What Is Generative AI | How Generative AI Works | Generative AI Explained | Edureka

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In this video on “what is generative AI”, we’ll explore concepts like technologies applying advanced algorithms such as generative adversarial networks and autoencoders to analyze data and produce novel images, sounds, and media based on identified patterns. Discover why generative AI has become so important for artists, designers, researchers, and creators in many different fields. It introduces viewers to the platform’s accessibility and functionality, highlighting how individuals can interact with it to produce their own distinctive creations. We’ll explore the reasons behind its growing popularity and how it’s changing the way people work and create. Learn about the journey of generative AI, where the evolution from its beginnings to the latest advancements.

✅ 00:00 – Introduction To Generative AI
✅ 01:32 – Large Language Model (LLM)
✅ 03:04 – Application of Generative AI
✅ 06:53 – Why Generative AI?
✅ 07:41 – Models of Generative AI
✅ 09:38 – Evolution of Generative AI

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Introduction of Generative AI?
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.*GAI provides and generates the needed for text ,videos,audios and other data using generative models often to stimuli. That’s how it makes all the human life more simplifying and directing. It aids in creative endeavors by generating ideas, designs, and content across various domains.

Why Generative AI?
Generative AI enhances decision-making processes by providing valuable insights, augmenting data analysis, and enabling scenario simulations. By generating diverse and realistic options, generative AI helps decision-makers explore alternative strategies, assess potential outcomes, and make informed choices and also they are the major economic growth.

Models of Generative AI?
Their primary function is to understand and capture the underlying patterns or distributions from a given set of data. Once these patterns are learned, the model can then generate new data that shares similar characteristics with the original dataset. Generative AI also has models that are used to improve the quality of the datasets and a additional information to the original dataset but which is not previously seen. The models are made and generated by the data that is trained with the use of main AI algorithms with allow to train the data and synthesis the new characteristic.

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