What is Generative Artificial intelligence?

Generative AI is a form of artificial intelligence that can produce content such as audio, text, code, video, images, and other data. While traditional AI algorithms can identify patterns within training data sets and make predictions, generative AI uses machine learning algorithms to create output based on training data sets.

Generative AI can produce output in the same medium where it’s given cues (for example, text-to-text) or in a different medium based on provided prompts (for example, text-to-image or image-to-video). Popular examples of generative AI include ChatGPT, DALL-E, MIDJERNEE, and DeepMind.

Key Takeaways

  • Generative AI, or Generative Artificial intelligence  , is a form of machine learning capable of producing various types of content like text, images, and more.
  • Examples of generative AI applications include ChatGPT, DALL-E, and BARD, which create text or images based on user prompts or conversations.
  • Generative AI is used across a wide range of industries, from creative and academic writing to translation, dubbing, editing, infographics, image editing, and more.
  • Generative AI raises significant concerns in legal, ethical, political, environmental, social, and economic realms.

How does Generative AI work?

Generative AI is a type of machine learning that operates without explicit programming, making predictions based on data it’s been trained on.
Specifically, for training models to generate new content, a generic AI model is trained on a large amount of existing content. Based on probability distributions, it learns to recognize underlying patterns in the data set and produces analogous patterns (or output) in response to commands.

Generative AI employs various models, such as Generative Adversarial Networks (GANs), Transformers, and Variational Autoencoders (VAEs), to train AI and create output using different techniques.

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Generative AI Interfaces
Wide-ranging AI applications have already transformed the way users interact with the digital world; for instance, voice-activated AI is now a standard feature on many phones, speakers, and other everyday devices.

Similar to this, several software interfaces allow consumers to communicate with generative AI. Early iterations of generative AI required data science or technical expertise to interact with the software; today, AI engineers are creating user interfaces that support hints and discussions in everyday language.

Some recent examples of generative AI interfaces include:


  • An example of a text-to-text generative AI is ChatGPT by OpenAI: an AI-powered chatbot trained to converse with users using natural language. Users can ask questions, engage in back-and-forth conversations, and prompt it to write text in various styles or formats, such as poetry, essays, stories, or recipes.
  • As of November 2022, a free version of ChatGPT is available online. OpenAI also offers an Application Programming Interface (API) for ChatGPT, among other enterprise membership and embedding options.


  • DALL-E is an example of a text-to-image generator AI released by OpenAI in January 2021. It utilizes a neural network trained on text descriptions to generate images.Users can enter evocative language, and DALL-E will generate photorealistic graphics using that text as inspiration.
    It can create variations in style and perspective within images.
  • DALL-E can also edit images, either by making changes within an image (known as inpainting in software) or by expanding an image beyond its original proportions or boundaries (known as outpainting).


BARD is a text-to-text generative AI interface based on Google’s large language model LaMDA (Language Model for Dialog Applications). Similar to ChatGPT, BARD is an AI-operated chatbot that can provide answers to questions based on user prompts or generate text.This is what Google refers to as a “enhanced experience for Google Search.”

Released in March 2023, BARD was made available for public use in the United States and the United Kingdom, with plans to expand to more languages and countries in the future.

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