Generative AI refers to a subset of artificial intelligence (AI) techniques that are focused on creating or generating new content, such as images, music, text, or even entire virtual worlds. Unlike other AI approaches that are mainly focused on recognizing or analyzing existing data, generative AI models are designed to generate new data that resembles or is similar to the training data they were trained on. Generative AI models often utilize deep learning techniques, particularly generative adversarial networks (GANs) or variational autoencoders (VAEs). These models learn patterns and structures from a given dataset and then generate new data samples based on that learned information. Generative AI has various applications, such as: 1. Image synthesis: Generating realistic images or altering existing images to create new variations. 2. Text generation: Creating new text content, including natural language generation, story writing, or even code generation. 3. Music composition: Generating new musical compositions or improvisations. 4. Virtual reality and gaming: Creating virtual worlds, characters, or objects in gaming or virtual reality experiences. 5. Data augmentation: Generating synthetic data to augment existing datasets for training machine learning models. Generative AI has gained significant attention and popularity in recent years due to its ability to create novel and creative outputs. However, it also presents challenges, such as ensuring the generated content is ethical, avoiding biases in the generated data, and addressing potential misuse, such as deepfake technology.
Note: The answer I just provided was generated by a generative AI!
Generative AI is a a type of AI that can make things up. Think of it as a creative AI that can produce new and realistic outputs without being explicitly programmed.
Lets learn it with a metaphor.
You have 2 kids .
1 is talented loves to make picture. Another one is boss who knows how the picture look like.
So you asked the talented one to make a picture of something and show it to the boss one .
Now the talented one tries to draw and show it to the boss kid. The boss kid says it isnt ok. You have some mistakes here and there. So the kid tries to fix those untill the boss kid is happy.
This is how a generative ai works. 2 model competing each other. One is finding error another one is fixing errors.
It has a similarity with Reinforcement learning.
Generative Artificial Intelligence (Generative AI) in images refers to a type of algorithms within deep learning that aim to generate new and synthetic data that are similar or consistent with some existing data. These models can be generative from random noise or based on an existing image, depending on what is to be generated. The general idea is to be clear about what will be the origin to enter into AI (such as random noise or a base image) and what will be the destination (the generated data). In a simple way, a distribution of data from the origin and destination is made, and deep learning algorithms are used to approximate the data distribution from the origin to the destination. Among the most well-known and used models today for these purposes are the Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and the Generative Transformer, among others.
In my particular experience, I designed a model based on GANs that has two stages. In the first, I use a GAN where the origin is random noise of numbers, and I apply the Wasserstein metric to approximate the data distribution from the origin to the distribution of peripheral blood cells. The result (destination) of this process is a low-resolution image. In the second stage, I employ the same generative concept of GAN but in an image-to-image approach. This means that I will approximate the data distribution from one image to another to improve its quality. This is achieved through techniques such as Pix2Pix, which allow for precise transformation of the features of one image into another, maintaining certain attributes while modifying others. If you want to know the work in depth, I invite you to read the publication: Article Automatic generation of artificial images of leukocytes and ...
Generative AI is a type of artificial intelligence that can create new content, such as text, images, or music, by learning patterns from existing data and generating similar, original output. Generative AI creates new content by learning from existing data and generating original output
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