What are Examples of Generative AI tools?
- Art and Music: Generative AI tools help to create pictures that show the beauty of art and also compose music in multiple styles. One such application is DeepArt or DeepDream tool which helps find and enhance patterns images. by using a Convolutional Neural Network. For music, there is one tool MuseNet is a deep learning model that can compose music in multiple styles.
- Text Generation: Generative AI extended its powers to text generation, It produces human-like content that is based on the given input by the user. Gpt-3 developed by Open AI is one such application that can generate text as per the need of the user such as content creation, programming help, and numerous applications.
- Deepfake Creation: There is one of the most famous technologies of generative AI is Deepfake which uses GANs to swap faces in videos. It is an image or a video recording that uses an algorithm to replace the person in the original video or image with someone else.
- Game Development: Generative AI is also used in game development, AI Dungeon is a text-based adventure game that uses the GPT-3 to generate a dynamic storyline that is based on user input.
- Drug Discovery: Prediction of the efficacy and toxicity of the drug compound is one of the main parts of AI in medicinal chemistry.
- 3D Object Generation: Generative AI assists in object generation. Generative AI tools like NVIDIA’s GauGAN allow users to create 3D landscapes by drawing simple handmade sketches and pictures.
What is Generative AI?
Nowadays as we all know the power of Artificial Intelligence is developing day by day, and after the introduction of Generative AI is taking creativity to the next level Generative AI is a subset of Deep learning that is again a part of Artificial Intelligence.
In this article, we will explore,
What is Generative AI? Examples, Definition, Models and limitations.
Generative AI helps to create new artificial content or data that includes Images, Videos, Music, or even 3D models without any effort required by humans. The advancements in LLM have led to the development of Generative AI.
Generative AI models are trained and learn the datasets and design within the data based on large datasets and Patterns. They can generate new examples that are similar to the training data. These models are capable of generating new content without any human instructions.
In simple words, It generally involves training AI models to understand different patterns and structures within existing data and using that to generate new original data.