The emergence of generative artificial intelligence (AI) indicates a paradigm shift in military research and application, ...

For instance, Vannevar Labs, a defense tech company, provided the U.S. military with generative AI tools in November 2024, securing a $99 million contract with the Pentagon’s Defense Innovation ...

The seminal paper “Generative Adversarial Nets” introduced the adversarial process of GANs. Although this paper does not mention deepfakes, it was the springboard for GAN-based deepfakes.

Generative adversarial networks (GANs) have been effective for learning generative models for real-world data. However, accompanied with the generative tasks becoming more and more challenging, ...

GenAI, on the other hand, creates new content — such as images, text, videos, or synthetic data — leveraging deep learning methods such as generative adversarial networks (GANs).

Generative AI’s promises for the software development lifecycle (SDLC)—code that writes itself, fully automated test generation, and developers who spend more time innovating than debugging ...

Various generative AI models, including transformer-based models, GANs, and diffusion models, are trained through different processes involving large-scale data, neural networks, and methods like ...

In the new paradigm for generative AI, the development process is very different from how it used to be. The overall idea is that you initially pick your generative AI model or models. Then you ...

Generative Adversarial Networks Generative Adversarial Networks (GANs) emerged in 2014 and quickly became one of the most effective models for generating synthetic content, both text and images.