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In today’s fast-changing digital world, Generative AI is a key player, changing the way we make, design, and use digital stuff. If you’re looking to boost your creativity and solve problems in new ways but don’t know where to start, this Generative AI tutorial is for you. It offers a simple step-by-step guide on how to write AI prompts that bring out the best in text and image AI tools. You’ll learn about what Generative AI can do and how to write prompts that avoid wrong or biased results. Plus, it’ll show you how to clearly explain your ideas to get consistent results, making it a must-read for anyone ready to explore the exciting possibilities of Generative AI.
When you think of AI, or Artificial Intelligence, what comes to mind? Perhaps you think of voice assistants like Alexa or Siri, or maybe AI tools like ChatGPT or AI Bard pop into your head. But what really is AI, and how does it function? Artificial Intelligence, in essence, refers to creating computer systems capable of performing tasks that usually require human intelligence. It’s similar to having a super-intelligent friend who can learn from information, make decisions, and carry out tasks without needing explicit programming for every action. AI operates through algorithms, which are essentially step-by-step instructions for processing data and making decisions. Imagine teaching a computer to learn from examples: it starts by gathering a vast amount of data, such as images of cats and dogs. Then, it learns to identify patterns within this data, like recognizing that cats often have pointy ears while dogs tend to have floppy ears. This process is at the heart of how AI interprets and interacts with the world around it.
Generative AI is a part of artificial intelligence that specializes in creating new content like text, images, music, and more, which is original and not just copied from already available examples. Unlike regular AI, which learns from data to find patterns or make predictions, generative AI takes it a step further. It studies the data it has and then uses what it learns to make completely new stuff, such as pictures or writing.
Generative AI algorithms often rely on deep learning frameworks like Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs). They learn to create fresh content by understanding the patterns within the training data and then using this understanding to generate new, realistic outputs. If you’re curious about what Generative Adversarial Networks or Variational Autoencoders are, you can join our Prompt Engineering Course with Generative AI course for a detailed explanation of these techniques. Essentially, GANs and VAEs are methods within artificial intelligence that generate new data, such as images or text, by leveraging patterns learned from existing data. GANs achieve this through a competitive process between a generator and a discriminator, while VAEs accomplish it by compressing and reconstructing data.
Prompt writing involves giving clear instructions or questions to guide the creation of written content. These prompts act as a starting point or framework to help organize thoughts and ideas. For instance, if your teacher asks you to write about climate change, that’s a prompt. Similarly, if someone gives you a sentence or a picture to inspire a story, that’s also a prompt. Using proper prompts is crucial because they provide clarity on what you need to write about, keeping you focused and organized, and making it easier to generate ideas and express yourself. Begin your journey to becoming a prompt engineer with our comprehensive guide and prompt engineering tutorial – uncover the essential steps and skills needed for success.
In this Generative AI tutorial for beginners, Let’s now delve into text-to-text generative AI. As the name implies, in text-to-text generative AI, you provide text-based prompts and anticipate a text output. It’s similar to having an intelligent computer that can both read and write text. Picture asking it a question and receiving a detailed answer, much like a knowledgeable friend would provide. Alternatively, give it a sentence, and it continues the narrative with additional sentences, similar to an imaginative storyteller. This AI comprehends written words and generates new text based on its knowledge. It’s like having a helpful writing companion who can brainstorm ideas, offer information, or even craft stories or articles for you. Text generation relies on machine learning, existing data, and past user input to produce responses.
Generative AI can be used to:
And much, much more!
But giving prompts to this generative AI is something that is going to make a difference in its effectiveness and that’s why there are some general rules that we follow during AI Prompt Writing. So, let’s have a look at them.
Rule 1) Start Simple – :
Start with a simple prompt, and then you can build on it.
Rule 2) Call to Action -:
Start the prompt with an action word like “Write”, “Create”, or “Summarize” instead of “Can you”
Rule 3) Add Context -:
Add specific and relevant context to the task you want to perform
Rule 4) Add Expectations:-
Add clear and direct expectations for the content, like how long it should be and what to include.
Now let’s have a look at some of the most trending Generative AI tools
1) ChatGPT-3.5
ChatGPT-3.5 is a smart AI Chatbot developed by OpenAI, which was launched in November 2022 This version of ChatGPT can talk with you, answer your questions, and assist with different tasks. Anyone can use ChatGPT-3.5 by creating an account with OpenAI. It knows a lot about many topics and can give detailed answers. However, some people have mentioned that ChatGPT-3.5 doesn’t always get things right. Now, to achieve an overall enhancement in technology and performance, ChatGPT-4 was introduced. Lets discuss about ChatGPT-4 in our Generative AI tutorial for beginners next topic.
2) ChatGPT-4
ChatGPT-4 is an updated version of ChatGPT-3.5 developed by OpenAI and was launched in April 2024. It’s a next-level up for chatGPT. This version is smarter and understands you better. It can handle more complex questions, give more detailed answers, and even understand pictures, not just words. So, it’s like ChatGPT 3.5, but with a major boost in skills and abilities.
3) ChatGPT-3.5 V/S ChatGPT-4
Features | ChatGPT-3.5 | ChatGPT-4 |
Training Data Availibility | Untill June 2021 | Up to September 2021 and beyond |
Model Parameter | 175 Billion | Over 1 trillion |
Corrections and Suggestions | Limited | Broader Range |
Safeguards | Less Improved | Improved (82% less likely to produce disallowed content) |
Coherence of Outputs | May be incoherent and lose track of topics | More believable and coherent |
Context Retention Capacity | Limited to 3,000 words | Extends to around 25,000 words |
Response Time | Within seconds | May take a minute or more for larger responses |
Have you ever imagined a cat wearing a wizard hat riding a skateboard? Or a picture showing a tiny city built on a leaf, complete with its little cars and houses. How about an image of a dinosaur and a unicorn having a picnic together? These ideas might sound whimsical or out of the ordinary, but thanks to an innovative kind of machine learning called text-to-image generation, they can be brought to life. This technology allows for the creation of vivid, lifelike images just from a simple text description, making even the most imaginative scenes possible to visualize.But How does it work?Let’s check that out.With text-to-image technology, you tell the computer what you want to see, like “an apple” or “a cat sitting on a couch,” and it creates a picture that looks just like what you described. You can even ask for something more detailed, like “a cute sloth holding a tiny treasure chest with a bright golden glow coming out of it.” Over the last few years, these systems have gotten really good because they’ve been shown tons of pictures and the words that describe them. This has made the pictures they create better and more varied.
Generative AI has revolutionized creativity by offering new ways to generate content like images, text, and music. As these technologies continue to advance, the possibilities for innovation and expression are endless, promising an exciting future of limitless creativity. If you’re curious about what Generative Adversarial Networks or Variational Autoencoders are, you can join our Gen AI course for a detailed explanation of these techniques.
Course Name | Date | Details |
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Prompt Engineering with Generative AI | Class Starts on 7th December,2024 7th December SAT&SUN (Weekend Batch) | View Details |
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