Advanced ChatGPT Prompt Engineering

Welcome to another exciting video on our channel! 🚀 In this tutorial, we're diving deep into the world of advanced ChatGPT prompt engineering, so get ready to level up your AI conversation game!

🔥 Are you tired of basic prompts and want to harness the true potential of ChatGPT? If so, you've come to the right place. We'll be covering everything you need to know to create prompts that yield advanced, relevant, and specific responses from ChatGPT.

📋 Here's what you can expect in this video:

1️⃣ Understanding ChatGPT's Capabilities:

We'll explore the capabilities of ChatGPT, so you have a solid foundation for prompt engineering.
2️⃣ Crafting Contextual Prompts:

Learn how to add context and specificity to your prompts to ensure you get the answers you need.
3️⃣ Leveraging System and User Messages:

Discover how to use system and user messages effectively for dynamic and engaging conversations.
4️⃣ Fine-tuning Your Prompts:

We'll share some pro tips on refining your prompts to achieve the best results.
5️⃣ Real-world Examples:

We'll walk through real-world examples, so you can see prompt engineering in action.
By the end of this video, you'll be equipped with the knowledge and skills to take your ChatGPT conversations to the next level. Whether you're a developer, content creator, or just curious about AI, this tutorial has something for you.

👉 Don't forget to hit that "Like" button if you find this video helpful, and subscribe to our channel for more in-depth tutorials on AI and technology. If you have any questions or ideas for future videos, please leave them in the comments section below.

Let's unlock the full potential of ChatGPT together! 🚀 #ChatGPT #AI #PromptEngineering #AdvancedChatGPT #ArtificialIntelligence

#ChatGPT #AdvancedPromptEngineering #AIChatbots #ArtificialIntelligence #MachineLearning #NaturalLanguageProcessing #Tutorial #AI #technology

Advanced ChatGPT Prompt Engineering (Advanced Course)
Advanced ChatGPT Prompt Engineering

[redhatravi]

FYI the video is cut off in all the moments in the video where you are modifying the prompt, and made it difficult to understand your content. appreciate your fresh take though

[yp]

Thanks dude. I got some useful tips out of this.

[ForWork-cknc]

I want to watch this, but Im unsure if I should because you use ChatGPT logo and I feel thats not cool bro, unless you are working with OpenAI and have their permission. Using their logo might confuse some watchers that they are watching official content, and thats not good.

[abdelhaibouaicha]

📝 Key points:

📌 Signal prompting is a technique that uses large language models to generate specific responses by adding certain words or associations to a list of historic figures.
🧐 The Open AI Playground offers more capabilities compared to Jet GPT's interface and allows for fine-tuning parameters and engineering solutions for websites.
🚀 By adjusting the "top P" parameter, we can control the number of words considered in text generation, affecting creativity and randomness.
💬 The playground offers examples and presets for grammar correction, code explanation, and emoji translation.
📊 The development of a model for accessing APIs in an application is explained, along with the concepts of frequency penalty and presence penalty to reduce repetition.
🌐 The next lecture will delve deeper into the subjects discussed in the video.

💡 Additional Insights:

💬 The accuracy of responses in reverse engineering prompt may vary, and adding a chain of thought prompt can improve accuracy in complex logical problems.
📊 The pricing for using the Open AI Playground depends on the model and is based on the number of tokens used.
🌐 The playground allows experimentation with parameters and provides inspiration for using the GPT model.

📣 Conclusion:

The video discusses signal prompting, the Open AI Playground, parameter adjustments, and the development of a model for accessing APIs. It highlights the capabilities and customization options offered by the playground and emphasizes the importance of adjusting parameters for desired outcomes. The next lecture is expected to provide further insights into the topics covered.