10 Practical Generative AI Examples to be More Productive

Despite being the focal point of the current tech market, it won’t be wrong to say that most of us have yet to harness the full potential of generative AI. Especially when it comes to various implementations and examples of generative AI. 

So, what is the best way to utilise generative AI’s competencies?

By understanding diverse individual examples of generative AI, you can acknowledge its various applications. 

Today, we’ll explore about ten of the most prominent use cases of Gen AI to help you use them better. Depending on your profession, some of these generative AI examples can increase your productivity by manifolds. So, let’s see what they are!

Top 10 Generative AI Examples

Allow us to offer you the top ten leading generative AI examples, revolutionising diverse realms with their innovative approach. 

• ChatGPT: Content Generation

• Jukebox: Music Creation

• Point-E: 3D Modelling

• RunwayML: Video Creation and Editor

• G3D.ai: Game Development

• LaMDA: Chatbots

• Dall E: Image Creation

• GitHub Copilot: Code Generation

• Midjourney: Art Creation

• Murf AI: Voice Generation

Understand the Basics of Generative AI

Generative AI is a subset of artificial intelligence that can generate content in diverse formats. Here’s a basic breakdown of how it works. 

1. Getting Trained on Data: To perform any task, first, the generative AI models need to be trained on massive datasets of existing content. This data can be retrieved from anything – books, blogs, pictures or images. 
2. Recognising Patterns: The algorithm then recognises patterns and relationships between various data sets based on all the retrieved training data.
3. Creating Content: Once the model has a good grasp of the patterns, it can use that knowledge to generate entirely new content. 

However, one crucial aspect to consider is using prompts. To achieve the desired outcomes, users need to add the right prompts, which is why prompt engineering is becoming a high-value career. 

There are no typical college curriculums on this subject yet. Rather, you can opt for a good Prompt Engineering course online to kickstart your journey. 

Why Should You Learn About Generative AI Examples? 

Whether you are a corporate employee, solopreneur or freelancer, you can always utilise generative AI to enhance your work processes. Here’s why you should work with Gen AI tools.

• Helps overcome creative blocks
• Automates things to streamline your process
• Helps in planning and organising
• Acts as a custom learning guide
• Analyse data and help make informed decisions
• Provide recommendations based on user preferences

Learning about GAI can help you in many ways. However, if you are completely unfamiliar with this subject, then there are many generative AI tutorials available online that you can check out. 

Notable Use Cases of Generative AI and Examples

The expansion of generative AI across multiple domains has led it to become a crucial partner in our day-to-day activities, right from creating content to working on code generation. Here are ten popular generative artificial intelligence applications in terms of performing tasks. 

1. Content Generation

AI can write different formats of content, from social media posts and marketing copy to news articles and even scripts. You can use popular models like ChatGPT-3, 4 or Jarvis to get help in this aspect. 

Currently, LLM is used in a few industries but in the future LLM will expand its applications in Education, Healthcare, Finance, etc. To know how LLM will be used in the future, Then enroll in our LLM engineering course today!

2. Music Creation

Generative AI can compose music in diverse genres and even create accompaniments to existing pieces. Jukebox by OpenAI is an example that many people use for producing musical pieces. It can create music belonging to diverse genres solely from text descriptions.  

Generative AI is performing unbelievable activities. After the GPT-4 invention, AI became too popular in all industries. GPT-4 creates new content by extracting the text from images, music, etc, and giving accurate results like humans. To know more about these generative AI, Then understanding of AI basics is more important. To know more enroll in our AI for Beginners course today!

3. 3D Modelling

Generative AI has greatly simplified the process of 3D modelling. Generative AI can create 3D models from text descriptions or even 2D images. Point-E by OpenAI is a popular tool for this function.

4. Video Creation and Editing 

Generative AI can automate repetitive tasks in video editing or even generate entirely new video content. One example is RunwayML, which is an AI video editing tool famous for generating realistic backgrounds or adding special effects.

5. Game Development 

Almost 62% of the developers in big gaming companies use AI to improve their productivity. They use it to create game environments, characters and even storylines. G3D.ai is a good example that allows game developers to build game worlds using text descriptions.

6. Chatbots and Virtual Assistants

People are incorporating generative AI with chatbots to facilitate natural conversations. This helps the language model better understand user intent and respond in a way that mimics human dialogue. Some popular models include LaMDA from Google AI and BlenderBot 3 from Meta. 

In the banking sector, AI tools are replacing humans by doing activities like fraud detection, loan approval processes, predicting financial data, analyzing customer behavior, etc. It saves time and cost. To know more enroll in our AI tools course today!

7. Image Creation and Editing

Generative AI is now capable of creating realistic images from scratch, simply based on text descriptions. It can also edit existing images in various ways, like adding/removing elements or changing styles. DALL-E 2 from OpenAI is a powerhouse in this field. 

8. Code Generation

People with limited coding knowledge can now leverage generative AI to simplify coding processes for themselves. Generative AI can help programmers by automatically generating code snippets, completing functions or even writing entire programs based on user specifications. GitHub Copilot is a popular choice among programmers. 

In the upcoming years, we can expect unbelievable AI domination in software development. Future AI will innovate new smarter debugging tools and it will increase the efficiency of generating advanced coding with good quality. To create your future AI tool, Then enroll in our GitHub Copilot Training Course today!

By using AI in finance, Fraud activities like identity theft, credit card fraud, phishing scams, etc. can be avoided. It prevents organizations from financial losses and damage reputations, etc. To know how AI is preventing fraud activities in the finance sector enroll in our AI For Finance Course today!

9. Art Creation 

Budding artists no longer need to master complicated illustration software to make their imaginations into reality. Generative AI like Midjourney can create unique and artistic images in various styles, inspiring artists and designers. 

10. Voice Generation

With apps like MurfAI, GAI can also create realistic-sounding human speech, which is useful for narration, audiobooks as well as creating personalised voice assistants. A lot of anonymous social media channels already use this for their long or short-form videos. 

Real-world Examples of Gen AI

• Visual Content for Architecture: Visual content generation through AI technology is being widely used by architects and planners to create a visual model of their dream projects. From buildings to their interiors, visual content generation capabilities are enabling architects and designers to bring their imagined plans on screen.
• Audio Generation for Music: Musicians and creative composers are utilising Gen AI audio generation applications to create unique and innovative compositions within a very limited amount of time. For people who are facing a creative slump, this can be a breath of fresh air!
• Text Generation: Text generation capabilities are being utilised by language translators as a support system to strengthen their translation abilities and to provide people with maximum accuracy. Whatever your choice of language is, language models and text generators are available to offer their assistance.
• Code Generation: Streamlining a week’s worth of work within hours, code generation platforms have emerged as a boon for software developers and engineers who struggle to work on repetitive coding tasks.

Industries Experimenting With Generative AI Tools

Apart from the creative fields, here are some core industries actively experimenting with Gen AI technology. 

Cautionary Note on Applying Generative AI

GAI is a powerful tool, however, it has its specific set of limitations. Here are things you should be mindful of when using generative AI. 

1. Gen AI models can give biased results as they are trained on massive datasets. If the dataset has any biases, then it will influence the outputs. 
2. Gen AI can give inaccurate facts and stats, so double-check the data. 
3. The outcomes are mostly unique but are ultimately inspired by existing content. Hence, you may have to struggle with copyright or originality issues. 

Future Generative AI Examples

Generative AI Perceiving the rapid growth of AI-led innovations, generative AI predicts an optimistic future with new applications emerging in the upcoming days. Here are some of the GAI applications that we can expect soon. 

Personalised Learning

Generative AI has already been revolutionising the way people acquire information, and in the coming days, it is aiming to take its power to the next level. By offering personalised learning for students, Gen AI will transform the learning experience to a more tailored approach, enabling the algorithm to evaluate patterns and to work on specifically tackling them.

Drug Discovery

Generative AI is set to impact pharmaceutical companies by helping them with drug discovery.  From unlocking disease mechanisms to predicting molecular properties of diverse compounds, Gen AI is assisting pharma corporations assess insights and patterns and as a result, creating impactful progress in the field of drug discovery. 

Immersive Story Telling

By leveraging generative AI practices to create realistic characters, story backdrops and other supportive elements, creative leaders are on their way to create immersive storytelling experiences. Interactive narratives will also be explored under this practice, creating a well-rounded storytelling experience which will be much more engaging.

Conclusion

The potential applications of generative AI are vast and constantly expanding. As technology progresses, we expect to see massive breakthroughs that will greatly impact different aspects of our lives soon, hopefully for the good. To keep up with these emerging and innovative technologies, you may want to improve your skills by taking popular courses provided by top online training platforms like Edureka.

One such program is the Gen AI course offered by Edureka online if you want to explore more about this growing technology. 

Generative AI Examples FAQs

• What is generative AI? Provide an example.

Generative AI is a subset of AI technology that can produce content in different formats, usually with the help of text prompts. A popular example of generative AI is ChatGPT. 

• What is the most popular generative AI?

Currently, the most popular Generative AI tools include ChatGPT and DALL-E 2, both created by OpenAI. 

• Where is generative AI being used?

From creative fields to research and development, Gen AI has many use cases. One such use case is the creation of high-quality images using text prompts with Midjourney AI.

• Is Google a generative AI?

No, Google is a search engine. However, Google is also harnessing the power of generative AI to improve search experience for users.