Generative AI is an artificial intelligence technology that uses deep learning models to create high-quality, realistic content, including text, images, audio, and video. Generative AI analyzes and identifies patterns in large data sets and then uses that information to create new content from the shared characteristics of the original data set, based on prompts from the user.
Generative AI is not necessarily a new technology. Its origin stems from 1960s technology used to power early chatbots. The 2014 discovery of Generative Adversarial Networks (GANs), which leveraged opposing generator and discriminator neural networks, led to the creation of realistic imagery and audio with AI, which was integral in shaping the generative AI models available for mainstream use today.
Transformers, a type of machine learning that can process large sets of unlabeled data and identify connections between words and information, and Large Language Models (LLMs), have further shaped modern generative AI capabilities, and the rapid adoption of accessible and user-friendly platforms such as ChatGPT.
Generative AI is gaining momentum as all types of organizations discover the benefits and use cases of using this technology to create and scale content efforts. The following are some of the most popular generative AI categories.
Seamless.AI / Murf / NeuralDB Enterprise / Xyonix / Steve AI / AI Studios / Jasper / Katonic / Observe.AI / LivePerson
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