👉 Generation engineering is a field within artificial intelligence that focuses on creating systems capable of generating new, original content or data sequences, such as text, images, music, or videos. This process typically involves training machine learning models on large datasets to understand patterns and structures within the data, enabling them to produce novel outputs that mimic or extend the original data. Techniques often include deep learning architectures like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models, which learn to encode input data into a latent space and then decode it to generate new content. The goal is to produce outputs that are not only coherent and contextually relevant but also diverse and creative, pushing the boundaries of what AI can create.
