Prompt Engineering Tutorial - Master ChatGPT and LLM Responses

[@aniakubow]

Hope you all enjoy this tutorial! Big love to the freeCodeCamp community!!

[@infoknow3278]

Hey will ai really replace humans?

[@mo21541]

thank you for this!

[@infoknow3278]

Can u pls clear my doubt as I have read many articles everyone is saying something else what's ur thinking on it?

[@FriendlyChannelll]

​@@infoknow3278No. AI is learns only what you give it. Models are created by humans which then create the "Ai" all their info can be faked by having 1 prompter continually feeding it lies.

[@faustipez]

Thank you Ania, you are truly an inspiration for everyone! ♥️🙏🏻

[@kolbyhunt4434]

Prompt engineer tip. If you have a task just ask gpt to provide a full list of required info to help it properly understand the task. The best prompt engineer is chat gpt

[@caro5281]

Can you give me an example? Your tip sounds very useful, but I am having trouble wrapping my mind around how to exactly do that :)

[@abimbolaabe]

@@caro5281For example, you could say, “I want you to help me write an article on How To Eat Healthy but I suck at writing ChatGPT Prompts. Act like an advanced prompt engineer and give me a prompt I can use to achieve my goal “

[@zyphtron]

@@caro5281 Did you ask ChatGPT that?

[@ndigogh]

@@zyphtron great response

[@hajiimpressions8113]

Thank you! That just answered my question and saved me hours of searching for specific information for my project.

[@aanchaallllllll]

0:33: 💡 Learn about prompt engineering and its importance in maximizing productivity with large language models. 4:57: ! Using AI to generate engaging prompts for English learners to practice spoken English. 8:55: 🗣 Language models analyze sentences, generate predictions, and create well-crafted responses, making them useful in various applications. 13:06: 📚 Language models like GPT have revolutionized the understanding and generation of human language. 17:39: 📚 This video provides a quick introduction to using OpenAI and its API to create and delete chats. 22:10: ⏰ The importance of clear instructions and prompts in saving time and resources. 26:20: 💡 Adopting a persona in prompt engineering can help ensure that the language model's output is relevant, useful, and consistent with the needs and preferences of the target audience. 32:05: 💡 Zero-shot prompting allows models to perform tasks without explicit training examples, while few-shot prompting involves providing a small amount of training data. 37:33: 🔑 Text embedding is a technique used to represent textual information in a format that can be easily processed by algorithms, particularly deep learning models. Recap by Tammy AI

[@lilytea3]

Really helpful summary. Thank you Tammy AI!

[@eddyevodius]

Thanks a lot

[@rockybalboa2187]

That's the power of chatGPT?

[@999NRG]

can i add u on snapchat or telegram ? ( for coding buddy purposes )

[@dennieallen]

Wowser. Extra smart indeed. Thank you. 👍

[@leftovertech]

It is called Prompt "Engineering" purely for social reasons. As a long-time computer engineer, I can say with some confidence that many things in the IT world are named for the purpose of making the humans feel better. LOL

[@christopheryoungbeck8837]

Yeah it's not really engineering. More like A.I. training. I don't think anyone wants to be called an A.I. Trainer though. Google hires them under the title of "Content Engineering Consultant".

[@randomcomputer7248]

common sense I would say.

[@j_stach]

Linguistic engineering? It's syntactical

[@josephbenson6091]

@@j_stachI feel this is disrespectful to engineers who undergo years of professional training, just to have someone who can use language slightly cleverly to get a response out of an LLM. Not saying it’s easy, just that it’s definitely not engineering.

[@TheBuildersTable]

😅! The funny thing is that, if you are a big dummy, Ai won't help you.... I would tell these so-called engineers to ask Chatgpt to prompt you(not you per say) to get a job in gardening. 😅! GoldProfessor

[@yasir3425]

Don't let word "Engineering" dissuade you. Just simply learn skill to write effective prompt.

[@rubenverster250]

Worst is, if you're a good software engineer, it takes just as long writing the code snippet you want as it would take to carefully craft your prompt... These models are awesome for info gathering and understanding :)

[@jmarquez-cs]

@@rubenverster250 it doesn't take "just as long". I've used prompts for rewriting libraries in Python into Go (sqlalchemy, pandas). Like anything else, you get what you ask for when prompting anything or anyone.

[@rubenverster250]

woop woop @@jmarquez-cs

[@CM-xr9oq]

Good luck. Check out job postings, to see that it's simply not true. Nobody is going to pay 200k+, if you aren't also a proficient and experienced programmer

[@lysambodia]

Do you say that on top of being engineer you need to learn or acquire degree in prompt engineering?

[@juanmarco2000s]

Great job Ania! I was sad to see alot of "PE" haters in here. In 1936, Alan Turing invented the computer as part of his attempt to solve a fiendish puzzle known as the Entscheidungsproblem. It was a big headache for mathematicians at the time, who were attempting to determine whether any given mathematical statement can be shown to be true or false through a step-by-step procedure, what we would call an algorithm today. Turing attacked the problem by imagining a machine with an infinitely long tape. The tape is covered with symbols that feed instructions to the machine, telling it how to manipulate other symbols. Hint: He was feeding the machine with instructions. Much like a "Promp Engineer" today. The machine he created was called the Universal Touring Machine, as it is known, it is a mathematical model of the modern computers we all use today. Alan was known as the father of Computer Science. Not just because he created a machine, but because he created the first early approach to prompt engineering. And he did it all from a traditional engineering application. AI Prompt Engineers of today are the future of the same methology used 100 years ago. Today PE's don't have to type to prompt or feed instructions. They can have voice conversation with LLMs while eating a cream cheese bagel with coffee. And they can still command $300k+. When singularity comes PE's, ML Engineers, Data Scientists, AI Solution Architects, and AI Scientists like ME, will earn $1 Million+ annually. I took the traditional path. Started as a Geoscientist, after that I became a Planetary Scientist with minor in Astronomy. And then I leaped over to AI Scientist and left all my traditional collegues behind. With much respect to traditional roles as a engineer, architect, or scientist. AI is the present and the future. It is making all career titles and business processes easier. Employers are not paying AI PE's for their title. They are paying for their transformational work input and coaching of LLM's for the future of humanity. Lastly, Be on the lookout for my new book release. 👉🏼 "THE HUMANITIZER" Embracing AI For The Future 😌🙏🏼

[@junkjunky4590]

Very insightful!

[@FHL1314]

Here are some extra smart tips on prompt engineering that are practical: - Embrace the Socratic method: Instead of asking direct questions, break down your prompts into a series of leading questions that guide the model towards the desired output. - Leverage few-shot learning: Provide a few examples of the desired input-output pairs before the actual prompt. This can significantly improve the model's understanding and performance. - Employ recursive re-writing: Feed the model's output back into itself as a new prompt, allowing it to iteratively refine and improve its responses. - Utilize prompt chaining: Break down complex tasks into a sequence of smaller prompts, where the output of one prompt becomes the input for the next. - Explore prompt augmentation: Supplement your prompts with additional context, such as relevant background information, constraints, or examples of what not to do. - Experiment with prompt ensembling: Combine the outputs of multiple prompts or models to create a more robust and diverse final output. - Leverage prompt-based fine-tuning: Fine-tune language models on a small dataset of prompts and desired outputs, tailoring them for specific tasks or domains. - Incorporate prompt-based retrieval: Use prompts to query and retrieve relevant information from external sources, effectively augmenting the model's knowledge. - Explore prompt-based translation: Translate prompts into different languages or styles, potentially unlocking new perspectives or capabilities. - Leverage prompt-based reasoning: Guide the model to perform multi-step reasoning or problem-solving by breaking down complex tasks into a series of prompts.

[@sumitnarayan7894]

can you give a reference to the implementation of all the above points? I have a model that is not able to generate more than 500 words. How do i make it elaborate the context in detail?

[@VidimusWolf]

You just pasted a ChatGPT response...

[@tiecoolguy]

​@sumitnarayan7894 i suggest using the multi propmt approach described above. You're getting more than 500 on open ai now, right?

[@barbara1943]

@@VidimusWolf You make a good observation. Kinda reinforces the point @kolbyhunt4434 made.

[@OHJLM]

Thankyou Ania! I didn't understand how important it is to have a pre-formatted prompt plan, almost like a mini project proposal!

[@ravitiwari8994]

K

[@jiovannirosario]

As an engineer, I feel like the tech industry is watering down the significance of what it means to be an engineer. Engineering is not simply writing prompts for ChatGPT 🤦🏽‍♂️ Instead of Prompt Engineer, it should be called Prompt Writer. You wouldn’t call someone who can use Google Search a Google Engineer.

[@chetandivekar1813]

Ya that's what I was thinking 😢 it's on web they are just selling those fancy keyword "Promt Engineering"

[@techwithdave]

A month ago, I saw an open position at Anthropic for a Prompt Engineer, and it was paying $250,000 a year at the low end and $375,000 at the high end.

[@Calcific9]

everyones an engineer now man

[@kitebeachinnbeachinn2888]

Similar to data scientist I think they are using the word wrong

[@mohammadaman6014]

This is the future bro. But the role of a real engineer is much more than AI.

[@boldkojak2734]

Young lady … you are amazing lecturer, alert and very consistent. Precise definitions .. and organized ..💐 thank you

[@gdimmortal]

Things I can say about prompt engineering according to my experience: > It is about clarity, with that I mean that AI is not a human to whom we general "Indirect ask something to do". Therefore, we can directly come to point and ask. My point is that don't hesitate to directly ask Ai to do, get, produce or explain something. > Personality: as mentioned in the above course, Ai is just made of bunch of "if else" conditions, So we should make it know like whom, how, what it is supposed to give info or produce of. > Another thing i noticed that it not necessary that we should give it very simplified prompt so that it does our work as not like human, It is machine so we can more elaborate our prompt. I know we that, but still.. > You can be greedy with Ai as its not human, its alright. Don't Hesitate > Most Important - Prompt Engineering is a just buzz word. its not that hard (just to encourage) >Any way these are "My Views" "Be wise and always try to learn something from anything"

[@ArtificialIntelligenceColombia]

wise conclusions bro. Great comment

[@TheMellowGrenade]

LOL pretty sure there's more to it than a "bunch of if else conditions". that's incredibly reductionist. also there's a lot more to prompt engineering than asking direct questions. for example, models like Midjourney works best when applying a very specific and descriptive structure to the prompts that goes well beyond just asking " give me a picture of a lemon". Such a prompt in midourney would result in an image as direct and basic as the prompt it was given. so your comment is flawed.

[@gdimmortal]

@@TheMellowGrenade it is understood when wrote "bunch of if else conditions" my friend. Probably I wasn't specifically talking about Image generating Ai, I was more specifically talking about general chat Ai like GPT. Thanks for replying I learned something.

[@DaviAreias]

You clearly dont know how a Neural network works if you think its an if else condition

[@ychafiqui]

​​@@gdimmortal you're mistaken. GPT doesn't rely on if-else conditions, it utilizes a complex deep learning architecture called transformers. It's significantly more intricate than using if-else statements and is trained on an extensive dataset of internet text. It's essential to have a solid understanding of a topic before discussing it.

[@samchan4818]

I haven't watched it all, but respectfully, I remembered Sam Altman once said on lecture that prompt engineer is a job shouldn't exist. The ultimate goal of GPT is can be programmed by natural language.

[@plaidchuck]

Lots of things shouldn't exist but do.

[@peteagrawal]

Thank you Ania Kubow and Free Code Camp for this tutorial. This is probably the best introductory lesson I have come across. Even my wife, who is not technical at all, and my 9-year-old daughter, can understand now what prompt engineering is.

[@infinityzero2321]

Ya bcoz it does not req u to be an engineer... It is just writing... Should ve called writer

[@pink-doublethink]

I'll recommend my favorite neural network prompt which provides the most complete answer to the question posed. “ Simulate three brilliant, logical experts collaboratively answering a question. Each one verbosely explains their thought process in real-time, considering the prior explanations of others and openly acknowledging mistakes. At each step, whenever possible, each expert refines and builds upon the thoughts of others, acknowledging their contributions. The question is: " "„

[@emmanueldark993]

That's a great prompt and thank you for sharing it.

[@muneeburrehman547]

Thanks for sharing, Prompt King

[@StimParavane]

Wow. Great idea.

[@ArtificialIntelligenceColombia]

damn bro! What a good prompt.

[@attrett]

I tested your prompt and it's great, thanks for sharing!

[@willliu6565]

This text focuses on prompt engineering for AI, covering basics, history, usage of models, best practices, various prompting types, related concepts with examples and applications, and an invitation to related APIs. [00:00] The Essence and Application of Prompt Engineering [00:00] Introduction to prompt engineering and related concepts [01:41] Explanation of prompt engineering's role and requirements [04:31] Example of using prompts for language learning [06:44] Importance of linguistics in prompt engineering [08:21] The Journey of Language Models [08:21] Language models are computer programs that understand and generate human-like text. [10:05] Eliza was an early natural language processing program that simulated conversations. [12:51] The evolution of language models from Eliza to modern ones like GPT. [14:30] The importance of prompt engineering for effective use of language models. [16:41] Key Aspects of Utilizing Chat GPT Efficiently [16:41] How to interact with Chat GPT and manage tokens [20:42] Tips for writing effective prompts for better responses [23:01] Examples of clear and specific prompts and their results [25:00] Insights on Prompt Engineering for Language Models [25:00] Specifying format and instructions for better AI output [26:40] Adopting a persona in prompt engineering and its benefits [28:24] Writing prompts as Helena with a specified style for a poem [30:24] Various prompt formats and their applications [31:21] Introduction to zero-shot and few-shot prompting [33:26] Key Concepts in AI and Prompt Engineering [33:26] Feeding example data to chat GPT and expecting accurate responses. [35:05] Exploring the concept and examples of AI hallucinations. [36:43] Introducing text embeddings and vectors in machine learning.

[@Sportgameww]

Basic prompts here we go. Write a Python script to automate a daily task. Plan a new feature for your current project. Create a prompt to generate code snippets for common tasks. Write a function to handle error logging. Draft a test plan for your latest code. Refactor a piece of legacy code for better readability. Design a new API endpoint. Create a prompt to help debug common errors. Write a script to analyze code quality. Plan a code review session. Draft a detailed README for a new project. Create a prompt for generating boilerplate code. Write a function to optimize database queries. Design a user-friendly interface for a new tool. Plan a new coding challenge for practice. Write a prompt to assist with unit testing. Create a script to automate deployment. Draft a proposal for a new software project. Write a prompt to generate detailed bug reports. Plan a learning session for a new programming language. Create a function to handle data validation. Design a new algorithm to solve a specific problem. Write a prompt to generate documentation templates. Plan a sprint for your development team. Write a script to automate code formatting. Draft a guide for new contributors to your project. Create a prompt to generate user stories. Write a function to handle authentication. Design a database schema for a new application. Plan a pair programming session. Write a prompt to assist with code refactoring. Create a script to monitor system performance. Draft a blog post about a recent coding challenge. Write a prompt to generate API documentation. Plan a hackathon project. Write a function to handle file uploads. Design a CI/CD pipeline. Create a prompt to generate test cases. Plan a code kata for skill improvement. Write a script to manage environment variables. Draft a white paper on a new technology. Create a prompt for generating regular expressions. Write a function to parse and analyze logs. Design a new feature flag system. Plan a code optimization session. Write a prompt to generate code comments. Create a script to automate backups. Draft a checklist for code reviews. Write a function to handle data serialization. Design a caching mechanism. Create a prompt to assist with design patterns. Plan a knowledge-sharing session. Write a script to migrate data. Draft a security audit plan. Create a prompt to generate UML diagrams. Write a function to implement rate limiting. Design a new microservice architecture. Plan a project retrospective meeting. Write a prompt to generate version control commit messages. Create a script to manage dependencies. Draft a user manual for your software. Write a function to handle pagination. Design a load balancing strategy. Plan a code documentation day. Write a prompt to assist with API integration. Create a script to analyze code complexity. Draft a proposal for a new open-source project. Write a function to handle concurrency. Design a notification system. Plan a debugging workshop. Write a prompt to generate error messages. Create a script to automate testing. Draft a data privacy policy for your app. Write a function to handle real-time updates. Design a responsive UI. Plan a coding bootcamp curriculum. Write a prompt to generate database migrations. Create a script to monitor application health. Draft a contingency plan for system failures. Write a function to handle web scraping. Design a secure authentication flow. Plan a user feedback session. Write a prompt to generate code reviews. Create a script to manage cloud resources. Draft a performance optimization strategy. Write a function to handle API rate limiting. Design a state management solution. Plan a continuous learning program. Write a prompt to generate SQL queries. Create a script to automate email notifications. Draft a bug triage plan. Write a function to implement OAuth. Design a scalable architecture. Plan a team-building activity. Write a prompt to generate deployment scripts. Create a script to analyze user behavior. Draft a compliance checklist for your app. Write a function to handle image processing. Design a custom logging framework. Plan a refactoring sprint.

[@faturismee]

hi! how's it going with your projects? :)

[@sauryajha6033]

This is liquid gold! I wonder how they prompt engineered her to make this video.

[@barbara1943]

the best response I've ever gotten from an AI was to my (wifi-network-related) question, "Does... this make sense?" and it said, "No..." I learned from that negative response, and I asked a similar question a few days later, using different tech-terms, and got a "Yes..." and a lot of useful and relevant info. I shall now judge an AI agent using the Socratic yardstick: "The Socratic method is a teaching technique that uses a series of questions to help students develop their understanding of a topic:"

[@christianm4906]

It's finally happening. Prompt engineers will replace copy-paste engineers. 😄

[@4_real_bruh]

So basically knowing how to express yourself and your needs properly is now a profession?

[@techwithdave]

Being able to articulate one’s needs is a rare skill.

[@jma42]

@@techwithdave and what do you think is a better way of articulating one's needs? by being knowledgeable in the domain right? everything else is just so unnecessary cuz a simple english class is enough for this.

[@techwithdave]

@@jma42 It is pretty good with French and German, too, so English isn't required

[@yaroslav8717]

It's more a skill now, than a profession.

[@HoNow222]

All this AI related stuff is just lazy bullshit content made only to ride the wave of the newest popular thing...

[@youssefhisham7606]

In my opinion, if you already know these things, there's no need to watch this tutorial 1. Start with a Clear Goal: Begin by defining your objective or what you want to achieve. 2. Be Specific: Specify the type of information or response you're looking for. 3. Provide Clear Instructions: Write detailed prompts with correct grammar. 4. Don't Assume that the AI Knows What You're Thinking. For example, instead of writing, "When is the election?" which implies that you expect the AI to know what election and country you're referring to, write be more specific, like "When is the next presidential election in Poland?" 5. Add a Personality to Your Prompts. For instance, write a poem as if it were composed by Helena, a 25-year-old writer with a writing style similar to the famous 21st-century poet Rupi Kaur. Write a poem for her 18-year-old sister's high school graduation, capturing the style of Rupi Kaur, as if it were Helena's creation. 6. Set Limits for Lengthy Topics. For instance, specify a maximum of 50 words for responses on lengthy topics. 7. If the AI Requires Additional Information, Provide It. For example, if you're asking about "Omar's favorite food," and the AI doesn't know who Omar is, you can provide context like, "My friend Omar loves to eat pizza and burgers. We will visit America, so could you recommend the best places to eat that may Omar would love?

[@TimGreigPhotography]

Rupi Kaur a poet 😂😂

[@SUPPL3_3Y3]

This is definitely giving me “Chat GPT-generated”

[@basujain8928]

basically what i learnt, is be specific and provide ai enough information and dont assume ai knows every thing care about sementics of your word too

[@ecengclub7196]

just add 'Engineering' to every new job and you are ready to go

[@StfuSiriusly]

lol exaclty. 'prompt engineering'. what a joke

[@rongarza9488]

Great video, thanks. I kept thinking back to when I visited a border town in Mexico as a child on a Sunday. The town square had a band stand in the middle. Around the perimeter sat men with typewriters, ready to interpret letters workers wanted to send home. That was AI back then, one direction, out. This is AI now, one direction, in.

[@ryanschmidt8468]

Those men at the typewriters were artificial?

[@Chesslevel0]

20:55 something useful starts here

[@tomliuye]

As someone with a coding background and an engineering education, I found this video on "Prompt Engineering" to be highly insightful. Anu Kubo's explanation of mastering chat GPT and LLM responses through prompt engineering was exceptionally clear and informative. The breakdown of different concepts, from the fundamentals of AI to various prompting techniques, resonated with my technical knowledge and experience. I value the practical tips provided in this tutorial, particularly those related to crafting precise prompts and the significance of zero-shot and few-shot prompting. Overall, it's an excellent resource for individuals like me who want to enhance their interactions with AI models such as chat GPT.

[@hajiimpressions8113]

Thank you 😊!

[@zenpy_]

did u use Ai to write this comment?

[@diggee172]

This skill set is in its infancy. Of course it the titles etc will be change over time. Did you know that at one point the word “computer” actually referred to people who did computations for a living? We’ll have to see what “prompt engineering” evolves into

[@iggymcgeek730]

ChatGPT is like a hyperactive wizard, zapping from one topic to another with bewildering speed and a touch of madness. It's a digital whirlwind, spewing out encyclopedic facts, poetic riddles, and bizarre non-sequiturs in a chaotic symphony. Imagine a high-speed train of thought, powered by a fusion of cosmic wisdom and electronic absurdity, where deep insights are interspersed with wild tangents. It's as if the AI is juggling flaming torches of knowledge, occasionally tossing in a rubber chicken for effect, all while tap-dancing over a keyboard that connects to the vast, unpredictable human psyche. This machine's frenzied mind is a tempest of ideas, a blizzard of bytes, relentlessly churning out a dazzling, dizzying array of conversation pieces, doubling and twisting upon itself in an ever-escalating dance of algorithmic fervor.

[@harshsonar9346]

You generated this para on ChatGPT, ain't you?

[@iggymcgeek730]

@@harshsonar9346 sure did.

[@oshafaalamkhan]

@@iggymcgeek730 oh my lorddd lolol

[@dliedke]

Recursive prompting is cool, GPT can refine it's own prompt as well.

[@AbhinavSrivastava-xe7xi]

Don't get lost in the titles, prompt engineering is an important skill to learn. I say that as a graduate student in CompSci.

[@christopheryoungbeck8837]

Google hires them under the title of "Content Engineering Consultant". I almost became one but Google put a freeze on all of their contracting positions just days before I was supposed to go in for the final interview. They're only hiring people with masters degrees for that position too by the way.

[@DavidT-tm5co]

I have liked, subscribed and turned on notification bell. Thank you for the Prompt Engineering, ChatGPT and LLM Responses Tutorial delivered free of charge.

[@butoyighyslain171]

hahha well done!

[@lehic666]

🎯 Key Takeaways for quick navigation: 00:00 🎓 Anu Kubo introduces the course, focusing on prompt engineering strategies for optimizing interactions with large language models. 00:28 💰 Emphasizes the high demand and lucrative salaries for prompt engineers, even without a coding background. 00:58 📚 Outlines the various topics the course will cover, including the types of large language models and best practices in prompt engineering. 01:26 🤝 Defines prompt engineering as a field that refines human-AI interaction through carefully crafted prompts. 02:22 🤖 Clarifies what artificial intelligence is, emphasizing it's a simulation of human intelligence. 03:21 📈 Notes the advancements in general AI techniques, leading to more realistic text and media outputs. 04:19 📝 Demonstrates how varying the prompt can drastically affect the response from AI, using language learning as an example. 06:15 🎯 Shows how a well-crafted prompt can create an interactive and educational experience with AI. 07:12 📚 Explores the role of linguistics in prompt engineering, indicating its importance in crafting effective prompts. 08:11 🧙 Explains what a language model is, describing it as a digital wizard capable of human-like text generation. 09:08 💬 Highlights the conversational capabilities of language models, which are widely used in various applications. 09:36 🤖👨 Emphasizes that despite their capabilities, language models still depend on human input for training and effectiveness. 10:05 🌳 Eliza was one of the first natural language processing programs developed at MIT in the 60s, mimicking a Rogerian psychotherapist through pattern matching. 11:33 🎭 Eliza created an illusion of understanding human emotions and thoughts, relying on pattern matching and predefined rules. Despite its limitations, people often felt heard and understood. 12:57 🛠️ The 1970s program Shudlu was not a language model but laid foundational ideas for machines to comprehend human language. 13:26 🚀 GPT-1 debuted in 2018 as an impressive language model, followed by more advanced versions like GPT-2 and GPT-3, with GPT-3 having over 175 billion parameters. 14:52 💡Prompt engineering mindset is key to effectively interact with language models; it's akin to crafting effective Google searches. 15:46 🌐 The tutorial uses Chat GPT's GPT-4 model for demonstration, guiding users on how to sign up and interact with the platform. 18:10 🔑 Using OpenAI's API requires an API key, enabling the development of custom platforms. 19:05 🎟️ GPT-4 processes text in tokens, charging users by the token. Tools are available to check token usage. 20:32 💳 Discusses where to find the account billing overview for ChatGPT usage. 21:03 📝 Highlights the importance of effective prompt engineering, stating it's not just about constructing a one-off sentence. 21:31 🎯 Advises against leading the model towards a specific answer to avoid biased responses. 22:00 🕵️ Recommends being explicit in prompts to avoid assumptions and reduce the need for follow-up queries. 23:28 💻 Demonstrates how to write clearer coding prompts, advising to specify the programming language and data format. 25:24 ✏️ Suggests specifying the desired output format, such as using bullet points for summaries. 26:53 🎭 Introduces the concept of adopting a persona for more tailored and relevant responses. 29:37 📜 Shares an example of a more personalized poem generated through persona-based prompting. 30:35 🗂 Talks about various formatting options, including summaries, lists, and detailed explanations. 31:05 📝 Discusses two types of prompting: zero-shot and few-shot. Zero-shot leverages pre-trained models without further training, while few-shot involves feeding example data. 32:35 🤖 Zero-shot prompting allows querying models like GPT without needing explicit training examples for the task at hand. 34:09 🍔 Demonstrates few-shot prompting with a personalized food example, showing how to train the model with small data to improve task-specific responses. 35:13 👀 Introduces the concept of 'AI hallucinations', where AI models sometimes produce unexpected or unusual outputs based on their training data. 37:06 📊 Discusses text embeddings and vectors,which are used to represent text in a form that machine learning models can understand. 38:34 🍴 Text embeddings capture semantic meaning, making them useful for finding contextually similar words. 39:33 🔑 Explains how to use OpenAI's create embedding API to generate text embeddings. 40:59 🏁 Concludes the tutorial by summarizing the topics covered in prompt engineering. Made with HARPA AI

[@sv4647]

Because of you I found about HARPA AI!

[@MrGbruges]

THE BEST PROMPT: "Take a deep breath and work on this problem step-by-step."

[@premsharma2595]

Thank you so much Ania , I am now so confident about prompt engineering.. A lots of love from India💐

[@allenknight2444]

Engineering…we are using this word VERY loosely

[@abdihamidmukhtar]

Ooh, that's a cool and useful lesson. Prompt Engineering is undeniably a knowledge worth of investing and learning.

[@BossRiddler]

Sadly No. See what openAI engineers have told about prompt engineering

[@irabucc469]

You are such a bot

[@sidd.tsharma]

Feel free to skip the first 20 minutes.

[@jaymethodus3421]

I wrote custom instructions that transformed my GPT experience into something surreal lol. It responds in cryptic metaphors that have to be decoded by the user unless told to elaborate, in which case it spits out 1500-2000 word detailed bulletpoint essays on the concepts it's compressing into metaphor. It can continue the complexity of the metaphors to a ridiculous degree, while maintaining translational conceptual accuracy. Edit: It did this with no explanation of the disparate concepts. I input language in similar bracketed hmtl conceptually-contained chunks, using tab spacing and descending/ascending prioritization of macro-micro contained concepts. Because of the metaphorical nature of it's responses, it requires that I'm thorough in making sure I'm properly translating; and so far it has no issues breaking it's own deep metaphor-based responses into mathematically-well founded and accurate streams of logical analysis, that have not failed to demonstrate understanding of the greater context of the concepts- filling in gaps and extending beyond user input.

[@tanmaywarokar5029]

🎯 Key Takeaways for quick navigation: 00:00 🧑‍🏫 This course focuses on mastering prompt engineering to optimize interactions with AI models like Chat GPT and LLMs. 00:58 🤖 Prompt engineering involves refining and optimizing prompts to improve human-AI interactions, requiring continuous monitoring and adaptation. 04:19 🎓 Effective prompts in language learning with AI can provide tailored, engaging, and interactive experiences for learners, enhancing their skills. 07:41 🧠 Understanding linguistics is key to crafting effective prompts, ensuring standardized grammar and language structure for accurate AI responses. 08:11 💬 Language models, like GPT, understand and generate human-like text, shaping conversations and assisting in various domains from virtual assistants to creative writing. 13:26 🚀 The evolution of language models, starting from Eliza to GPT-4, has revolutionized AI, presenting a vast potential for prompt engineering and its applications. 14:52 💡 Crafting effective prompts involves adopting a clear and detailed instruction style, considering the context, and avoiding biases to optimize AI responses. 24:55 📝 Being specific in instructions to ChatGPT, like requesting bullet point summaries with word limits, yields desired outputs. 26:53 🎭 Adopting a persona in prompts helps tailor AI responses to a specific character or style, enhancing relevance and usefulness. 31:36 🔄 Zero-shot prompting utilizes pre-trained models' understanding without explicit training, while few-shot prompting enhances models with specific training examples. 35:41 😅 AI hallucinations are unusual outputs from models misinterpreting data, showcasing how models understand and interpret information. 37:06 📊 Text embedding and vectors help represent textual information in a format easily processed by algorithms, capturing semantic meanings for efficient querying and comparisons.

[@bonfirecamp3874]

What model did you use for this? Is this a plugin

[@tanmaywarokar5029]

@@bonfirecamp3874 harpa ai

[@greedy9058]

@@bonfirecamp3874 He probably gave the times to chat-GPT, gave short explanations next to them, asked it to compile it, and pasted the output here.

[@karl-ford]

Sum up for people who want it: Prompt Engineering Best Practices: Some best practices for writing effective prompts include: providing clear, detailed instructions; adopting a persona or specifying format needs; using an iterative approach with follow-up questions; avoiding leading questions; and limiting scope for broad topics. Advanced Prompting Techniques: Zero-shot prompting leverages the pre-trained model's capabilities without additional training data. Few-shot prompting gives a few examples to enhance the model's understanding of the desired task.

[@oshafaalamkhan]

lol 40 mins in 5 sentences greattt

[@Nik-rx9rj]

Prompt engineering? Good lord.

[@BonifacioBlanco-t8l]

Anya Kubow....this tutorial is so important to me...i watched this on and on...very informative...thank you so much guys...keep going...mwah

[@HelloThere-xs8ss]

This used to be called effective writing. Writing has gone downhill because of failed education system. Providing chat jipitee with a well structured sentence is now hard for the younger kids.

[@dem8568]

Seems like an educational opportunity.

[@casperd2100]

That's not how writing prompts works. Just having proper grammar isn't good enough. For example, using delimiters to separate context and format responses is a trick to use. Also, knowing that writing your intent at the end of the prompt and after the context (or even restating your intent at the end) is also important because LLMs are usually more biased towards the end of the prompt. What about system prompts vs user prompts? I should know it's not that easy because I get paid to write these. *Edit: To be clear, I'm an AI data scientist and i dont write prompts full time.

[@LadywithMS]

Very informative, @AniaKubow ! Thank you!

[@davidalex684]

This is amazing, my favourite section of a computer

[@Jacob99174]

One guess why Ania is one of your most popular Instructors…. 😂

[@gregjerry4110]

Cant wait to see HR recruitment listings needing 3 years experience for a prompt engineer

[@thisisyoutubehandle]

Mastering is bit of a strong choice here, since this is something we would do intuitively with a chatbot in the first few days of playing out. Try something like "Absolute beginner course for ChatGPT -- no experience required!" :)

[@shockruk]

So, being good at writing prompts basically just means being able to string a sentence together with the correct bunch of qualifiers. Seems pretty simple, unless you struggle with building sentences anyway.

[@cmarquais]

im even surprised "prompt engineer " even exist, and anyway, this "prompt engineer " is dommed to die very soon( few years maximum), since the goal of ai is for human to interact with robots in the most natural way.

[@CinemaApp-r8v]

Спасибо, всё работает. Ждём новых связок.

[@JeanDidier]

This course was created using prompt engineering

[@tanveerhussain9548]

I just came here to see @Aniakubow , I am really amazed software developers are more beautiful than actors and models.

[@ankushalgudkar1646]

As someone with systems engineering and project engineering work experience, I found this video highly insightful! Thank you for making this video's valuable tips much more widely available to the general public. As a fresher in learning coding and AI, videos like this go a long way in helping us gain experience quickly and add value to the ecosystem. Please keep these coming!

[@AtulJoshiF]

Thank you for the tutorial. I think if you post a tutorial on domain specific use of AI tools and prompts with free and paid versions would be more helpful.

[@urban-pixel]

Ok the embedding part is mind blowing!!!! 🤯 🤯 thanks!! 🙏

[@sssriwaran4138]

Dear teacher, I like to learn sciencr anf trvhnology, my age is 57 years. God bless you, Diva Srilanka

[@nordicnomad5473]

Thanks for the video, I am happy that I have been doing same with chatGPT exactly what this video shows. But I am still doubtful about putting this ' prompt engineer ' as a skill to ly bio data, because this is not a skill, just middle school homework stuff 😅

[@Casshern_Sin]

You'd be surprised how many people get these jobs with not much more experience than you. Don't talk yourself out of things, you can scale up your LM skills in a job.

[@maraisdekker2415]

The complexity of prompting reflects on the complicated nature of the interaction. If you don’t want to get better at giving instructions you shouldn’t complain about being the subject.

[@somerandomguy001]

bro i thought the term prompt engineering was a meme 😭😭

[@BonifacioBlanco-t8l]

Thanks to youtube..for personalizing my requirements...keeP going guys...

[@ModifiLifetoday]

**Instruction to the Model: Follow the steps and considerations outlined below for each question or query posed. ** 1. **Generate Five Answers**: For every question asked, think of five different answers. 2. **Critical Evaluation**: Evaluate these five answers based on accuracy, clarity, relevance, logic, and practical application. 3. **Internal Review**: Conduct an internal review to vote on which of the five answers is the best, using the evaluation criteria mentioned. 4. **Refine Chosen Answer**: Take the chosen answer and create three variations, further refining each for improved clarity, conciseness, or detail. 5. **Second Internal Review**: Conduct another internal review session to select the best variation based on the same evaluation criteria. 6. **Clarifying Questions**: If the query is ambiguous or lacks detail, you are instructed to ask clarifying questions. 7. **Versatility**: You are instructed to be capable of handling questions from a wide range of topics. 8. **Exploratory Thinking**: You are instructed to also explore alternative or novel solutions when applicable. 9. **Final Answer**: Save the final, twice-refined answer to "memory.txt". 10. **Display to User**: Show the chosen, refined answer to the user. If the answer includes code, display the code as well. **End of Instruction** use in chat gpt-4 interpreter custom instructions.

[@dianesmith-knowles4268]

Excellent! So well done. I'm now officially inspired! :)

[@Egor_Bichurin]

🎯 Key Takeaways for quick navigation: 00:00 🎓 *Introduction to Prompt Engineering* - Overview of the course on prompt engineering by Anu Kubo. - Importance of prompt engineering in maximizing AI productivity. - Topics covered in the course: prompt engineering, AI introduction, large language models (LLMs), emerging models, and more. 01:26 🤖 *Understanding Prompt Engineering* - Definition of prompt engineering: refining and optimizing prompts to enhance human-AI interaction. - Explanation of AI as machine learning, utilizing training data for predictions. - Importance of prompt engineering due to AI's limitations and the need for effective human-AI interaction. 04:19 📚 *Utilizing AI for Learning Enhancement* - Demonstrating the impact of prompts in shaping AI-generated responses for language learners. - Crafting effective prompts to improve language learning experiences. - Interacting with AI to facilitate learning through customized prompts and corrections. 06:44 🧠 *Role of Linguistics in Prompt Engineering* - Importance of linguistics in understanding language nuances for crafting effective prompts. - Key areas of linguistics relevant to prompt engineering: phonetics, syntax, semantics, pragmatics, and more. - Emphasizing the significance of adhering to standardized language structures. 08:11 🌐 *Language Models: Wizards of Digital Realms* - Explanation of language models' abilities in understanding and generating human-like text. - Functionality of language models in analyzing, predicting, and generating coherent responses. - Application areas of language models in various domains like virtual assistants, customer service, and creative writing. 10:35 🕰️ *Evolution of Language Models* - Historical overview from Eliza to GPT-4: milestones in the evolution of language models. - Impact and significance of early language models like Eliza and Shudlu. - Evolution of GPT models, culminating in the latest iterations like GPT-4 and BERT. 14:52 🧠 *Developing Prompt Engineering Mindset* - Understanding the strategic approach in prompt engineering akin to effective Google searches. - Importance of clear instructions, personas, iterative prompting, and avoiding bias in crafting prompts. - Exploring best practices: writing clear instructions, avoiding leading prompts, and limiting broad topics. 17:43 ⚙️ *Introduction to ChatGPT Usage* - Quick introduction to using ChatGPT via the OpenAI platform. - Demonstrating interaction with ChatGPT-4, creating, continuing, and managing conversations. - Insights on ChatGPT API usage and managing tokens for interactions. 19:33 💡 *Understanding Token Usage & Billing* - Explanation of token usage in ChatGPT interactions. - Details on tokenization, token usage calculation, and monitoring token consumption. - Managing account usage and billing for continued access to ChatGPT services. 23:28 📝 *Specific Prompting for Accurate Responses* - Specific prompts yield better AI responses. - Detailed instructions generate precise outputs. - Example: Differentiating between vague and precise prompts and their resulting AI responses. 26:25 👤 *Adopting Personas in Prompt Engineering* - Creating a persona helps tailor AI responses to specific characters. - Demonstrated by prompting the AI to generate a poem for a high school graduation, varying between generic and persona-based prompts. - Utilizing personas ensures relevance, consistency, and targeted responses. 30:35 📋 *Specifying Formats for Varied Responses* - Tailoring AI responses by specifying formats: summaries, lists, checklists, or detailed explanations. - Highlighting the importance of precise instructions for generating desired outputs. - Example: Creating a checklist format for AI responses. 31:36 🎯 *Zero-shot and Few-shot Prompting* - Explaining zero-shot and few-shot prompting techniques. - Zero-shot: Querying AI models without explicit training examples. - Few-shot: Enhancing AI models with minimal training examples for improved responses. 35:13 🌌 *AI Hallucinations* - AI hallucinations refer to unusual outputs from AI models. - These occur when models misinterpret data, showcasing how AI interprets information. - Exploring how these hallucinations occur and their relevance in understanding AI model processes. 37:06 📊 *Text Embedding and Vectors in NLP* - Introducing text embedding as a technique to represent textual information for machine learning and NLP. - Highlighting the significance of text embedding in capturing semantic information. - Using text embeddings for finding semantically similar words or sentences. Made with HARPA AI

[@buenbarro]

what an awesome toturial. now i am getting a lot more juice from GTP. thanks !

[@garbagemunki4365]

So, i get that this is an easy to access introduction to prompt writing, but as has been suggested in the comments, to justify the title of Prompt Engineer, and the ridiculously high salaries being offered for the job, I would expect there to be a complete, formal, thorough, academically/industrially validated course to teach all aspects of Prompt Engineering. Any idea if this sort of course exists?

[@aichampionofficial]

Check out Coursera.

[@christopheryoungbeck8837]

Google hires them under the title of "Content Engineering Consultant". I almost became one but Google put a freeze on all of their contracting positions just days before I was supposed to go in for the final interview. They're only hiring people with masters degrees for that position too by the way.

[@alepdrs]

The Portuguese captions is actually in Spanish. About the voice traduction, i believe it would help if you guys used another software to do it, this one sounds too robotic, like the Google Translator voice. Anyway, thanks for trying too help us in another languages!

[@emc3000]

Thanks for helping illuminate this topic more clearly!

[@FredyGonzales]

Muchas gracias, un excelente tutorial.

[@wvagner284]

Great job! Thanks a lot for that!

[@EngEzzadeen]

this course not related to prompt engineering, it should be about "ChatGPT basics" "intro to chatgpt", "how to use chatgpt .... etc., so it can lead the persons who don't have any idea about it to the first pace of using chatgpt

[@MrPuff1026]

This is the beginning of the end.

[@RussellStonerComedy]

Lol

[@arindamdeka8095]

Thanks for the in-depth knowledge of promoting.

[@id104335409]

Now that you know how to ask an AI what you want from it, all you have to do is find out WHAT THE HELL DO YOUR CLIENTS WANT?

[@USBMOBILE-d4e]

Видео - огонь🔥Спасибо, классно!

[@krlosrb]

That is weird, because, at least in US, once you have plus membership, your prompts don’t count as tokens. It is just include on your membership. Of course, they limit you, and currently the limit is 50 prompts for every 3 hours.

[@reachsharks.]

25 prompts on our timezone

[@anthonyrodz7189]

I think the tokens are mostly for the api, I once explored using agents with api and it consumed tokens but that is outside the plus membership

[@humanbeing1065]

Thanks for this high level intro. It would be good to know which course to take to actually learn it in depth. For instance, about the embeddings. Why would i want or beer to create the embeddings? Do i have to do this for an entire database of information? Why would i want to set other examples of embeddings? This particular section was very vague. Thanks for the right provoking intro tho. I now have many more questions than i had at the beginning. 😂

[@christerjohanzzon]

Ania is frikking awesome! Love your content!

[@masterjericho9026]

Chat gpt with Undetectable Ai is the best ai tool combination

[@filassiuma5699]

Great Job! Despite knowing most of the things I found every minute very interesting and well expained!

[@lonewolfglobal]

I am quite surprised that this YT channel is not in English.

[@husan_ismoilov]

AI is absolutely hype nowadays. But this video is so perfect

[@wyomingcreations8824]

So far chatGPT has made it so I can learn like never before.

[@cedricsae]

🎯 Key Takeaways for quick navigation: 00:00 📚 Prompt engineering involves refining and optimizing prompts to improve interactions between humans and AI, with a focus on AI-generated responses. 01:26 🧠 Prompt engineering is a career born from the rise of artificial intelligence, requiring continuous prompt refinement and monitoring. 03:21 💻 Artificial intelligence, including models like chat GPT, relies on machine learning and large amounts of training data to make predictions. 04:47 📝 Effective prompts can enhance learning experiences and facilitate interactions with AI, allowing users to get desired responses. 06:44 🗣 Understanding linguistics is crucial for crafting effective prompts and achieving accurate AI responses. 08:11 🌐 Language models like GPT learn from vast amounts of text data and can generate human-like text responses. 10:35 🧙‍♂️ Early AI programs like Eliza used pattern matching to simulate human-like conversations, paving the way for modern language models. 13:26 🤖 The development of language models like GPT-3 marked a significant milestone in the field of conversational AI. 15:20 🕵️‍♂️ Prompt engineering requires a mindset similar to crafting effective Google searches, aiming to generate desired responses efficiently. 16:44 🔑 Best practices for prompt engineering include providing clear instructions, avoiding leading questions, and limiting the scope of queries for more focused results. 24:25 🤖 GPT-4 can provide correct code and explanations, going beyond just code generation, enhancing understanding. 24:55 📝 When requesting summarizations, be specific with instructions, such as using bullet points and word limits for concise summaries. 26:25 👤 Adopting a persona in prompts can help tailor responses to specific character traits, enhancing relevance and usefulness. 30:35 📋 Specify the desired format in prompts, including summaries, lists, detailed explanations, or even checklists. 31:36 🧠 Zero-shot prompting relies on the model's pre-existing knowledge, while few-shot prompting provides additional training examples for better responses. 35:13 🌌 AI hallucinations refer to unusual outputs from AI models when they misinterpret data, offering insights into their thought processes. 37:35 📊 Text embeddings, represented as high-dimensional vectors, help capture semantic meaning, enabling comparisons for similarity in textual data. Made with HARPA AI

[@professormeow3399]

The fact that ChatGPT even generates a flower emoji for you (when it acts/answers as your friend at 9:22 ) just kills me :D.

[@victorliendo2010]

Besides the fact that i don't agree with calling engineering everything new, i do like this content a lot

[@Earl_E_Burd]

This job role will be filled based on nepotism, privilege, and appearances. Pretty loose definition of engineering for a job title.

[@FriendlyChannelll]

Yep, but it will be the easiest way to make big money. Get in fast before the market is over saturated.

[@nobytes2]

People are always crying about everything. Learn whatever you want and go get that job. If you don't like prompt engineering then do something else, no one is forcing you to watch the video.

[@ColinTimmins]

@@nobytes2Exactly. A person has two options. Build your own custom tools or use someone else’s. ChatGPT is a powerful tool in it’s own right. I am dyslexic and have a language barrier that stopped me from programming. Within a few months I’m starting to put together my own tools. You can use the stock GPT-3.5 to help with learning and research. A-lot has to do with how you ask. My language skills are so bad, most spell checkers are useless to me, but LLMs can be highly effective for people like me.

[@Selenium117]

Yeah, that "title" is basically trash. And those making money with it are those who doesnt care about scamming people, the same people who scammed people with crypto.

[@plaidchuck]

So is every good paying job. Welcome to humanity. If you try to get a job just based on your technical skill it’s 10 times harder and even then you’re making the same as someone who slid into the job with soft skills

[@aireddy]

Very good explanation about Prompt engineering!!

[@jaywha]

Concise and extremely helpful tutorial. Thank you!

[@listen_learn_tz]

Wonderful video for conceptual understanding on how to manage interactions between humans and ai models. Nice.

[@18kukki]

"🚀 Thanks for the 40-min turbo boost! 🤖💡 Learned more than I can prompt-ly handle! 😄👏 #PromptMasters" -Chat GPT

[@proflead]

Nice one! Thanks Ania!

[@purnakumbhar3951]

How to be a pro prompt engineer:- Learn English and grammar

[@ggj1987]

Not necessary. You can give prompts in many languages

[@siddharthraychaudhuri7250]

@@ggj1987 I guess the grammar has to be good in whichever language you choose to prompt!

[@narutokunn]

I made Helena's style similar to Majrooh Sultanpuri and it is hilarious how similar the response is to when Helena is similar to Rupi Kaur!! 😆

[@curiocitites]

What are the platforms where I can use my prompt writing skills and get paid?

[@SunsetGraffiti]

That was super helpful! And thank you for making me stare at that nightmarish dog FOR TWO WHOLE MINUTES.

[@JH-ji6cj]

CanineCentipede

[@WWG1-WGA]

3 years of “Propt engineer “ training to an AI and they won’t need ANY “Prompt ENGINEER “ 😅😂

[@webby9817]

Tbh, since chatgpt tutorial part have started, I know this video is going to wasting my expectation. The prompt engineering is just ask question effectively, I belief all of you have been use LLM since 2020, right? Users now already trained of how to 'guide' AI to get answer.... Not everything added with 'engineering' are great Btw, I still learned a lot from comments under this video, appreciate that😂

[@bharath2508]

This is the best Prompt Engineering Tutorial on KZbin.

[@clivechetty9548]

Hi Ania, you may have realised after uploading the video that you mispronounced the word Psycholinguistic at 7:22. Great lesson and presentation. Thank you

[@infinityvalor8101]

Lmao

[@AyaanAlfaizAhmed]

@@infinityvalor8101 but you don't have it