Adversarial

Artificial intelligence (AI) offers transformative potential across industries, yet its vulnerability to adversarial attacks poses significant risks. Adversarial attacks, in which meticulously crafted inputs deceive AI models, can undermine system reliability, safety, and security. This article explores key strategies for mitigating adversarial manipulation and ensuring robust operations in real-world applications. Understanding the Threat Adversarial attacks target inherent sensitivities within machine learning models.…

Application of GANs for data augmentation to adjust an imbalanced datasetPhoto by Brett Jordan on Unsplash“Generative Adversarial Nets” (GANs) demonstrated outstanding performance in generating realistic synthetic data which are indistinguishable from the real data in the past. Unfortunately, GANs caught the public’s attention because of its unethical applications, deepfakes (Knight, 2018).This article illustrates a case with a good motive in the application of GANs in the context of fraud detection.Fraud detection is an…

Nested bi-level optimization and equilibrium seeking objectiveIntroductionGenerative Adversarial Networks (GAN) demonstrated outstanding performance in generating realistic synthetic data which were indistinguishable from the real data. Unfortunately, GAN caught the public’s attention because of its illegit applications, Deep Fake. (Knight, 2018)As its name suggests, Generative Adversarial Nets (GAN) is composed of two networks: the generative network (the generator) and the adversarial network (the discriminator).…

The rise of Generative Artificial Intelligence (GenAI) has introduced innovative services and cutting-edge tools to automate tasks, optimize processes, and speed up transactions. These benefits make it more enticing for businesses to deploy AI services for their expansion and growth strategies. One important technological breakthrough that has made this growth possible is the conditional generative adversarial network (CGAN). What Are Generative Adversarial Networks? Before diving in, we first need to explain the “GAN” in…

NEW YORK CITY—Amidst rock music, a rap about consciousness, and the calling in of a 25-year-old drunken bet, camps backing two leading theories of how consciousness arises from the brain waited anxiously in a Greenwich village theater on Friday to hear who had won the first round of an ambitious “adversarial collaboration.” Three neutral judges chosen to help design the experiment and evaluate the results gave a qualified victory to advocates of the idea that…

Introduction In this modern and innovative world, individuals are capable enough to get what they see. The role of artificial intelligence would be simultaneously straightforward in that case. Artificial intelligence is one of the most famous data-driven technologies emerging at a swift pace, accommodating the whole world. There would be no surprise in saying that the market size of artificial intelligence is growing dramatically and will reshape the dimensions of technological advancements in the upcoming future. In…

It is not hard — at all — to trick today’s chatbots into discussing taboo topics, regurgitating bigoted content and spreading misinformation. That’s why AI pioneer Anthropic has imbued its generative AI, Claude, with a mix of 10 secret principles of fairness, which it unveiled in March. In a blog post Tuesday, the company further explained how its Constitutional AI system is designed and how it is intended to operate. Normally, when an generative AI model is being trained, there’s a human in the loop to provide quality…

Top 10 project ideas that are based on generative adversarial networks for your next project Earlier this year, MyHeritage’s Deep Nostalgia, which used AI technology to bring old photos to life, took the world by storm. People all over the world were captivated by the results because seeing your deceased loved ones in action again, smiling and moving, was an emotional experience. Images of many famous people, including freedom fighters, renowned scientist’s activists, researchers, and authors, were animated and shared on…

How GANs work and how you can use them to synthesize dataFig. 1 — Synthetic images of a person, generated entirely by a GAN. Image source: https://thispersondoesnotexist.com/ . License: https://github.com/lucidrains/stylegan2-pytorch/blob/master/LICENSE (MIT)If you’re working in deep learning, you’ve probably heard of GANs, or Generative Adversarial Networks (Goodfellow et al, 2014). In this post we will explain what GANs are, and discuss some use cases with real examples. I am adding to this post a link to my GAN…

Here’s how to build a generative Deep Learning model for Signal Processing in a few lines of codePhoto by Michael Dziedzic on UnsplashIn my research, I use Machine (Deep) Learning a lot. Two days ago, I was working on Generative Adversarial Network (GAN) and seeing how I can apply it to my work.After the code was ready, I started writing this article on Medium and I tried to find the best words to start with a proper introduction, as I always do.I start asking myself questions like:“Why should a reader read this? Why what…