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Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers

2023-11-17 00:08:19
Staphord Bengesi, Hoda El-Sayed, Md Kamruzzaman Sarker, Yao Houkpati, John Irungu, Timothy Oladunni

Abstract

The launch of ChatGPT has garnered global attention, marking a significant milestone in the field of Generative Artificial Intelligence. While Generative AI has been in effect for the past decade, the introduction of ChatGPT has ignited a new wave of research and innovation in the AI domain. This surge in interest has led to the development and release of numerous cutting-edge tools, such as Bard, Stable Diffusion, DALL-E, Make-A-Video, Runway ML, and Jukebox, among others. These tools exhibit remarkable capabilities, encompassing tasks ranging from text generation and music composition, image creation, video production, code generation, and even scientific work. They are built upon various state-of-the-art models, including Stable Diffusion, transformer models like GPT-3 (recent GPT-4), variational autoencoders, and generative adversarial networks. This advancement in Generative AI presents a wealth of exciting opportunities and, simultaneously, unprecedented challenges. Throughout this paper, we have explored these state-of-the-art models, the diverse array of tasks they can accomplish, the challenges they pose, and the promising future of Generative Artificial Intelligence.

Abstract (translated)

ChatGPT的发布吸引了全球关注,标志着生成人工智能(Generative Artificial Intelligence,简称GAI)领域的一个重要里程碑。虽然生成人工智能(GAI)在过去十年里已经存在,但ChatGPT的引入引发了对AI领域的全新研究和技术创新的激情。这一兴趣激增导致了诸如Bard、Stable Diffusion、DALL-E、Make-A-Video、Runway ML和Jukebox等众多尖端工具的开发和发布。这些工具表现出非凡的能力,涵盖从文本生成和音乐创作到图像创建、视频制作、代码生成和科学工作的各种任务。它们基于各种最先进的模型,包括Stable Diffusion、Transformer模型(如GPT-3,最近发布的GPT-4)以及变分自编码器(VAE)和生成对抗网络(GAN)。这一生成人工智能的进步为人们带来了丰富的令人兴奋的机会,同时也带来了前所未有的挑战。在本文中,我们探讨了这些最先进的模型,它们可以实现的各种任务,它们所面临的问题以及生成人工智能令人担忧的前景。

URL

https://arxiv.org/abs/2311.10242

PDF

https://arxiv.org/pdf/2311.10242.pdf


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