In this section we will see the different types of Generative AI which is used these days.
Generative AI - What are different types of Generative AI?
In the previous section we have learned the basic details about Generative AI or Generative Artificial Intelligence. In this section we will see the types of Generative AI popular in today's world and how it is being used in different industries.
The Generative AI is all about generating the new contents based on the user input. Users can ask the Generative AI model to answer something or generate content on some topic, then the model will understand the user's internet and generate content for him.
What are the types of data generated by Generative AI?
Generative AI models of current time are very powerful and still these are being upgraded or re-developed from scratch to add more intelligence. The type of data it can generate depends on the training data supplied to these models at the time of training. If it is trained with the text data then it should be able to generate text content. If it is trained with the image data then it should be able to generate images or paintings. So, there are unlimited potential and use cases in the different industries.
Now we will see what type of data it can generate?
In short, Generative AI can generate data based on the data on to which it is trained. For example if you train in images then it will be able to generate images. If trained with text then it can generate emails, text, books, questions and answers etc..
These days it is mostly used for the generation of following types of data:
- Text Data
- Synthetic data
- Scientific and Research data
Let's see all these in detail.
Text Data Generation
Generation of text data such as emails, articles, blog posts, or marketing contents are the popular uses of Generative AI among command Internet users. Generative AI can also be used for SEO Keyword research or finding the topics for the content. Users are also able to find the information that they are using in their academics. So, there are lots of potential use cases of text data generation.
Image or Graphics Generations
People are using well trained Generative AI models for generating the images and graphics for their websites, advertisement material, and painting for various uses. These models are pre-trained and able to generate high quality unique images for various personal and business use cases.
People are also using such models to generate realistic portraits, relevant images for advertising and making images for their specific work. This is one of the best use cases of Generative AI where people can generate quality images.
Audio and Music Generation
Well trained Generative AI model will be able to generate audio of different types such as music, text voice over, various sound effects and even audiobooks. There are many ways people are using these days in their videos and audio books. In future the use of such models will increase very fast.
Video Clip or Full Video Generation
If you are planning to make Videos for advertisements or for your YouTube channel then you don't have to go out to take actual videos. Now with the help of Generative AI people are generating videos very fast for their business or some other purposes. There are many reports of generating videos for YouTube, which resulted in huge income for the video creator. So, in the coming days we will see upward trends in the use of such Generative AI models.
Companies are also generating TV shows, creating movies , creating cartoon videos, developing videos for virtual reality and many more. If you have ideas then you can easily generate audio/video and through this you will be able to earn as well.
Generating Synthetic Data for Model Training
Now it's very easy to generate synthetic data for machine learning and deep learning purposes. With the help of Generative AI models you can generate data which can be used effectively for model training, software testing, model validation and some case simulation of some use cases.
Beside this it can also be used for the generation of financial data, medical data, scientific data, research related data, social media data and many others.
There are a lot of high stack use cases of Generative AI and many companies have already started exploring the issues of these technologies in their business. Due to its high impact on business companies like Google, OpenAI and others working hard to improve their Generative AI models. Generative AI technologies are evolving fast and technology is under heavy development. In the coming days we will see huge use of this model in various businesses.
We have seen the various ways Generative AI models can be used by individuals and companies. Now we will understand the different types of Generative AI.
What are different types of Generative AI?
Generative AI is a deep learning mode or combination of multiple models trained with large amounts of data so that it can achieve content generation intelligence. These models are developed using different complex mathematical algorithms.
Here is the list of some of the common types of Generative AI Model which can be trained for data generation:
- Generative Adversarial Networks (GANs)
- Variational Autoencoders (VAEs)
- Recurrent Neural Networks (RNNs)
- Autoregressive Models
- Deep Boltzmann Machines (DBMs)
- Reinforcement Learning-based Models
Pre-Trained Generative AI Models
There is a huge cost of Generative AI models training, so small companies and individuals can't train these models. So, big companies like Google, Microsoft, OpenAI and others trained the model and released (some free and others paid). Here are list of pre-trained Generative AI Models:
- Google Bard
- GPT-3, GPT-4 and ChatGPT
- GitHub Copilot
- DALL·E 2
- Bing Search
- Bing Chat
In this section we have seen different types of Generative AI Models and understood what type of data these models can generate. These models will help users in generating text of different types, images, videos, audios and musics.