Generative AI is an artificial intelligence technology where an AI model can produce content in the form of text, images, audio and video by predicting the next word or pixel based on large datasets it has been trained on. This means that users can provide specific prompts for the AI to generate original content, such as producing an essay on dark matter or a Van Gogh-style depiction of ducks playing poker.
While generative AI has been around since the 1960s, it has significantly evolved thanks to advancements in natural language processing and the introduction of Generative Adversarial Networks (GANs) and transformers. GANs comprise two neural networks that compete with each other. One creates fake outputs disguised as real data, and the other distinguishes between artificial and real data, improving their techniques through deep learning.
Transformers, first introduced by Google in 2017, help AI models process and understand natural language by drawing connections between billions of pages of text they have been trained on, resulting in highly accurate and complex outputs. Large Language Models (LLMs), which have billions or even trillions of parameters, are able to generate fluent, grammatically correct text, making them among the most successful applications of transformer models.
To read more – https://www.leewayhertz.com/generative-ai-architecture-for-enterprises/
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