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Welcome to Dissecting Technology

Dissecting Technology focuses on educating you on the latest research in information technology, particularly in artificial intelligence, with a major focus on computer vision. Today on dissecting technology, I will be educating you on the topic “Imagen”

DEFINITION OF TERMS

  • Artificial intelligence: refers to systems or machines that mimic human intelligence to perform tasks and continuously improve themselves based on the information they collect.
  • Machine learning (ML): is a subset of artificial intelligence devoted to understanding and building methods that ‘learn’; that is, methods that leverage data to improve performance on some set of tasks.
  • Machine learning algorithms: Builds a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.
  • Computer vision: is a field of artificial intelligence that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs and can take actions or make recommendations based on the information.
  • Machine learning model: Represents what was learned by a machine learning algorithm.
  • Transformer: is a deep learning model that uses a self-attention process and weights the importance of each component of the input data differently.
  • Diffusion model: A model that generates data similar to the data on which it is trained.

IMAGEN

“Imagen” is one of the Google research projects on CVPR by the Brain Team, which was posted on May 23, 2022. You may click here to learn more: https://imagen.research.google/

Imagen is an AI system that creates high-quality, realistic images from input text. Imagen leverages the power of large transformer language models in understanding text and depends on the strength of diffusion models to create highly realistic and quality images.

WATCH IMAGEN ON YOUTUBE:

https://youtu.be/VGi29lVDpuo

With the use of Imagen, some high-quality images have been created, which are displayed below.

LIMITATION

Imagen generates a range of social and cultural biases when generating images of activities, events, and objects.

RELEVANCE

To produce high-quality images of people, events, places, and animals through the use of text. That is, Imagen should be able to generate a high-quality image of any kind through an input text description.

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