Machine Learning and Neural Networks - page 44

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Getting Started With OpenAI ChatGPT (GPT-3.5) API In Python | Tutorial For Beginners

Getting Started With OpenAI ChatGPT (GPT-3.5) API In Python | Tutorial For Beginners

The video tutorial explains how to use the OpenAI ChatGPT (GPT-3.5) API in Python for beginners. The presenter introduces the GPT 3.5 Turbo model as a cheaper alternative to DaVinci, which is a composition model that can generate both natural language and code and has no token or total limit. The tutorial then demonstrates how to sign up for an OpenAI account, obtain an API key, and use the chat_gpt-completion function to keep a conversation log with user and system inputs. The video also covers how to retrieve responses, append follow-up questions, and modify the code to keep the conversation running nonstop.

• 00:00:00 In this section of the video, the speaker introduces the GPT 3.5 Turbo model from OpenAI, which is a cheaper alternative to the DaVinci model. The GPT 3.5 Turbo model is a composition model that can understand and generate both natural language and code, and it costs 0.002 cents per thousand tokens. Unlike the GPT 3.0 models, there is no token limit for the GPT 3.5 Turbo model, and it does not have a total limit. The video then goes on to demonstrate how to get started with using the OpenAI GPT API in Python, including how to sign up for an OpenAI account and obtain an API key.
  
  
• 00:05:00 In this section, the creator of the tutorial discusses how to use the OpenAI ChatGPT (GPT-3.5) API in Python. This API works differently from the regular GPT 3.0 models because it is more conversational. The API uses a function called chat_gpt-completion that references the OpenAI library and the chat completion model. The conversation log is passed to this function to keep adding conversation records. The user and system roles are used to determine if input is coming from a user or from the system itself. The response option is printed, and the most important part of the response is the Choice key.
  
  
• 00:10:00 In this section, the tutorial discusses how to use the OpenAI ChatGPT (GPT-3.5) API in Python. The tutorial explains that unlike regular GPT 3.0 Models, the ChatGPT model can only return one message or one response at a time. The tutorial then proceeds to demonstrate how to retrieve the row and content from a response, how to compose a conversation with the ChatGPT API, and how to retrieve and display the composition history. The tutorial also covers how to append follow-up questions to the composition and retrieve additional information from the API based on the follow-up question.
  
  
• 00:15:00 In this section, the speaker discusses a code modification that can be made to keep the ChatGPT composition running non-stop. The modifications involve starting a session with the system row, engaging the composition by setting the content to "how may I help you," and inserting a while loop to keep the conversation running. The user inputs questions or prompts into the input statement, which saves the string into the problem variable. The content key is set as the message, and the user runs the ChatGPT compensation function to send requests and append the message to the composition list. The conversation can then be continued with follow-up questions, and all conversations are saved in a list that can be referenced by the ChatGPT API.

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Getting Started With OpenAI GPT-4 API (ChatGPT Official API) In Python

Getting Started With OpenAI GPT-4 API (ChatGPT Official API) In Python

The video covers how to use the OpenAI GPT-4 API in Python using the ChatGPT Official API. After generating an API key and installing the OpenAI python package, the user can use the GPT-4 model by creating a function and calling OpenAI's endpoint with the model ID and conversation logs. The speaker demonstrates how to append conversation logs to the composition log argument, create a command line tool, and use the ChatGPT API to generate responses. Viewers are encouraged to try out the API and subscribe to the channel for future videos.

• 00:00:00 In this section, the video explains how to use the ChatGPT Official API in Python. The API is based on the GPT-4 model, and there are four different versions available. The regular GPT-4 model can accept up to 8192 tokens, while the GPT-4 32k model can accept up to 32768 tokens. To use the API, you first need to generate an API key by signing up for an account on platform.openai.com. Then, you have to install the OpenAI python package and attach the API key to the OpenAI module. Finally, you can use the GPT-4 model in Python by creating a function and making an API call to OpenAI's endpoint, passing the model ID and a list of conversation logs to the method.
  
  
• 00:05:00 In this section, the speaker demonstrates how to use the OpenAI GPT-4 API in Python. They start by creating a list of conversations and explain how the API can access the list to provide responses. To send a request to the API, the user needs to provide a row ID to identify if the conversation belongs to the AI or user, and the content of the conversation. The speaker shares an example code block which adds a conversation to the list and shows how to call the API using the chat GPT conversation function. They also explain the response format, including the timestamp and the cost of the API call, as well as how to access the GPT-4 response within the choices key.
  
  
• 00:10:00 In this section, the speaker walks through how to append a conversation log to the composition log argument using Python in an OpenAI GPT-4 API. They refer to the composition lock that contains the latest records and append the response record from the choices key to the composition log argument. The output then is tested by running the code block and printing the composition list. The speaker also demonstrates how to create a command line tool to allow users to provide inputs, which then can be appended to the composition log based on the user's purpose. Overall, this section provides a useful guide for developers looking to use OpenAI GPT-4 API in Python.
  
  
• 00:15:00 In this section, the presenter shows how to use ChatGPT API to generate responses using Python. He codes a function to take in user input and send it to the API, then print out the response. He demonstrates this by asking the API to tell him a joke and shows the output, which includes both the user input and the API response. The presenter concludes by encouraging viewers to try out the ChatGPT API and to like and subscribe to his channel.

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Reverse Prompt Engineering in ChatGPT

Reverse Prompt Engineering in ChatGPT

In this video, the concept of reverse prompt engineering is explained, where chat GPT is used to create prompts to achieve desired outputs. The example of generating a product description is discussed, where semantically relevant entities from the text are extracted and used to instruct chat GPT to generate relevant content. The process can be applied to various types of content and can be used to generate product descriptions similar in tone and style to the original prompt. The speaker encourages viewers to subscribe to the SEOPub mailing list and YouTube channel.

• 00:00:00 In this section, Mike from the SEO Pub explains the concept of reverse prompt engineering and how it involves starting with the end goal in mind and having chat GPT create the proper prompts to achieve the desired output. Mike demonstrates an example of reverse prompt engineering using a text on smart notes. He instructs chat GPT to extract the most semantically relevant entities from the text and use those entities to generate content which can be used as a product description output. He also shows how reverse prompt engineering can be used not only in coding but also in creating content to give specific instructions to chat GPT to create better content.
  
  
• 00:05:00 In this section, the speaker discusses the process of reverse prompt engineering using ChatGPT. They demonstrate how to create a chart with numbered entities and their salience scores, and then use those entities to generate a prompt for a new article. The generated prompt includes all the specified entities and information, and the speaker notes that additional instructions could be added, such as using relevant headers and expanding the content with more detail, to further refine the output. The speaker suggests that this process can be applied to various types of content, including product descriptions, to generate new and relevant content.
  
  
• 00:10:00 In this section, the speaker discusses how reverse prompt engineering in ChatGPT can be used to generate product descriptions similar in tone and style to what was fed to the system as a prompt. The process involves inputting a description of a product, having the system analyze it, and then generating similar prompts for other products. The speaker concludes by encouraging viewers to subscribe to the SEOPub mailing list and YouTube channel.

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How To Use GitHub Copilot (with Python Examples)

How To Use GitHub Copilot (with Python Examples)

The video showcases the features of GitHub Copilot, an AI language model that provides smart coding suggestions compatible with multiple programming languages and frameworks. The video provides Python examples to demonstrate how GitHub Copilot can suggest functions, variables, comments, class, and data models. GitHub Copilot is a controversial tool that some developers criticize, but the video suggests that it can be an effective time-saver for developers despite its $10 monthly fee. The video showcases various examples of GitHub Copilot's capabilities, including creating a program to solve Roman numeral conversion, pulling stock market data from a public API, building a Tetris game, and more. The speaker suggests that GitHub Copilot can improve the efficiency of coding and allow more time to focus on other essential development tasks like software architecture, design, and business requirements.

• 00:00:00 In this section, the video introduces GitHub Copilot and its features, which include an AI language model and the GitHub dataset. The plugin offers coding suggestions that are smart, compatible with various programming languages and frameworks, and available on multiple IDEs. The video provides coding examples using Python, demonstrating how GitHub Copilot offers intuitive suggestions for comments, functions, variables, and even class or data models. The video also notes that GitHub Copilot is a controversial tool and discusses counterarguments against its use. Despite its $10 monthly fee, the video suggests that GitHub Copilot can be an effective time-saver for developers.
  
  
• 00:05:00 In this section, the video showcases examples of using GitHub Copilot with basic Python commands as well as creating a program to solve a Roman numeral conversion problem. While Copilot can anticipate what the user wants to do, some code it outputs may not be easy to read or work with, so the user needs to review and adjust as necessary. Copilot was also able to predict that the user wanted to create a list of test cases and even wrote a loop to run them, demonstrating its ability to save time and effort in the coding process.
  
  
• 00:10:00 In this section, the video shows an example of using GitHub Copilot to create a Python program that can pull stock market data from a public API called alpha Vantage and display it in a table using the pandas library. The instructor first structures the program and adds comments to guide Copilot's suggestions. Copilot then suggests a URL that is compatible with alpha Vantage and imports the necessary library. Copilot also shows its capability to understand the structure of the retrieved data, allowing it to easily create a table of stock price information. The instructor then demonstrates Copilot's integration with matplotlib to plot the data, requiring only two lines of code. The video concludes with a successful program that can pull stock market data from an API and plot it on a graph or table, showcasing the capabilities of GitHub Copilot in more complex scenarios.
  
  
• 00:15:00 In this section, the speaker demonstrates how to use GitHub Copilot to code a simple data science program, plot a stock price graph, and build an entire Tetris game using PyGame. The speaker suggests setting constraints for the AI tool for specific tasks rather than leaving it to interpretation to achieve better results. GitHub Copilot's suggestions help the speaker create the block shapes and define the game state. Finally, the speaker mentions that the AI tool efficiently updates the game state every frame rate, checks if the game is to be exited, and fills the screen based on empty block color and fixed blocks in place, ensuring the smooth functioning of the game.
  
  
• 00:20:00 In this section, the speaker demonstrates the use of GitHub Copilot to create a Tetris game with Python code. They acknowledge that the code quality is not perfect but it was able to write around 80% of the code in just 20 minutes. Although some developers have expressed concerns about Copilot making them a worse coder or slowing down their learning, the speaker believes that it will only shift their focus to a different set of skills, such as problem solving at a more strategic level. The privacy and data aspect is another concern since GitHub is owned by Microsoft and using Copilot means they have access to users' code. While it might not be a fit for high-profile companies or government institutes, it should be okay for startups and personal projects.
  
  
• 00:25:00 In this section, the speaker discusses their verdict on using GitHub Copilot. They suggest that if your company policy allows it or if you're using it for your own projects, then you should use it or at least try it for a couple of weeks. It can save you a lot of time coding and free up time to focus on more important and interesting tasks like software architecture, design, and business requirements. The speaker encourages viewers to share their opinions on GitHub Copilot in the comments section.

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How to learn to code FAST using ChatGPT (it's a game changer seriously)

How to learn to code FAST using ChatGPT (it's a game changer seriously)

The video introduces ChatGPT, a natural language processing tool developed by Open AI, as a game changer for those looking to learn coding faster and better. The speaker shares a framework for creating a customized study plan with ChatGPT based on the learner's learning style and lifestyle, as well as using ChatGPT to generate project ideas and serve as an expert tutor to explain coding concepts. The video also discusses the importance of project-based learning and recommends the stem learning platform Brilliant.org as an additional resource for learning to code. The video concludes by inviting viewers to explore using ChatGPT as part of their learning workflow.

• 00:00:00 In this section, the speaker discusses the benefits of using ChatGPT, a natural language processing tool developed by Open AI, to learn how to code faster and better. The speaker shares her framework for how to ask Chat GPT to design a custom study plan based on the user's learning style and lifestyle, as well as how to come up with project ideas and use Chat GPT as an expert tutor to teach coding concepts step by step. The speaker also gives tips on how to get the most out of Chat GPT by going back to the basics of prompt engineering, which is how to frame questions to get better answers from the AI.
  
  
• 00:05:00 In this section, the speaker introduces a framework to create a better study plan for coding using ChatGPT. The framework is based on the five W's, including who, what, when, where, and why. The speaker then provides an example of a study plan for learning to code in Python with a focus on data science, consisting of several learning topics with relevant resources and timelines. However, the speaker advises that the approach to learning is just as important as the study plan itself, and introduces a Breath First Learning framework that solidifies learning through project applications.
  
  
• 00:10:00 In this section of the transcript, the speaker emphasizes the importance of projects in the learning process and explains how ChatGPT can help generate project ideas. They provide an example of an exploratory data analysis project centered around the anime show Naruto and demonstrate how ChatGPT can even generate code for the project. While the generated code appears legitimate, it ultimately does not work due to missing elements. Overall, the speaker rates ChatGPT's project creation ability three out of five and invites viewers to share their experiences with ChatGPT-generated projects in the comments.
  
  
• 00:15:00 In this section, the video discusses how Chachi BT can act as an expert tutor to explain concepts to users, such as object-oriented programming concepts of inheritance and polymorphism. The video emphasizes that this is helpful for users who come across difficult concepts while coding but need a more detailed explanation. Additionally, the video gives tips for how to effectively prompt Chachi BT to get better responses, such as appending questions with the desired role that Chachi BT should play and asking for it to generate starter code. The video also notes some limitations of Chachi BT for learning, such as generating incorrect results and not being able to replace other learning resources entirely.
  
  
• 00:20:00 In this section, the speaker recommends the stem learning platform, Brilliant.org, as a resource for learning to code. The courses on Brilliant are specifically designed for STEM subjects and focus on interactive, hands-on learning. The speaker personally used Brilliant to brush up on skills and new topics, particularly in the field of artificial intelligence. Recruiters from companies like Meta even recommend using Brilliant to candidates. Brilliant offers a free 30-day trial and a discount on the annual premium subscription for the first 200 sign-ups through the provided link. The speaker encourages viewers to explore using ChatGPT for efficient learning and to see its potential in changing their own workflows.

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How to Use AI | 20 ChatGPT Use Cases Full Course [100 min]

How to Use AI | 20 ChatGPT Use Cases Full Course [100 min]

This video discusses how to use AI to improve productivity in a variety of tasks. It demonstrates how to use ChatGPT to help write a resume, create a math curriculum, and save for retirement. It also explains how to use AI to solve a problem by providing a step-by-step guide. AI can be used to create a company-wide email reminder for employees to update their talent and skills profile, to generate cover letters for job applications, or to create a series of short blog posts.

• 00:00:00 In this video, the presenter shows how to use AI to generate a resume for someone based off information the chat provides. The chat first asks the presenter to provide some basic information about themselves, such as their name and contact information. The chat then begins to write the resume for the presenter, breaking down their experiences and skills into different categories. The presenter gives the chat a thumbs up and says that the resume was "awesome."
  
  
• 00:05:00 In this video, AI is used to help write a resume in ChatGPT. The AI is able to understand U.S. code and explain it to the user in a simple and straightforward way.
  
  
• 00:10:00 ChatGPT is a computer program that can be used to distill complex text into easy-to-understand explanations. In this video, the creator shows how to use ChatGPT to learn Python. First, they ask ChatGPT to give them code. Then, they use the code to generate information that can be easily analyzed in Excel or a pandas data frame.
  
  
• 00:15:00 ChatGPT is a Python data science project that can be used to get code from a chat session. This code can then be used in Google Colab to generate charts and maps.
  
  
• 00:20:00 In this video, the presenter demonstrates how to use AI chat-bot (chatGPT) to generate fake JSON content for programming projects.
  
  
• 00:25:00 In this YouTube video, the presenter shows how to use ChatGPT to generate fake data for a variety of programming projects. They use chat GT to generate data sets for customer visits, menu items, and nutritional information for fast food restaurants.
  
  
• 00:30:00 The video demonstrates how to use AI to analyze customer data, identify patterns and make recommendations.
  
  
• 00:35:00 The video discusses how the Boston Tea Party affected Colonial families, specifically by decreasing employment and wealth.
  
  
• 00:40:00 The video shows how to use AI to create a remade copy of a text that has been found to have plagiarism and grammar and spelling errors.
  
  
• 00:45:00 In this video, the creator asks chat GPT to help create a basic math curriculum for a fifth grader. chat GPT provides resources, outlines a schedule, and provides a quiz.
  
  
• 00:50:00 The video provides a guide on how to use AI to help with tasks such as planning retirement, grading math quizzes, and more. It suggests using chat bots to ask the AI questions, and provides a video demonstration of this process.
  
  
• 00:55:00 This video shows how to use AI chat bots to help with saving for retirement. The chatbot can help you calculate how much you would need to save each month to reach your retirement goal.
  
  
• 01:00:00 In this video, the presenter explains how to use AI to solve a problem. They first describe the problem, and then show how AI can help by providing a step-by-step guide.
  
  
• 01:05:00 This video explains how to use chat GPT to format and send an important email to all employees.
  
  
• 01:10:00 This video explains how to use AI to create a company-wide email reminder for employees to update their talent and skills profile. The software, called "Jet GPT," will generate email templates for you to use.
  
  
• 01:15:00 In this video, YouTube user "ryanstewartmorgan" discusses how AI can be used to create a cover letter for a job ad. ChatGPT can be used to create a resume cover letter that accurately represents the applicant's qualifications for the position, based on the job ad description.
  
  
• 01:20:00 This video explains how AI can be used to help with the task of writing cover letters for job applications. AI can generate cover letters for you that are tailored to the specific job you are applying to.
  
  
• 01:25:00 The video explains how to use AI Chat GPT to create a prioritized list of tasks to be completed, as well as a possible schedule.
  
  
• 01:30:00 This video shows how to use AI to create a performance work statement for a job. AI helps to identify key responsibilities and the education requirements for the job.
  
  
• 01:35:00 This YouTube video demonstrates how to use AI to create social media posts for a Facebook group called "How to Use ChatGPT." The video explains how to stack a variety of different videos and text posts to create a post, and then shows how to paste the post into chatGPT. The video demonstrates how to use AI to improve the quality of a social media post.
  
  
• 01:40:00 This YouTube video demonstrates how to use AI to create a series of short, blog posts in just a few minutes.

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Prompt Engineering with OpenAI's GPT-3 and other LLMs

Prompt Engineering with OpenAI's GPT-3 and other LLMs

This video explains how the OpenAI GPT-3 machine learning algorithm works and how to use it to generate text and images. The presenter covers some best practices for prompt design and demonstrates how to use the algorithm to improve the accuracy of answers to questions.

• 00:00:00 Prompt engineering is a discipline within the world of generative AI that describes the art of writing good intentional prompts that produce an output from a generative AI model that we actually want and to a degree, it is an abstraction of programming. There are a few things to learn about prompt engineering, one of which is thatprompts typically use one or more of the following components: instructions, external information, user input, and prime problems with an output indicator.
  
  
• 00:05:00 This YouTube video explains how OpenAI's GPT-3 artificial intelligence model works and provides an example of a prompt. The model is trained to answer questions based on external information (context) and verified information (the question). If the information is not within the context or the model does not have the correct information, the model will answer with "I don't know."
  
  
• 00:10:00 The video explains how OpenAI's GPT-3 model uses randomness to produce more interesting outputs. The model is more creative and entertaining when the temperature is raised.
  
  
• 00:15:00 The video describes how to use OpenAI's GPT-3 machine learning algorithm to create a prompt that can provide better answers to questions. The video also demonstrates how to use source knowledge to improve the accuracy of the GPT-3's answers.
  
  
• 00:20:00 In this video, the OpenAI GPT-3 machine learning model is used to generate text and images. The GPT-3 model is able to handle a maximum of 4096 tokens within a prompt and completion creation, but it is not able to handle a prompt with a context window of 4097 tokens. The maximum completion length of the GPT-3 model is set to 412 tokens.
  
  
• 00:25:00 In this video, the presenter explains how the GPT-3 algorithm works and how to set up a prompt to use it. The presenter also covers some best practices for prompt design and Branch Engineering.

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REAL Uses of ChatGPT As A Developer | 12 Practical Examples

REAL Uses of ChatGPT As A Developer | 12 Practical Examples

Travis from Travis.media discusses the use cases for Chat GPT in the context of being a developer. Experienced developers should utilize AI tools such as Chat GPT to become more efficient, while novice developers should wait until they understand the technology before utilizing it. He provides 12 practical examples of how Chat GPT can be used by developers. These range from writing code to generating templates, summarizing articles or pdfs, and even creating dad jokes. Chat GPT can help developers keep up with the ever-changing technology landscape and lessen negative repercussions like burnout. The speaker emphasizes that AI is a tool that enhances efficiency, not a replacement for the need to understand coding fundamentals. Finally, the speaker believes that harnessing the power of AI can help developers become more efficient and effective and help them move up to work in the next stage of technology.

• 00:00:00 In this section, Travis from Travis.media discusses the use cases for Chat GPT in the context of being a developer. He explains that experienced developers should absolutely be utilizing AI tools such as Chat GPT to become more efficient, while novice developers should wait until they understand the technology before utilizing it. Travis gives 12 practical examples of how Chat GPT can be used by developers, starting with a non-coding related example of coming up with engagement tweets for Twitter. He stresses that Chat GPT can help developers keep up with the rapidly evolving technology landscape and lessen negative repercussions like burnout.
  
  
• 00:05:00 In this section, the video discusses several practical examples of how to use ChatGPT as a developer. One of the most popular use cases is to have ChatGPT write code for you instead of writing it from scratch. Users can give specific information, such as the language and framework, to generate accurate code and templates that they can customize. Other use cases include optimizing resource usage for Kubernetes, writing AWS policies, and refactoring existing code. ChatGPT can also explain code and clarify any confusion, making it an excellent tool for learning to code.
  
  
• 00:10:00 In this section, the video discusses how ChatGPT can help developers find bugs in their code and make it more efficient. By pasting in code with errors or slow performance, ChatGPT can suggest changes such as refactoring code, eliminating unnecessary loop iterations or replacing slow operators. Furthermore, developers can use ChatGPT to generate templates for Kubernetes manifests, Cloud Formation templates, and GitHub readme files, which can save time and improve efficiency. Overall, ChatGPT can help developers write cleaner, more efficient, and error-free code.
  
  
• 00:15:00 In this section, the speaker provides 12 practical examples of how developers can use ChatGPT. The first example is to summarize long articles or pdfs that may be too time-consuming to read. The second is to use it as a tutor to help with learning concepts or programming languages. The speaker also suggests using ChatGPT for automating tasks, generating code or SQL queries and creating templates for Terraform or CloudFormation. They also suggest using it to write short blog posts or even getting a chuckle with a dad joke for your daily stand-up. The speaker emphasizes that although AI is a useful tool, it should not replace the need to understand the coding fundamentals and that it is the developers' use of AI that will enhance efficiency and not replace jobs.
  
  
• 00:20:00 In this section of the video, the speaker highlights the increasing demand for developers, I.T professionals, cyber security experts, devops engineers, and SREs due to the proliferation of technology. The speaker advises anyone learning to code to keep themselves focused and stay the course while putting in the necessary effort to land a job. Ultimately, the speaker believes that harnessing the power of AI can help developers become more efficient and effective, and as technology advances, everyone will move up to work on the next stage of technology.

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ChatGPT Tutorial: How to Use Chat GPT For Beginners 2023

ChatGPT Tutorial: How to Use Chat GPT For Beginners 2023

This video tutorial provides an introduction to Chat GPT and explains how it can be used for a wide range of purposes. The video covers various command prompts for Chat GPT, including role-playing, tutoring, asking for new command prompts, and seeking advice. The tutorial also highlights the importance of being specific and providing feedback to get the best results from Chat GPT, and suggests thinking of Chat GPT as a mentor and assistant in any topic. Overall, the video emphasizes the flexibility and usefulness of using Chat GPT for planning personal and professional tasks.

• 00:00:00 In this section of the tutorial, the instructor introduces Chat GPT and explains how to sign up for a free account, indicating that the legacy or the 3.5 version is sufficient for this tutorial. They proceed to explain how to create new chats and how each conversation is saved for future reference. The instructor then highlights some limitations of Chat GPT, such as the lack of current event knowledge and some inaccuracies, which require fact-checking. They proceed to cover the first two command types: asking for specific facts or details and asking for suggestions, respectively. The instructor demonstrates how to give prompts for each command type and offers tips on how to improve the AI's accuracy through feedback.
  
  
• 00:05:00 In this section, the video presenter explains how ChatGPT can be used for language translation and comparison. ChatGPT can provide more accurate translations than Google Translate as it takes context, social cues, and real-life situations into consideration. It can also be used for written translation, making it a versatile tool for users. ChatGPT is also adept at comparisons, as it has a lot of information and data scraped from various sources. It can provide answers on the differences between cats and dogs as pets or the differences between iOS and Android operating systems. Users can also provide feedback to ChatGPT to help it provide even better responses. Finally, the video presenter highlights ChatGPT's ability to do creative writing, everything from email templates and blogs to songs and jokes.
  
  
• 00:10:00 In this section of the tutorial, the video shows how ChatGPT can be used to generate various types of content. The first example given is asking ChatGPT to write a short story about a caterpillar that falls off a tree, loses its family, and is reunited in a funny and feel-good way. The narrator demonstrates how ChatGPT can also rewrite the story as a song or a poem. Another example is asking ChatGPT to write an email to a car dealership about an overcharge on a repair while being super nice. Additionally, ChatGPT can brainstorm ideas, such as outdoor activities under a $50 budget for a birthday party, and provide step-by-step guides, like organizing a picnic in the park. The tutorial also shows how ChatGPT can summarize and reformat a given text into a more concise summary or an outline.
  
  
• 00:15:00 In this section of the transcript, the speaker discusses the various command prompts and features of Chat GPT, an artificial intelligence tool that can be used for a wide range of purposes. The tool can help users to summarize information, generate lists, provide pros and cons for different topics, find names, quotes, or studies on given topics, and offer feedback on written text. The speaker notes that one particularly interesting use of Chat GPT is for role-playing and conversation, as the tool can generate responses based on given prompts. Overall, the speaker emphasizes the flexibility and usefulness of Chat GPT for a variety of tasks.
  
  
• 00:20:00 In this section, the video tutorial explains different command prompts for ChatGPT. The first use case is role-playing, where the user assigns an identity to ChatGPT and simulates conversations. For instance, asking practice job interview questions or practicing a new language aloud. The second use case is having ChatGPT explain different concepts, making it a free tutor for the user. The third use case is asking ChatGPT for new command prompts to learn more about what it can do. Finally, ChatGPT can be used as a mentor, providing advice on various topics, including starting a business.
  
  
• 00:25:00 In this section, the tutorial covers tips for using Chat GPT effectively. Users should consider Chat GPT as a mentor and assistant in any topic. The tutorial explains the 15 different command types that users can use to make their lives easier. To get the best answers, users need to be specific and clear with their prompts and provide feedback to Chat GPT for better results. Patience is also important as it can take time to get the desired answer. Users should think of themselves as a journalist and ask follow-up questions to hone the conversation. With these tips, users can use Chat GPT to plan their personal and business lives.

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How to Use GPT-4 to Easily Learn Any Skill (7 ChatGPT Prompts for Studying)

How to Use GPT-4 to Easily Learn Any Skill (7 ChatGPT Prompts for Studying)

The video discusses how GPT-4 can be used as a versatile personal study aid to learn any skill more effectively and efficiently. The speaker introduces seven chat GPT prompts for studying, such as using worked examples, step-by-step guides, and mental models to understand difficult topics, and using role play scenarios and clinical case studies for language learning and medicine. GPT-4 can also act as a performance coach by guiding users through visualization exercises. The video provides a link to all the prompts and encourages viewers to try them out for themselves.

• 00:00:00 In this section, the video discusses how GPT-4 can be used to learn any skill more effectively and efficiently. Seven different prompts are provided, including using GPT-4 to act as an examiner and quiz you on topics, identify high yield topics using the Pareto Principle, learn professional skills with step-by-step guides, understand difficult topics using worked examples and mental models, and practice language skills through conversation and role play scenarios with GPT-4. With GPT-4’s improved creativity and training, users can save time and learn faster in a variety of ways.
  
  
• 00:05:00 In this section, the video introduces how GPT-4 can be used as a personal study aid to learn any skill. The speaker provides seven chat GPT prompts for studying, including using role play scenarios for language learning and using clinical case studies for medicine. Chat GPT can also act as a personal performance coach by guiding users through visualization exercises for mastering a skill. The video includes a link to a list of all the prompts, and the speaker encourages viewers to try them out for themselves.