albert Einstein. So how cool is that, right? And the next question that I ask is, for example, what were your reflections on the political climate during World War two? Okay, and it answered the political climate when World War two was a source of deep concern and distress for me. As a German born physicist who had witnessed the rise of Nazi ideology, I was well aware of the devastating consequences of the war and the atrocities committed by the Nazi regime. So Again, you can extract information, and this is correct information again sourced from all the datasets that JTB has access to, right? Then this is extremely cool. So the next step is to pretty much engage with HJBD and ask more questions based on the fact that it answers like Albert Einstein and you need to your research. So we utilize JGBT to stimulate, to simulate the conversation with Albert Einstein. You can input your questions and explore the AI generated responses as if you were actually engaging in a dialogue with the historical figure himself. So, for example, I asked again, what was your biggest inspiration for pursuing a career in physics, and how do you manage to stay motivated during challenging times? Okay, again, based on the information that exists on Albert Einstein, it gives me a simulated response. So my biggest inspiration for pursuing a career in physics came from a combination of curiosity about the natural world and a desire to understand the underlying principles governing its behavior. As a child, I was fascinated by the laws of physics and the way they could explain the phenomena I observed around me, ya, ya a so the rest, Okay, you can read by yourself. So how good is that? The final step if you're conducting research is obviously analyze the responses that JGBT or Albert Einstein gave to us, right? So we need to evaluate those responses, considering the historical accuracy, coherence, and relevance to Albert Einstein's known beliefs and viewpoints. So again, as we said, HAHPT at some point is biased, it is created by people, so it is not bad if we're conducting research to actually cross check everything that we get from this AI tool. So this analysis will help you understand how JZPT can be utilized as a tool for historical research and gain insights into the perspectives of influential figures. So to conclude, okay, HTPT is an artificial intelligence language model, which as we said, revolutionizes communication through human like conversations with users. Students benefit from HGPT by receiving academic support, instant information retrieval, and writing assistance because at the end of the day, HTP, as we said, is a artificial intelligence language model. Okay, researchers, on the other hand, leverage HGPT for literature reviews, idea generation, data analysis, and task automation, and pretty much anything else that can be generated again through text. Okay, prompt engineering plays a crucial role, as we said, in shaping AI's responses, and users must be mindful of potential biases. Okay? We really highlighted the importance of delivering and giving actually the correct input, the correct prompt to HPT, to get the tailored answers that we're looking for. And obviously, if you're a researcher, you need to know that HPT might be potentially biased, so we need to cross check every factor we get from this HPD artificial intelligence model before we actually submit a publication. So embracing the AI language model responsibly opens new avenues for collaboration knowledge sharing and transformative advancement. Okay, so let's harness technology to create a brighter future. So this was the lesson on HGPT. I hope that you got some information out of it, some very new facts perhaps that you learned. I think the Einstein example was very, very cool, the fact that AGPD can actually simulate a conversation with a historical figure that could have passed away from one of the data that it can retrieve from the web. Okay, the more data, of course, we have on a person, the more accurately JAGPD is able to simulate the conversation with and in the next lesson, we're going to be discussing about research rabbit, one of the most powerful artificial intelligence research assistants that we can utilize for our research. So thank you very much, I'm going to see you in the next lesson of the course. 4. What is ResearchRabbit: Welcome everybody to the second lesson of the scores in which we're going to be discussing this amazing research assistant, okay, research rabbit. So I'm very happy that you're here. After we're done with Chachi begin, we've analyzed the most basic and widely known artificial intelligence model. It's time to dive deeper into the research process and how to utilize the power of artificial intelligence again, as an assistant, how to utilize as an assistant. For our research. So this is exactly where research rabbit comes into place. And again, we have many different things we're going to be analyzing in these lessons about research rabbit. We're going to start this lesson in a general ideological approach on what is research rabbit and how we can utilize this. As researchers, then we're actually launching research rabbit, and on real time, I'm going to be showcasing how to utilize this amazing tool. And finally, we have another a case demonstrative scenario in which we're going to demonstrate the power of research rabbit and how it can be utilized again for our benefit in research. So I'm very happy that you're here. Let's start with the Spar for presitation and let's analyze what research rabbit really is. 5. ResearchRabbit Main Features: Right here is the logo of research rabbit and we're going to start this presentation with analyzing what is research Rabbit. So Research Rabbit is an artificial intelligence powered platform that assists users in various aspects of research process, making it easier and more efficient to conduct high quality studies. In other words, Research Rabbit is a research assistant. It aims to make research process more manageable, efficient and organized for students and researchers by leveraging the power of artificial intelligence and providing a centralized platform for various research related tasks. Those tasks usually are citation, author management, navigating and networking with more authors, okay, seeing how different manuscripts are connected through different authors, and it provides a visual representation, again, of how all of those manuscripts, all of those research articles are interconnected through a network of aors, okay? So what are the applications of research rabbit in research? Okay? Of course, there are various. Okay, we have citation management, research idea generation, data analysis, and visualization, collaboration and teamwork, literature review assistance, okay, and plagiarism checker. So we get all of those possibilities inside research rabbit in more detail, okay? Because I think that the information Abels one are a bit vague. Tse platforms helps users, okay, find relevant academic papers and articles, saving time and effort in conducting literacy reviews. So again, it is a data visualization AI model rather than just a virtual assistant, right? It assists with citation management, making it easier to keep track of references and generate citations in different formats. And again, it includes a plagiarism checker to ensure the integrity of research work and avoid unintentional plagiarism. So except for the fact that it is a artificial intelligence research assistant, Okay, it helps with data visualization, and it also has a build in plagiarism check, which is, again, another just layer of assistance in your research. This platform can suggest can digest research ideas and topics based on the user's interest and academic focus. So the more that you engage with research rabbit, the more again, based it is when it comes to suggesting research ideas. In addition to that, Research rabbit may support collaboration and teamwork enabling users to work together on group projects more efficiently and effectively, and you can discuss this and I can show you how this is done in the real world example on how to use research rabbit. So depending on its capabilities, it might offer also data analysis and visualization tools to help interpret and present research findings. This is one of the most important details about research rabbit, the fact that it helps visualize, okay, research. So if you could summarize this in one sentence, we could say that Research Rabbit is a very, very powerful artificial intelligence research assistant. So enough other words, let's launch research rabbit. Let me show you in a real world, again, example how I would use research rabbit and how we navigate through this program. 6. ResearchRabbit Website Navigation: After we have logged in in Research rabbit, this is the interface that we have. And of course, in order to visualize data, we have to input some data. So the first thing here is, as you can see, we can add new collection, new category or connect to Zotero. Okay. But in this case, the first thing we're going to do is we're going to add a collection. Okay, so let's name this collection. For example, let's say we're conducting research into the impacts of let's say, smartphones into youth. So let's write smartphone mental health. Okay, health. Great. So this is our smartphone mental health collection. Now, we have the ability to add papers to this collection right here. So let's actually add papers, and this will pop up. Okay, this bar with the search bar with pop up, and we have the luxury to actually input some keywords, Okay, to select some papers that are relevant into the research that we're conducting and it's going to help us visualize, again, the interconnection between all of those papers. So let's write some keywords because I don't have a specific paper in mind to add the exact title or Doi. So just write some keywords. So let's write smartphone. Okay, teenagers mental health. Okay. Impact. Strike those keywords, and let's search actually what we got. Now, of course, Richard Rabbit has access to all of the different journals that have published with those keywords. We're going to see impact of phone mobile game addiction on stri Lankan teenagers or empirical study on game design for using smartphone usage amongst young children or comparing all of those depression scores again, employed and unemployed mothers of children. So let's add for example, this, we usually add about five different manuscripts to our collection and actually delete impact. Let's search like this, smartphone teenagers mental health, the relationship of smartphone addiction with teenagers mental health in vocational high school, okay, in Indonesia. So let's add this to our collection, mental health, literacy of Internet gaming disorder at the store collection. Okay, and we add the more we add pretty much, the more okay papers we add to our collection, the more based and correct data the more data pretty much the program will give us. Okay, so we've added all these to collection. Now we can close this window, and we have all of the different papers that we have added right here. So one, two, three, four papers we have added. So now this, as you can see, window has popped up. And once we select one of the papers, we can first of all, read the abstract. We can download the PDF. So again, this is the data visualization that we were talking about, okay? We can pretty much read a very superficial part of the abstract. Obviously, we can read the whole paper from here. We can unload again the PDF. We can see the different keywords that those people have worked on, and on top of that, this new window has popped up, which is exactly the visual and the data visualization that we talked about. So once we press those buttons, we have many buttons we can push. Okay, so similar work, these as suggested authors. So pressing these authors, you can see the different authors that have contributed into this paper right here. So those are the authors. And as you can see, you can see this networking of individuals, which is very, very important and very, very interesting. In addition that, we can check suggested authors, so different people and all of their citations. So for example, this paper right here, Research Rabbit suggests me this author right here. We has 1,700 citations. And once we again click on this, we can see his published work, we can dig in deeper and deeper into this network of authors. You can see. We now have visualized all the published work of this suggested author that was suggested from this manuscript right here. The same thing can be done with different papers, right? So as you can see, let's click on this. We have citations to check, so we can actually check the different citations. So those were the articles that were cited, again, the manuscripts that were cited for the conduction of this research right here. So we can easily see again the other. Again, manuscripts, we can read their abstract and again, similar work. So this is just a very easy way to visualize a networks, to visualize networks of cited manuscripts, and again, to extract information for our research. So this is pretty much how the interface of research drive it works. I very superficial we demonstrate how we can start a collection, right? We can start a theme of research, and we can start actually conducting research and knowing more about the papers that we're interested in. And now let's move into a real world example again, in our PowerPoint presentation. 7. Research Rabbit Demo Case: Again, let's put the computing power and what we have learned about research rabbit in this lesson right here to the test. So the scenario that we're going to be going through right now is to conduct a literature review and manage citations. So the objective is to showcase how research rabbit assists in conducting a literature review and managing citations for a research process. So let's go step by step on what I would do, for example, again, to complete this object. So the first thing is to access obviously research rabbit. We log in to a research rabbit using, of course, our credentials, and then we define the research topic. So we choose a research topic that we want to explore. For example, as we said, the impact of social media on mental health in adolescents. Okay? So as you can see, this is the interface. We have created a new collection which is named the Impact of social media on mental health in adolescents. Okay, we've been through the program, we've been through the product, interface, and you can see, you can remember how we created this new collection. So the next thing is to obviously click on the ad papers button. Okay? The next step is to find relevant literature based on this category that we have created. So we use search rabbit search functionality to find academic papers and articles that are related to our research topic. As we said in the demonstration, we need to save at least five relevant sources. Okay, to reach a Travit library to have the most accurate data coming back to us again from this artificial intelligence model, because as we said, when we're dealing with AI, our prompts and our inputs and the amount of information that we give to the program is completely related to the information that we're going to extract. Okay, so this is the next step. As we said, it says, add a paper you know and love, and we can either search with a title the Doi, the PMID or keywords of This paper. So in this case, just as in our demonstration, I added some keywords, and those keywords are social media, mental health, and adolescence, right? And after pressing search, we have all of those different articles Okay, all of those different papers, manuscripts, you canall them whatever you want, that we can add to research rabbit. So the third step after that is obviously to review and summarize the literature that we have. So read the saved sources and use research rabbit note taking feature to summarize the key points, findings, and relevant quotes from each source. So, what we're going to do, as we said, we can select. We got all those papers visualized right here. And once we select the paper, you can see that we have, as we said, the abstract right here and many other choices depending on which papers we have, for example, to watch the references, to see the authors, to visualize any other suggested authors and how they're interconnected in those network. The first step is to generate citations, and for each source, you can use Search rabbit citation management tool to create accurate citations for our preferred citation style. So as we said, when we go to all references, we can see those are the references. Research rabbit actually makes it very, very easy for us to cite those references. In additon to that, I think this is very cool. You can see also the network of references and how all of those documents are intertwined together. So I think this is one of the most valuable and coolest features of this artificial intelligence program. The next step is to organize our research materials. So we create folders or tags within research rabbit, so it gives us the opportunity to create folders and tags to organize the saved sources and research note that we based on different aspects of our research topic. So in more detail, we can pretty much add this to more collections and we can have subcategories to be as organized as possible because obviously a research obviously adheres to a wider category, but we have many subcategories within every time we research a specific topic. So for example, the impact of social media and mental health and adolescents have many, many, many, many, many subcategories, and this is what we're doing right here. The final step, okay, those do are optional, but we can have data analysis and data visualization, which research rabbit really, really helps us do that. Okay, so sometimes research rabbit offers data analysis capabilities. Okay, we can use sample dataset to perform basic data analysis relevant to our topic. And we also have data visualization. Again, this is optional to the program. So this is pretty much again, the cool feature of research rabbit, the factors we analyze and visualize the data in front of our eyes. So in conclusion, as we said, Research Rabbit is a powerful artificial intelligence driven platform that simplifies and enhances the research process for students and researchers by offering valuable tools for conducting literature reviews, managing citations, and organizing research materials efficiently. In other words, it is a research assistant, as we said, that helps us really visualize data that could be very hard to visualize, otherwise, using conventional methods. So this pretty much concludes our lecture, our lesson in research rabbit. In the next lesson, we are going to be discussing one of the coolest programs that have implemented the power of artificial intelligence in literature review and research, which is going to be had PDF. So thank you very much, and I'm going to see you in the next lesson. 8. Introduction to ChatPDf: Going to revit it to the third lesson of the scores. I'm very happy that you're here because actually the topic of this lesson is a combination of the two previous artificial intelligence tools that we analyzed in the previous lessons. So in this lesson, we're going to be disussing about hat PDF. And the coolest thing about Chat PDF is the fact that it has a live chat, just like JGBD and it is also a research assistant like research Rabbit. So it is the best of both worlds, and combine the usage and the implementation techniques of the previous to our facil intelligence tools, it is easier for us, again, which is combined in hATPDF. It is easier for us to understand what this tool does and utilize its fullest potential. So in the stat right here, we're going to start by analyzing in some general information, some introductory things about ATPDF to understand pretty much what it's all about. And then we're diving into the implementation of hat PDF into our research process. Finally, we are, of course, finishing this lecture in the normal way that we finish lectures in this course right here with a test, a real world example on how to utilize the power again of hat PDF. So thank you very much for being here. Let's launch our presentation, let's discuss about this beautiful and very, very useful artificial intelligence tool for our research. 9. ChatPDF Main Features: Come again this power point presentation regarding hat PDF. We're going to start analyzing what is hat PDF. So hat PDF is an innovative tool that combines the convenience of real time chat with the functionality of a PDF document. It allows students and researchers to collaborate, share and discuss PDF files in a live chat environment. So again, as you said the first point, it combines the convenience of real time chat, right, just as we have in JGBD with the functionality of a PDF document. If you will, hat PDF is HGPT after it has understood the PDF document that we're inputting it, right? Because you can't input the PDF document as a prompt in GBD, but this you can do actually in ABF and we can show I'm going to show you how you do this in hat PDF. So with CRPDF, users can highlight, annotate and comment on specific sections on the PDF. Fostering interactive discussions. Okay, this tool enables seamless file sharing, making it easier to exchange research papers, articles, and study materials. And again, students and researchers can leverage hat PDF to engage in virtual study groups, peer reviews, and academic discussions, enhancing their learning and research experience. So this is another huge point with hatPDF. It does not only provide you with a live chat regarding the PDF that you have inputted, but it is also it also again enables those this amazing file sharing capabilities. And again, it is easier to exchange research papers and study materials amongst students and researchers. So here comes the question that we have in every single tool that we analyze. What are the applications, of this tool of hATPDF in research. Are there any applications of JTPDF in research? Obviously, there are many applications, and we're talking about virtual journal clubs, real time collaboration between researchers, ID generation and brainstorming, the exact same application that HPT had, if you remember, in a research, because, again, ID generation and brainstorming can be done by a language model, and hatPDF is an artificial intelligence language model just like HGPT. And again, we have peer review and feedback, data sharing, analysis, and again, as we said, real time collaboration between students and researchers. Now, in more detail, okay, researchers can collaborate and discuss PDF documents in real time, enabling, as we said, seamless exchange of ideas. And hatPDF simplifies the peer review process if you're a peer reviewer by allowing reviewers to provide feedback directly within the PDF document that we input as a prompt to this artificial intelligence language model leading to quicker and more effective review cycles. 10. Chat PDF Test Case: Let's actually put hat PDF to the test in this example right here. So let's say it's a scenario, okay, that you're conducting research on the impact of smartphones to the mental health of young people, as we said, again, the same exact scenario that we did in Research Rabbit, and you want to fastly review and note the important points of a six page manuscript that you found. So again, you conduct research in the impact of smartphones to the mental health of young people. And again, you need to review fastly a vast amount, a big amount of pages in a manuscript. So the first step would be to open, obviously hatPDF and import the PDF file that you wish to analyze within the program. This is how the interface used. The first looks. The first page of hatPDF is this page right here, and you drop a PDF file in which you want to engage with this artificial intelligence language mole. So after we have dropped a file kay, we need to review the introductory text texts that have been generated automatically by the AI program. So let's say that we inputted this again, manuscript right here, which titled smartphones social media use and youth mental health, right? So in the left side of the page, as you can see, we have the manuscript of different pages, the PDF document that we have inputted on the right side, we have the chat with Chat PDF. So as we said, the first step was to review the introductory again, information that it gives us regarding this PDF document that we've inputted. So let's say we input this PDF. What chat PDF told us is welcome to this helpful PDF guide. Okay, while it addresses a serious topic, we hope that the information provided will be useful in promoting mental health and well being among youth. Okay? Here are three questions you might have about the file. So what are some specific ways that the smartphone social media use maybe contributing to mental diseases among youth Okay, are there any particular interventions or strategies that have been shown to be effective in addressing mental health concerns among young people? So again, it gives us some questions that we could ask. It gives pretty much some prompts, right? So questions, the input that we could ask to extract some cool information regarding this program and the PDF that we have selected. So the next step is to start engaging with this AI chat model to collect the data that you wish. So here are some useful prompts, okay, because as a language model, we said that we input prompts to get the information that we want. Here are some useful prompts that you could use. Again, utilize the power of hat PDF. So when it comes to abstract summarization, those are some abstract summarization prompts that you can use to help again chat PDF summarize the abstract and make you understand faster and easier what you're talking about. So you could say, please provide a concise summary of the papers abstract. Okay? This is a prompt, again, and this prompt is tailored to receive the information that we want regarding abstract summarization. Another prompt that we could use is, for example, summarize the main findings and contributions mentioned in the abstract, or what are the key search objectives and results outlined in the abstract. Again, those are prompts, okay, that you can copy and paste to chat PDF to summarize the abstract, again, of the PDF that you entered. Okay, so let's say, for example, I said, summarize the main findings and contributions mentioned in the paper. Okay? And I said he said, This paper discusses the potential negative impact of social media and smartphone use on the mental health of the authors review the current evidence on the topic and suggest that prolonged use of social media and smartphones is associated, so it pretty much again, summarized the main findings and contributions in this paper. So how cool is that? In chat PDF, the input that we give, okay, the main prompt that we give is the whole PDF document, and we have a chat, a real time chat, again, regarding this PDF document. So this is very cool. The next thing that I ask, for example, what are the key research objectives and results outlined in the paper? And it goes ahead and answers. The key research objects of the paper is to review the current evidence on potential negative impact of social media and smartphone use on the mental health of youth. The authors aim to identify the specific factors related to social media and smartphone use that may contribute to mental health issues among youth, as well as to provide recommendations for physicians, patients, and caregivers on how to mitigate these negative effects. So again, more interaction, as you can see, this artificial intelligence language model is trained to provide a bigger response, bigger responses in general regarding to our questions. So this is very, very cool. And the next step is, again, some more prompts that you can use after moving from the abstract to the main body, again, of the paper. So when it comes to introduction and background, you can say, give me an overview of the introduction and the problem statement addressed in the paper, or what is the motivation behind the research conducted in this paper or briefly explain the background literature and related work mentioned in the introduction. For example, we have more proms regarding methods and experimentation. Describe the experimental setup and methodology used by the researchers. Or what are the data sources and tools utilized in the research or summarize the key steps of the experiments conducted in the study. Many many proms or many proms that you can use, and you can actually come up with your own prompts. Those are just some prompts that I'm giving you for free, and you can utilize if you want to work with Chad PDF. We got more prompts, in results and discussion than conclusion and contributions in impact and significance. Let's say we want to, let's say, review the impact and significance, right? And we need to ask some prompts regarding the PDF that we have. So you say, access the potential impact of this research, okay, on the specific community or real world applications. Or why is this paper significant in the context of the broader research area. So again, many, many prompts, take those prompts, take a screenshot of this lesson right here of this slide because those are some very helpful tools to understand if you want to faster absorb information from the PDF document that you have inputted in chat PDF. So the fourth step is to extract information that you wish and note it in a Word document. So, for example, I asked, give me ten. Okay, give me the ten most important bullet points of this paper. This is one of the biggest assets of Chart PDF, right? It can summarize fast la period document that you've given. As I said, give me the ten most important bullet points of this paper, and those are the ten most important bullet points. Okay? The first one is social media and smartphone use are associated with poorer mental health outcomes among youth. Okay, prolonged use of social media and smartphone can lead to increased rates of depression, anxiety, and sleep disturbances. Okay, and eight more key points on this topic. Okay, so in conclusion, as you said, hat PDF is an innovative tool that combines the convenience of real time chat with the functionality of PDF documents. It allows users such as students and researchers to collaborate, share and discuss PDF files in a live chat environment. And it streamlines streamlines the research process. It enhances collaboration and promotes interactive discussion, making it a valuable tool for knowledge exchange and academic pursuits. So this was ladies and gentlemen, Chad PDF, as we said, a great combination of HTPT and research rabbit because JTB is an artificial intelligence language model, and research rabbit is more of a research assistant. So the combination of two is perfectly demonstrated in CHAPDF. Now it is time to move to the next dozen of scores in which we're discussing this amazing artificial intelligence tool, trinka.ai. So I'm going to see you in the next dozen of the scores. 11. Introduction to Trinka: Ladies and gentlemen, welcome to this fourth lesson of the scores. In this first lesson, okay. So, ladies and gentlemen, I'm very happy that you're here. Welcome to the fourth lesson of the scores. As we said, in the conclusion of the previous lesson, this isn't really here, we're going to be analyzing this amazing artificial intelligence program, okay, which is called Trinka. Now, what Trinka is, okay, I won't say that it's the best world from all the other artificial intelligence programs that we have used, but it proposes a completely different thing, o, and it solves a completely different problem, okay, that isn't solved that much from the other programs that we discussed previously in the scores. What Trinka does is that it's not only an artificial intelligence language bottle, but on top of that, it is generative artificial intelligence language model, which means that it has an input in the grammar, in the spelling, in the phrasing of your articles. In addition to that, it can analyze all of the information and the character that you want to deliver in your articles, again, your manuscripts, and it can propose and suggest different changes you can apply in order to apply, again, your research papers into journals. So this might sound confusing to give you a short explanation on how this status is going to go, we're going to start with an introduction on Trinka we're going to point out the most important tools of this program of this software. And after that, we are launching Trinka in a real world scenario in which we're going to be going through everything you need to know when it comes to this program. Finally, just like in every other lesson of this course, we're closing this lesson right here, this lecture with a real world test scenario again to test the capabilities of this amazing program. So after the induction, let's move into the presentation. 12. Trinka Main Features: Again, is the logo of Trinka. Let's move into actually discussing what Trinka really is. So as we said in the introductory video of the starting Trinkas the world's first grammar and language enhancement tool, which is custom built for academic and technical writing. So this is a tailor made artificial intelligence tool again, for academic purposes. It is a next gen grammar correction and language enhancement. Writing assistant, right, which is designed for academic and technical writing. It also stands out by working with the author and going beyond grammar and spelling checks to ensure holistic language enhancement. So again, it doesn't only assist, again, researchers and students, but it also enhances what we have already created. This is why in the introduction of the course in the fifth dozen, I point out that it is a generrative, okay? It generates it is a garrative AI language model. So it stands out by working with the author and going beyond grammar, as we said, in spelling to ensure holistic language enhancement. It refines the tone, delivery, and phrasing of the researchers, writing to match academic writing conventions and best practices. So again, the researcher can focus more on ideas rather than grammar, which is boring and can be with Trinka. So one of the main again, features of this amazing artificial intelligence program. The first and the most high selling feature of this program is its powerful grammar and spelling checks, right? It knows how to check for grammatical errors for spelling mistakes. This is very easy, obviously, doesn't require that much of computing power. Okay, so again, as we said, academic writing needs to be clear, concise, formal, objective, and readable. So again, Trinka makes sure that all of those boxes are checked in your writing. In addition to that, it provides enhancements for publication ready writing because in some cases, some journals, okay, in order to accept your manuscripts, your submissions, they need to be written in a specific way. So what Trinka does is that it analyzes the way that you write a manuscript and it enhances it to meet the standards of different journals. In addition to that, we have a plagiarism check tool. This is very common on those AI tools. So again, we have a high quality plagiarism check with the most advanced text similarity detection algorithm, and this is actually true. It is very, very good how well the plagiarism text in Trinka works. And again, we also have this auto file edit, which pretty much Okay, we apply powerful language revisions in one go in the manuscript that we submit and we want to analyze with Trinka. On top of that, okay, we have publication readiness check. So again, it analyzed all of the different journals that your manuscript could be submitted to, and it actually proposes, which is the number one best journal to submit your article, the number two best journal, so it gives you just a visible again, map on the different journals that you can apply your manuscript to. And, of course, we have these citation checker, so it checks how relevant your citations are in your document. Okay, how strong they are, how biased, how good they are to use. Okay, if they're biased, if they're poorly cited. So all of that, we have a citation checker tool inside Trinka. In this that we said, we have the journal finder, which based on the way that your manuscript is structured, we can find different journals and propose different journals for you to apply. And finally, we also have the consistency check, which pretty much strengths your communication, and it pretty much helps you, again, eliminate any inconsistencies if you have in your writing. This is also part of the grammar and spell check. So enough of the introduction, and again, after we have outlined all of the different tools inside Trinka I think that it is time to launch a program. I'm going to show you in real time how to navigate through this program. So I'm going to see you 13. Trinka Website Navigation: Here we are ladies and gentlemen, inside the Trina program. This is obviously the online version of the artificial intelligence language model. And as you can see, right when we launch this program, we can pretty much choose to upload a new file. So once we press this, okay, it creates automatically a new file which we can process inside the document. So this is the first thing that you want to do if you're axing this program. Now, I've already created the file that I want to demonstrate, but for demonstrating reasons, okay, I want to stay in this window right here. So first, regarding that you use Trinka, this means that you actually have a very rough, you know, version of a manuscript that you want to make better with Trinka. So now you enter the title here, so title of the manuscript. Okay, Okay, let's change this title of the manuscript, right? And the most important thing is that you need to choose your story guide and the paper type. So first, say is it an academic writing or of general writing? Let's say academic writing. Okay, what is our subject area? In my case, I've actually submitted an article that has been accepted in a journal. Okay, so my subject area is cardiac surgery. Okay, so I wrote cardiac surgery here, and when it comes to style guide, I think AMA is perfect. When it comes to paper guide, my article was a case report. So the more information we give in general to those artificial intelligence model, the better results we can get. And this is exactly what it suggests right here. It says get better results, again, and more personalized suggestions based on the information that we give. So this is why after pressing save and proceed, we have okay, the text which we can paste. So let's go back, actually, and let's open an article that I have already submitted to Trinka. So this is, for example, a case report that has been submitted in the journal of carditratic surgery, and it was actually a case report that I have submitted and I have written, and we have all of those different suggestions, again, to improve grammatic. So Grammar, for example, let's say operation, I say, eventually, he consented and he was transferred to the operating room. This is wrong, it is it changed actually operation room to operating room. So this, for example, a change that was applied. Okay, for example, right now, it says the ventricular, change it to ventricular. And once I press this, the change applies. Now, the thing that I want to note here is that how to access the different tools that we discussed in this lesson right here. So all the tools can be accessed from here. And as you can see, we have the consistency tool, the publication check, the citation checker, the plagiarism check, and the journal finder. So let's go, for example, to the journal finder. Okay? Go to Journal finder. Okay? And this is the results that I got after I have underwent through the journal finder. So let's see my results. And based on the abstract that I gave, and I pasted my abstract in the search bar. So TwinkA suggests the annals of thoracic surgery, okay, for my article. I pretty much can mention you the He index, the site score, the impact factor of the journal, if it is possible. Also, curious and rank three, the BMJ case reports. So all of that. And once you press the back button, we can go back. And make a check all of the other again, tools right here. So this is very cool because we have the manuscript. The manuscript can be changed obviously because this is a document in which we can write. Okay, so we can have a real world, okay, changes to our documents. We can apply the changes that are proposed in this part of Trinka. And again, we can use all of the different tools, all of those different tools, okay, to change our manuscript. So now that we're familiar with how Trinka used, it is time to put Trinka to the test in a real world scenario. 14. Trinka Test Scenario: Now let's put again all the knowledge that we got out of this lesson, again, and the implementation that we did in the actual website of Trinka to the test. Let's say, in this test scenario, you have a rough first draft of a paper that you're considering to submit, and you want to have it checked with the assistance of Trinka. And those are the four, again, landmarks that we're going to check with Trinka. We're going to conduct a plagiarism tech check. We're going to do publication readiness check, citation check, and the journal finder check. So the first step is obviously to upload and create a file on Trinka. We discussed on how we do this. We add the file name, the document type, and once we add the document type, we can have our subject area, our language preference, our style guide, and our paper type. And the more information, again, we give to the program, the better outcome and the better information you're going to give us back. Okay, it all depends on the prompts that we give to receive the correct and valuable information. So after that, once we have created, again, a file or Trinka, we click on the plagiarism check button. And we have all of those different again, things to check grammatically, and we click on the plagiarism check button. And once our file has been processed and checked for plagiarism, this is the window that pops up on Trinka. So for example, my file actually had a 60% similarity detection after the plagiarism check. Okay, 20% out of the 60% is through Internet match and 60% out of that 60%, so a smaller percentage was from paid publication match. So again, 68 words matched with top one resources that was checked with Trinka, so this is very important to keep in mind. The next thing is to click on the citation check button, okay, because this is the next step again of our process. So after that, Trinka evaluates your citations, your references, and it gives us an analysis overview. So we or retracted. Again, citations. Okay, one citation that might have journal bias. Okay, six non standard citations and 13 citations that were poorly cited. And it gives you, again, a score depending on your citation. So this is very, very interesting and very few artificial intelligence model can assist you that far into your research process. So this is very, very cool. Next, I'm going to move into the journal finder button. So once we click the journal Finder button again, which is on the right side, as we said, of our screen where we're accessing Trinka you can see that we have all of the different results, all of the different journals that we can apply again, to have our manuscript published. So the first journal is, for example, the annals of thoracic surgery. Okay, the second is curious. And the third is the BMJ case reports. And again, those are all journals that Trinka actually suggest me to pretty much publish my literature that I submitted in this artificial intelligence model. So this was pretty much Trinka. So in conclusion, it is a next gen grammar correction and language enhancement writing assistant, which is designed for academic and technical writing. It provides valuable insights on manuscripts that are ready to be submitted, such as plagiarism check application readiness check, citation check, and proposes the most appropriate journals to publish each manuscript with the journal finder tool. So this was Trink, again, one of the most powerful artificial intelligence models that we have analyzed up until this point in this course right here. Now it is time to move to the next artificial intelligence tool for students and researchers we're going to be discussing, which is consensus. So thank you very much, I'm going to see you in the next lesson. 15. What is Consensus: Welcome everybody to the fifth lesson of the scores. I'm very happy that you're here. And in this lesson, we're going to be analyzing the power of an amazing artificial intelligence tool, which is called consensus. Now, we're going to dive deeper into what consensus is in the slides that will follow in this lesson right here, but in a very brief case, in a very brief explanation, consensus is an artificial intelligence tool that utilizes the power of artificial intelligence to access a huge dataset of publication and research articles and provide us with evidence based answers to any research questions that we have. So again, I'm very happy that you're here. Welcome again to the fifth lesson of this course, and let's dive into analyzing what consensus is. 16. Consensus Main Features: Come again into this lesson in which we're going to be analyzing consensus. So let's start with analyzing what actually is consensus. We've dived very briefly into the introduction of this lesson towards consensus. So let's now dig deeper. As we said, consensus is an artificial intelligence powered search engine which is designed to take in research questions, and find relevant insights with research papers and synthesize those results, Okay, using the power of large language models. So pretty much we input questions that we have regarding research, and it gives personalized and evidence based results. Is main function is to provide accurate and real time insights, Okay, by aggregating information from diverse sources. And huge emphasis here in the fact that provides real time insights, right, because it is always updating on real time applications that are uploaded into those datasets that it has access and gives us again information from all of those diverse sources. And again, the service uses advanced algorithms and natural language processing. To interpret unstructured data, and generate meaningful patterns, trends, and sentiment analysis. So what consensus pretty much is is that it could be characterized as a research assistant, okay, but it assists us. It gives us results which are evidence based, again, based from information that it has from all of those diverse sources. Okay? So Consensus, artificial intelligence, assists in decision making processes by presenting data driven recommendations and predictions, Okay, helping our organization to make informed choices and respond promptly to the changing market conditions. And this is a huge point that we said that consensus is updated on real time. On top of that, facilitates collaboration within teams, and it allows teams to share data insights and analyzes fostering a more data driven and informed approach to business strategies. So yes, obviously, consensus has a file sharing model in which you can share the answers as we will see in the demonstrative case of our research. So this is pretty much, how the consensus search bar works. You can see right here it has evidence based answers faster, and you ask questions in the search bar, and it pretty much gives us, again, evidence based answers while utilizing the power of artificial intelligence. So in other words, okay, to take a recap in the introduction of what consensus is, it is a search engine. It's pretty much a search engine just like Google that uses language models to surface and synthesize claims from academic research papers. Okay, results are cited and cross check from actual published studies. This means that all of the results that we're going to get from consensus are published in journals and they are legit. Okay, so who is consensus for? Who can benefit as a person with consensus? So the first thing is obviously students. If you're a student and you're trying to find evidence for your paper, consensus is a great way to do that. You could argue that you could also Google something, but Google the Google results are not always evidence based, and they're not always based on actual publications. But consensus is, and this is where consensus stands in the artificial intelligence tool market. Okay, researchers also can hugely benefit from consensus, right? Because we easily conduct literature reviews. While using this artificial intelligence model. Okay, clinicians, obviously, they can really benefit from consensus. If a patient has a question about a disease and you're not sure about it, which happens really often, right, in the hospitals, you can just type the question in consensus, and the results you're going to get are going to be 100% evidence based. And it's completely different to have evidence based results using consensus rather than just a result from a blog post that someone who might not be even licensed has on Google, right? So this is very, very important. You know this that analyst, right? You can instantly find expert quotes for presentations if you're an analyst again, and you're working with consensus. So the question is, how can consensus really benefit students and researchers? Can consensus really benefit students and researchers? The answer is yes, and consensus can actually benefit students and researchers in a wide variety of cases in literature reviews, in plagiarism detection, in language translation, right, in collaboration and sharing again the data that we have obtained in data visualization, topic modeling and in data analysis and insights. So before we actually move into the real world examples on how to use consensus, it is very, very important to highlight a very specific point about this artificial intelligence program. And this specific point has been highlighted in other lessons, such as HGVT, research rabbit, and all of the other tools that we have analyzed. It is the fact that when we're dealing with artificial intelligence, it is of extreme importance to make sure that we give the correct input to receive the correct output from, again, those algorithms. And in this case, the input that we're going to give, the prompt that we're going to give to this artificial intelligence model of consensus is going to be the questions that we're going to ask, okay? So I want to dedicate the next part of this presentation on teaching you how to get the best results with consensus, okay, how to ask the correct questions, okay, that have been, again, proven to give you the best results from the team. So I note that consensus only searches through peer reviewed scientific research articles to find the most credible insights to your queries. And it is recommended to ask questions related to topics that have likely been studied by scientists. So here are some examples of queries that perform well and have loads of relevant research included. So for example, what are the benefits of mindfulness meditation? Does spanking impact childhood development? Does NO three improve exercise performance? What predicts success for a startup thunder? What is the impact of climate change on GDP? So those type of questions that have been heavily studied will give us the best results when we're dealing with consensus. Okay, on top of that, okay, asking questions is proven to drive the best results while using this program, as we said. So you can ask simple yes or no questions. Are COVID 19 vaccine effective? Are genetically modified food safe? Does the death penalty reduce crime? Okay, you can also ask about the relationship between concepts. So what is the impact of climate change on GDP? Does creating improved cognition, does raising the minimum wage increase unemployment. So you can compare two or three subjects again by asking questions on them. Or you can ask about the effects, impact or benefits of a specific concept. So what are the effects of gratitude practice? What are the effects of immigration on the economy? So now, ladies gentlemen, it is time to put consensus to the test. Let's launch this program, and let's actually show again on real time how to utilize this search bar and how we can get 100% out of this program. So I'm going to see you after we launch, actually the website. 17. Consensus Test Case: Everybody to the consensus website, and the website is really as basic as it can get, right? After you sign in with your account, which I have signed in right here, you can see that you can scroll down the website. It gives you some basic information on how to search and how to have the best answers from your questions, like the best topics. You can search for medicine, social policy, okay, mental health, all of that stuff. But the main feature of the website and the feature in which we are going to be focusing in this lesson is obviously the search bar. So let's take as a case scenario, Okay, that we want, for example, to research the impact that smartphones have, right, the same test scenario that we have done in previous lessons. Okay, let's say we want to research the impact of smartphones in the mental health of teenagers. So in this case, I would ask, okay, does smartphone usage impact the mental health of teenagers. So let's try and search this, right? A pressed Enter, and let's search this. Or we can search, what is the impact of smartphone usage, okay, in the mental health of teenagers? So let's see what will come up with this search, right? Waiting for the results. So these are the results that we got, and as you can see, the first thing that we can see is that we got tiles, right? And we are able to cite this. And we can also we also know the name of the journal and if the journal is rigorous, very rigorous and some other characteristics, write the names of the instructors, of the people that wrote this. Okay, so for example, the results of we got is excessive smartphone use among adolescents associated with multiple suspected, okay, factors including substance use, poor sleep, and negative emotions with differences in prevalence and impact between boys and girls, according to a large scale public health survey. Okay, the next thing, conclusive smartphone overuse was independently associated with an increased risk of mental health problems which did not seem to be mediated by problems caused by smartphone usage. Okay, so if you want something more specific, okay, and you don't get the results that you pretty much look for, you can go ahead and ask and structure pretty much your question differently. So let's see. Does smartphone usage? Okay, cause Depression in teenagers. Let's see. Do smartphone uses cause depression in teenagers. So this pretty much we ask about the specific outcome of an action. So we ask the smartphone use cause, specifically depression in teenagers. So the results indicated that problematic smartphone use was positively related to adolescent depression or overall physical inactivity, and problematic smartphone use can reduce vigor and increase symptoms of depression in adolescent students. So once we find something that we want to further analyze, we click on it. Right? And once we click on it, you can see that it loads the actual study. So, for example, this is the finding, the outcome, which was generated with AI. Like the results indicated that problematic smartphone use was positively related to adolescent depression. Okay, and you can see the paper that backs up this artificial intelligence finding. So the paper is is problematic smartphone use related to the lesson depression, a moderated mediation analysis. And you can see the abstract and all of the different authors that we have. Now, once we open one of those, right, findings that we have, we can either save it, we can cite it or we can see the full text. In this to that, you can see that it was published in this article right here, and it has 32 citations, and it was published in 2019. So that's just a very cool way to again, find evidence based answers to your question. And this is how in this case, we conducted research based on smartphone usage and depression. And if you want to share share finding and either copy it or link it to a chat with other people. So this is pretty much how consensus works. This amazing platform in which we search something and the answer we get are 100% evidence based. How cool is that? So, ladies and gentlemen, I hope that you understood some stuff and you learned some new stuff regarding consensus, this amazing research bar that gives, again, evidence based answers to our research questions. Now it is time to move to the sixth lesson of the scores in which we're going to be analyzing plag.ai, the first artificial intelligence plagiarism tool and much, much more to be discussed in the next lesson. So thank you very much, and I'm going to see you. 18. What is Plag.AI: So hi, everybody, and welcome to the sixth lesson of the scores. I'm very happy that you're here. And now we're done by analyzing consensus and all the other four artificial intelligence tools, it is time to move to the more targeted artificial intelligence tool, and we're going to start with plag.ai. Now, plag stands for plagiarism, okay? And this is exactly what this tool does. This tool identifies and performs plagiarism texts and tests after having access to a huge huge, huge online, offline published and unpublished data sets of documents and articles so you can literally check our literature before we submit it. This is one of the coolest tools we going to be analyzing in this course, so I can't wait to launch this PowerPoint presentation with genars for being here and let's launch this PowerPoint 19. Plag.AI Main Features: And this is the logo of a company, and we're going to start by answering what is plague.ai? Now, plag.ai is the first, as we said, plagiarism checker completely powered by artificial intelligence. And don't get me wrong, there have been plagiarism checkers before, but none of them was actually powered by artificial intelligence. And what does AI help us do here? AI, actually, okay, with the access that plagued the DI has to those online databases of billions of published and unpublished documents, emphasis on the fact that it has access to both published and unpublished documents. Okay, it's able to drive data from all of those documents while utilizing, again, the power of artificial intelligence and compare the style and type of your academic writing to them to detect plagiarism, again, using AI. So let's now talk about the databases because when we talk about plagiarism, it is very important to know the different databases that the tool utilizes in order to detect plagiarism, okay? So Play DEI has actually two databases to do that. The first one is the open database, and the open database consists of any open documents, that might be found on the Internet and archived websites. This means that what we're referring to an open database, this is not journals and publications, okay? This could be books, okay, encyclopedias, periodicals, magazines, blog articles, newspapers, and other again, content that is openly available. Also some journals that could be open to the public. Now, if you're a student, for example, and you want to submit a project, it is very important that the AI tool that you utilize in order to perform a plagiarism check actually checks websites, encyclopedias, books, and other stuff that are open and online. If you're a researcher, though, it is very important for your tool that detects plagiarism to actually have a database of scholarly articles. Why do we do that? Because when we detect plagiarism, okay, it is very important not to copy, obviously, the work of somebody else that has published an article online. So, in addition to the open database that Plague DI has, they actually offer the ability to check files against our database of scholarly articles. Again, this database consists of more than 80 million articles from some of the best known academic publishers. Okay, so what types of plagiarisms does it detect because there are many, many different types of plagiarism. The first type is copy pasted plagiarism, and this is absolutely detected by plague.ai. So we're talking about verbatim plagiarism, self plagiarism, clone plagiarism, recycle plagiarism, okay, masa plagiarism, all of those plagiarism types that you might even know that existed, okay? They exist and they're detected. In addition to that, it detects improper reference plagiarism, okay, if the sources are invalid or they're secondary sources, or if they're not even sources, and this is original text, what you're writing. In addition to that, it detects paraphrase plagiarism, a mosaic plagiarism, remixed plagiarism, hybrid plagiarism, find and replace plagiarism. So there are many, many different types of plagiarism. In addition to that, one of the most important features of plague AI is that it provides different plagiarism scores based on the amount of plagiarism that has detected in your article. So what does this mean? We have the similarity score. Okay? And all of the reports that are created, they note that are provided with a similarity score. And this score pretty much shows how many similarities exist in your own document. So it can not only detect plagiarism, and if you have copied, for example, the some other people intentionally or unintentionally. It also gives you feedback on the quality of your work. In addition to that, we have plagiarism risk score, and this score shows you the risk of plagiarism in your document. The more similarities that are detected, the bigger the risk of plagiarism. And our research has shown that this feature detects the risk of plagiarism by 94%. The next score is the paraphrase score, and this score alerts you to the number of paraphrases in your document. So again, flag.ai doesn't only detect similarities with other people's work, but it can actually help you improve your own original work. So a high paraphrase score may signal again plagiarism. Okay? The final score is the improper citation score, and improper cities shows pretty much how many improper citations exist in the document. And while it is acceptable, again, to use citations, okay, they should not comprise the majority of a document. It is also very wise to verify the sources of any citations used in order to avoid the risk of plagiarism. So again, much more than just a simple artificial intelligence plagiarism tool in plague.ai. So when it comes to using, okay, plegEI, any kind of plagiarism which is found in the document will be highlighted again, for the researchers and the students review and correction. Plagiarisms in orange that are again, seen in orange. Improper quotations are going to be seen in purple, and proper quotations are going to be seen in green. Again, the plagiarism checker will place links to the sources of the matched parts in the documents. Obviously, it doesn't only highlight the parts in which you know, they might have been issued from somewhere else, but they also it pastes the source of where it believes that you find those parts. And these links allow, again, researchers to connect with any improper quotations, words, and paraphrases in their documents. Okay? So now it is time to launch actually plag DEI and put it to the test with this real world scenario. So let's say that you're a student, right, and you're ready to submit your work on a project that you have been working on and want to check on plagiarism if you have any faults using plag.ai. So the next step is to actually ask hope to the plag DI website, launch based are, again, research, okay, the project that we have been working on and actually test for any issues and problems. So let's hop in the website, and I'm going to see you there. 20. Testing Plag.AI: Right care, ladies and gentlemen, is again the interface that you see once you launch, and again, you have signed in to plag.ai. So the first thing is that it creates an example text, right, which pretty much gives you an already ready text that is that has plagiarism and it has detected it. So it is perfect to demonstrate the powers of plagued AI. So let's say, again, in this test case scenario that this was the report that you actually want to submit. This was, again, the project that you have to submit in your work, and we have actually worked this through plegdI to detect any similarities and anything else regarding, again, all of the functions of the program. So of all, you can see here, let's press View Report to actually view and visualize the malfunctioning parts of the report. So let's say that this is the report. Again, you're the student. You can see that we have different colors, and every color in our document, okay, signifies a different flow. So first of all, we got a similarity index right here, which is 85%, and this means that it is highly similar and it needs to be changed. So we got three different colors for three different outcomes. Okay, one we have this orange color, this indicates paraphrasing. The purple color indicates improper citations, and the red color indicates, again, matches, and these need to be addressed. Now, as we said, leg DAI not only notifies you when it sees a match, but it can also helps you identify the source of that match. So once we click again on the red area, so let's click on the red area right here, for example. Okay, we click on the red area and you can see that it shows us the part which has been completely copied and pasted in the program, and we have a link again to enter the website in which it has been cited from. So as you can see, this part has been cited from this website, and this is the website that we can see it, okay? And this was from Wikipedia. This means that it is open access source. So we know again that plague grab the data from its open access datasets. Okay, the next thing that we can click on is the purple one, and as we said, purple are improper citations. So this hasn't been cited correctly. And we can see actually the source again, by clicking on this, this is a source, it doesn't load right now. So this was a source. And this is pretty much it. We also got the green, Okay, which green stands for a very good against score in the similarity index. So again, we are aiming to have as much green as possible. Okay. So now, in addition to that, okay, we can utilize the tool which you see here, which is the plagiarism removal tool. And the plagiarism removal tool, pretty much, as you can see, is a special service designed to collect your work, okay, to correct your work in order to meet your academic ethical requirements. Okay, so it is provided by specially trained editors in accordance with our ethical standards, okay, and we guarantee full privacy and fast delivery. So what you pretty much do is that you upload your document. The price is calculated in which they're going to give you pretty much a quote on the price that you're going to ask, and they're going to create original work in, again, a 34 hour support with full privacy and academically, it is academically ethical. And again, you get all of these things that they say. Okay, so again, if you're going to go back, you go to my papers, and you can upload as many papers as possible. So what you can get pretty much for plague DIO from completely free is these reports. Okay, and once you view you can see the matches where any academic tool would strike on plagiaris. So we got a lot of red as you can see, and you also get this plagiarism index. So this is pretty much what you get in the website of plague dot IO for free. Let's move back now to the PowerPoint presentation and the outro of the las. So, ladies and gentlemen, now we're done with play DI, it's time to move to our next tool in our list, which is going to be poised.com, and it's going to be a completely different tool, a completely genre of tools, again, rather than the ones that we have further analyzed in the beginning of the scores. So I can't wait for the next lesson, and I'm going to see you there. 21. Introduction to Poised: So, ladies and gentlemen, welcome to the seventh lesson of the course. I'm very happy that you're here. And in this lesson, we are discussing and as I mentioned in the final part of the previous lesson. In this lesson right here, we're discussing about a very, very interesting AI tool. And this is poised.com. Now, poised.com is completely different from different tools that we discussed previously in this course. Why? Well, the main thing is because the previous tools that we disguised were artificial intelligence language models, okay? They would either detect language and detect plagiarism, for example, or B language generation models like JGBT, Chat PDF, and consensus and all the other stuff that we discussed about. Now, what POIs does is that it utilizes pretty much artificial intelligence to give you real time feedback on the way that you communicate through your online conferences. So Zoom calls, Google met calls, all of that stuff. But it doesn't only analyze how you talk and how you sound and how impactful your words are in real time and give you feedback. Then you can actually test the way that you present something on camera with pis.com, and it keeps a score and a track, and it's pretty much like you have a personal coach, if you will, when it comes to communicating with people online with a camera. So I'm very happy that you're here. This is actually a very, very impressive artificial intelligence tool, and I can't wait to dive into this presentation with you. Again, welcome to the seventh lesson of the score. 22. Poised Main Features: PloeExTking not. So we're so we're going to start this presentation by analyzing what again is poised. So as we said, poised is the artificial intelligence power communication coach okay, if you will, this is a communication coach, not a research assistant, not a artificial intelligence search bar like consensus. It is a communication coach that helps you speak with confidence and clarity. Okay? This tool gives you real time feedback on everything you mentioned from words most spoken to filler words, confidence, energy, empathy, and more. Yes, you heard it right. This tool can literally rate, okay, how empathy you show in your words, how many filler words you show. Okay, how much confident you appear on camera. It has special artificial intelligence tools built inside that can analyze all of those factors in real time and actually give you a notification, for example, to sound more energized or to stop with the filler words, live as you are in a cold. This is extremely interesting. Okay, it helps you track your progress, analyze speech trends over time, and improve your speaking in real time. So what do we say with all of those artificial intelligence model? More you use them, the more you implement them. The more information you give, the more information you take from them. So if you start using Poise again and again and again, over a big period of time, it has more data to work on, right, more data to analyze. So this is how it tracks your process and analyzes all those speed strengths over time and give you amazing visual representation of your data and how you've grown as a speaker. So, in addition to that, Poised then provides, as we said, a visual representation of your stat, speaking habits, and overall performance on a call. So once you're done with a call, once you've used Bois, and you're completely done with a call, it provides, again, a visual representation of how you did, what you can improve. And again, all of those facts factors that we analyzed in this slide, for example, how many feeler words you used, how was your confidence, how was your energy? How was your empathy and much more which we're going to see in the demonstration of the program later in the station. So as we said, Poise helps you grow as a speaker? It is an artificial intelligence coach. Okay? So what we do in POS is that, first of all, it assesses, okay? And it pretty much navigates you and mentions how you stack up against the best in your industry. Okay, it has also some challenges in meeting challenges. For example, you're in the meeting, you're talking with someone, and then a challenge pops up, which you can take or you can leave from Poise. And obviously, it provides videos, exercises, and articles from Poised experts inside the website that will help you again grow as a speaker, because as we said, at the end of the day, Poised is an artificial intelligence speaker. Okay, so as you said, also POIs provides real time feedback, and this is one of the biggest assets of this program, the fact that as you're in a meeting, you have real time feedback from POIs that has analyzed your performance in this meeting and knows also other meetings that you have been and how they went. So you know automatically finds the top moment to learn from in a meeting. It looks at trends across time to see if you have improved. So, for example, you use a lot of filler words, right? Poised nose and pops up identification that tells you, Hey, let's chill down with, you know, words that you have been saying all over again and over again because it doesn't sound good. And after every meeting, you see how you did it quickly and easily again using poised. So poise now, it can be pretty much disguised and used by many, many different categories. The first category of people that can use poised are those with leadership positions. Okay, so pretty much Boise helps you communicate with clarity, okay? Being understood is the lifeblood of communication, poised helps improve what you say and how you say it. So when it comes to leader, you improve conciseness and reduce rambling in retrospect moments of clarity to incorporate in the future. Voiced mentions those moments, and it helps you reduce filler words and hedging words. Okay, so also for literacy position, you get live coaching in your meetings, again, with all the notifications that pop up. You never go off track again off track from your speaking style, and it also tracks non verbal cues such as your facial expression. So this is also extremely cool because it has access to your camera, and it can see how you communicate with an audience also with non verbal cues. So for example, if you do like this with your head, it will understand that you said no, and this is extremely cool. Also, when it comes to leadership position, you get education and leading frameworks from the best storytellers, because again, it is a coaching, a storytelling coach. And you can also track how many stories you told across time and you get feedback on your storytelling after a meeting. So how cool is that, and everything, again, is done with artificial intelligence that simple. Okay? The other huge area of expertise that poised can be used, and a huge area that we will be using poised as students and researchers is for interviewing, okay? So when it comes to strong communication skills, job candidates can't afford to miss the mark. Imagine you're a student or, you know, a researcher and you want to apply for a researching job, POISE will very much help you to that. Okay, so you get discrete actionable feedback real time during interviews. Okay, you use what you learned to quickly course correct with better pacing, better pitch or better clarity, and you build your confidence with callous for a job well done. So pretty much, if you're not doing well in an interview and you want to find something artificial intelligence code comes in, it tells you to, you know, better your pacing, better your pitch, better your clarity, and then you get an o from POISE, meaning that you did your job greatly. Again, for interviewing, Poise gives a high level assessment of how well you did and a play by play analysis of key moments to improve retrospectively. So after the interview has passed, and this will help you again improve over time after interviews and interviews and interviews. So you can review the moments that could have gone better. You can see any unintended facial expressions or non verbal cues, again, in film clips that are, you know, stored inside Poised. And you can get a transcript of your contributions to see where filler worlds over. So finally, for interviewing, online interviewers have changed completely the game, as we know. Body language, speech, and energy works differently when filter through screen. So POIs give you also new rules for success on your terms in your voice. It helped you establish a better port instantly with one simple questions, read yourself of the filler words that dilute your authority and harness the real power of storytelling. Okay, finally, with storytelling, you get education and leading frameworks from the best storytellers. Again, as you said, those are coaches. This is a coaching program to help you become a better storyteller and a better communicator. And you also track how many stories you told across time. So this is, again, extremely cool. Now, all of this is, in theory, again, poised and it is a very practical website. It's a very practical artificial intelligence tool. So it is time to test poised with this case scenario. So let's say that you're presenting the abstract of your work on a live Zunkl in two days, and you want to practice and improve your live presentation skill. Okay? So again, you're presenting the abstract of your work in two days, but you don't want live feedback as you're presenting this abstract, but you just want to get better and get coaching feedback before you actually enter the room and present the abstract. The thing is that Bois has, okay, a coaching program which helps you before you actually present your abstract or anything you want to present in a live scenario. So this is what we're demonstrating in the case scenario that follows. Thank you very much, and I'm going to see you there. 23. Copy.AI - Introduction: Ladies and gentlemen, welcome to this final lesson of the scores, and arguably perhaps one of the most interesting lessons because we're going to be analyzing one of the most interesting artificial intelligence tools out of the eight tools that we have analyzed in the scores. And the tool that we're going to be analyzing and focusing in the next 15 minutes is going to be copy.ai. Now, let's stand in the title and actually the name of this artificial intelligence tool because Copy comes from the word copywriting. And copywriting is the art of generating text, based on a general topic of demand. And obviously, this is going to be of key importance for students and researchers. Students and researchers, in a sense, are a type of copywriters because they need to generate, again, original text for their studies. So this is where copy DAI comes into play. Again, thank you very much for being here and let's launch this presentation and let's dive into the features of this artificial intelligence program. 24. Copy.AI - Main Features: Okay, okay, okay. So again, welcome to this lecture. So again, welcome to the final lesson, and let's dive into what actually is copy.ai. So again, as the name suggests, copy.ai is an artificial intelligence copywriting tool that generates original text fastly and reliably. It helps people write better content faster in a wide variety of topics. Okay, so how does copy.ai actually work? So it is a five step process. The first step is to enter your copywriting project. So you choose from emails, social posts, long form blog posts, and much more. This could be articles that you want to write blogs for a scientific paper. This could be abstracts or manuscripts, again, of your scientific paper. So you have the search buret here and it's going to ask you, What are you looking to create? Okay, and you can say, for example, a case report of a medical study. Okay, then what are the main points you want to cover? Okay, so I want to cover the impact of the case, the outcome of the case. And for example, some learning outcomes that reviewers should have when they review this, again, case report. And then you choose a tone. You're going to have friendly, sad, stressed, emotional, non emotional. And again, this is the general topic of Again, your copywriting theme. So we have many topics to choose, and we're going to see this once we launch our website. So what input are we giving into this AI model, right? We're giving the general topic the main points that you wanted to generate and finally the tone because at this point that we are right now, artificial intelligence also can mimtate the emotional intelligence of a human being. The next step is to give copy the DI a bit more context. So you enter a few sentences about your brand, your products, or, again, the type of content that you want to create. So again, what are the main points that you want to cover? Let's say I want to cover a journal article post about how smartphones and the association of smartphones causes or might lead to depression in young lings and teenagers. So again, you just give more context. And as you said, this happens in every single AI model. The more context we give, the better the input, the better the output is going to give. So once we're done with this, right, we press Create copy, which means generate text. And the next thing is that we're going to sift through the results and check the results with our own eyes. So our content generator gives you multiple options for each campaign that you're working on. And again, Copy Do DI is usually targeted in copywriters. Copywriters are very, very importantly utilized in jobs as sales, you know, transcripts, social media, so this is the type of things. But we definitely can utilize Copy DDI as students and researchers. Okay, so you can see, those are the posts that Copy DI has generated, but we can actually, and I'm going to show you once we launch our website, utilizes as again, researchers and students. The final Okay. And the final step in the process is to edit polish and publish. So you can use copy to DI's editor to rewrite paragraphs and polish up sentences. Then copy and paste the work into your CMS for publishing. Okay? Now, the very cool thing with copy.ai is that it doesn't give you a generic input. So please input here your title, input here more information, even with your tone and generate text. It has built in writing generators. So now we're going to be analyzing the different writing generators with different writing styles that are preset again in this artificial intelligence program. So the first is the paragraph generator, and the free paragraph generator generates complete paragraphs according to the instructions provided by you again so that you can quickly build unique content. And the paragraph generator is going to be, of course, of key importance if you are a student or if you're a researcher. It is very important generate paragraphs with more input again and more personalized with the correct tone that you wish, because we also can generate paragraphs, as we said, with HTPT and HATPDF. But Copy DI gives you the opportunity to add more layers of customization in the paragraphs that you provide. Okay, give more input, give another layer of prompt, if you will to this AI model, so you get better output. Okay, the second thing is the paragraph writer. So this free paragraph rewriterTol will rewrite your paragraphs according to the instructions provided by you, so you can get a unique version of your content. So this is very interesting because you might have a paragraph which is already written, right? And the paragraph rewriter will rewrite and change the words, Okay, something like the previous tool that we discussed. Okay, change the words in a way in which it seems to be unique. Then we got the sentence rewriter, which is a tool that rewrite an entire sentence according to the instructors provided by you. So you might not want to rewrite a whole paragraph. You might want to rewrite just, you know, some sentences. So this can be done with the sentence rewriter moving on, we got the free outline generator. And if you got, for example, writer's blog, which is a case of which you just see the cursor blinking and you don't know what type as a student. Okay, the outline generator will take you from a blank page to a full blog post in under 5 minutes. And this is extremely important and extremely useful if you've actually got a post as a student, a blog as a student or, you know, a blog as a researcher, for example, a magazine or something of an area of research. Okay, then we got the content idea generator. And again, you can use your exclusive content degenerate to come up with your next blog post or social media post if you have a social media account or a blog in which you're going to be focusing on. And finally, we got the paraphrasing tool, which is a tool that helps you rephrase any sentence quickly and easily. And this is very similar again to the plagiarism tool that we discussed in play Do Dio, because again, plagiarism is something that is very easily, you know, fixed, a problem that is very easily fixed, and all of those AI tools have incorporated a way to fix plagiarism. And this also happens in copy.ai, and we're going to be checking all those tools in the website portion in the test, again, case which will follow. Okay. So the next question is, can copy.ai be used for research? Because again, copywriting is a thing of sales, a thing of marketing. A lot of marketers actually are also copywriters. So can it be used for research? The answer is, of course, yes. And we need to put this to the test to prove this. So how about this scenario, okay? You're a student, okay? Ask to compose a blog post about the impact of smartphones on the mental health of teenagers using Copy DEI. Let's say you're a student, you have been invited from, let's say, the newspaper or the website of your school to compose a blog post, again, about the impact of smartphones on the mental health of teenagers. So we've done this example regarding the impact of smartphones to most of the lessons of the scores. So let's actually see how copy.ai manages to deliver in this case. So I think very much I'm going to see you in the actual implementation of this test case scenario on the website of copy.ai. 25. Testing Copy.AI: Here we are, ladies and gentlemen, inside the website of Copy DDI, please note that you don't have to actually download the application of Copy AI. You can actually access it through the website after creating a very simple account, which is the process of about 30 seconds to a minute. So this is Copy DotI and we can see that it immediately gets us to the chat version. So we got hat my Copy dot DI. It says, Get started by writing a task, and hat can do the rest. Not sure where to start. Check out the prompt library for inspiration. So the very cool thing here is y DI actually provides you with a prompt library, so you actually know in general terms what a prompt is already, but it actually helps you with more specialized prompts. So we got real time search. Summarize the latest news on generated DVI, for example, we got long form content that can be produced with Copy DDI. And this is one of the most pivotal points that discriminates, copy to DIF ChaGPD for example, create a blog post about search engine optimization. Writing press release about w.copy.ai. Okay, we can also brainstorm ideas. So let's go ahead and actually ask this. Let's go ahead and say, write a blog post because this was the test case scenario. Okay, write a blog post about the impact of smartphone overuse to the mental health health, okay, of teenagers. So let's see what it will generate right here. So I said, write a blog post about the impact of smartphone overuse, okay, to the mental health of teenagers. So the impact of smartphone overuse on the mental health of teenagers. In today's fast based digital area, smartphones have become an integral part of our lives. They provide us with instant connectivity, a wealth of information and endless entertainment options. However, it is essential to recognize the potential negative impact that excessive smartphone use can have on the mental health of teenagers. So in this blogpost, we'll explore the various ways in which smartphone overuse can harm the mental well being of young individuals. So now, mentions, again, all of those different points highlighted from title of this again, Blog post. So we got sleep disturbances. Okay, social isolation and anxiety, addiction and dependency, poor mental health and body image, impaired concentration and emotional regulation, and the conclusion of this blog post. So how is that the first thing that I see once I've generated this blog post is the fact that it gives us more context, okay, more context and more content compared to HAGBD. So what I want to do now is that I could ask, for example, to make it bigger, make it smaller, change some stuff. But let's just go to the templates because I really want to see and show you the templates of Copy the AI. So we go to all templates, and those are all of the different templates, all of those, again, presets already built into Copy the AI. That we can utilize for our advantage. So we got the blog post wizard, for example. You can sum me to a whole first draft of your post in 5 minutes. A right blog intro, a light blog outline. Okay, we got motivational quote. We got sales landing page, called outreach email, freestyle, job description, case study, results statement. You got all of those different presets, and here are the general categories of Th presets. So for example, we can go to the writing tool and see we got the freestyle, command a flexible AI to generate anything you need written. So let's go here, start new project, and now we've started a new project with this freestyle. So let's say, what are you looking to create? Okay, I'm looking to create a blog post on the impact of smartphones, okay, to the mental Health of students off, sorry, teenagers. Teenagers. Okay, what are the main points you want to cover? Let's see. Attention, Impact. Impact on attention. Okay, I want to cover also the usage of smartphones at school, networking effect, enhanced by smartphones. And these are just on top of my head, right? I'm not thinking about it. And now we choose a tone, and we got to have the friendly tone, luxury tone, relaxed, professional, bold, adventurous, persuasive and empathetic. Now, in our case, you know, we're talking about students, we're talking about researchers. So let's just say persuasive, right, and create content. So let's see what COVID AI will come up with. So here is, again, the block post. The impact of smartphones on the mental health of teenagers is not just about how it can be used to distract them from school or homework. It is also about how smartphones affect the way in which they perceive themselves and the place in the world. So again, this is the first point, the impact at school, the uses at school, and the networking effect that is enhanced. A research study show that teenagers who use smartphones at school are less likely to feel ashamed, which could be because they are more confident in their ability to control their intention when using a smartphone. This confidence may also translate in more creative thinking and innovation as a result of being able to stay focused on work while using a smartphone. And this is the blog post, and it gives you actually three to four different blog posts in order for you to choose. So how cool was that? And again, you can access all of your projects from the My project app. And this pretty much concludes the basic general user interface of Copy dootI and how we actually utilized the power of original copywriting capabilities of Copy dotI to create a blogpost as a student about the negative effects of smartphone overuse in the mental health teenagers. And this ladies and gentlemen concludes this lesson of ours on copy AI, again, an artificial intelligence tool that in one sense is similar with ChatBT ChatBDF and the other language generative models that we discussed about previously in the lessons of the course, but on another way with all of the presets that it has inside of the program and the different capabilities to choose the tone and the different inputs that it provides you to give as a prom to get special output out of the artificial intelligence model is very, very interesting and a very unique way again to enter the world of copywriting as a student and as a researcher in your project. So thank you very much for sticking up until ends lesson, and I'm going to see you in the thank you message of the scores. 26. Thank You!: Ladies and gentlemen, this concludes the eight lessons and this course on artificial intelligence tools and their usage on students and researchers. Thank you very much for sticking up until the end of all of those lessons with me, okay, for showing up in every single one of those lessons, for analyzing with me all of those tools. Again, during those lessons we've analyzed a vast majority and a huge variety of artificial intelligence tools. And trust me, if you manage to remember 10%, 20%, 30% of the information that we discussed in those lessons, you're going to have a huge competitive advantage guarding all of the other people that don't know all the tools that we analyzed in this course. So again, I'm very happy that you chose to undergo this journey to analyze all of those AI tools with me, I'm going to see you in the next course.